Rob Scott sits down with Josie Gaeckle, Senior Vice President of Client Insights at SMG, to break down how Unified Experience Management is turning data into revenue, retention, and ROI.

How does improving customer experience actually impact revenue? Josie reveals why many organizations struggle to show ROI: siloed data, lack of analytical maturity, and disjointed ownership of customer, employee, and brand experiences. But it doesn’t have to stay that way.

SMG’s approach to Unified Experience Management—bringing together customer, employee, and brand feedback into a single data ecosystem—helps organizations connect the dots between action and outcomes.

Discover why experience metrics aren’t enough without linking them to business metrics. Learn how predictive analytics and AI are reshaping the ROI conversation. Hear a real-world case study from Sally Beauty that ties associate behavior to average spend. Explore how cross-functional alignment with finance and operations is the secret to scaling success. Josie also offers a future-focused look at how prescriptive AI and real-time journey analytics are redefining what’s possible for CX leaders in 2026 and beyond.

NEXT STEPS: Want to see how SMG’s Ignite® platform helps brands drive measurable experience improvements? Visit smg.com to learn more.

Looking for more thought leadership on CX strategy? Subscribe to CX Today and don’t miss our upcoming interviews with industry leaders shaping the future of experience.

For enterprises, that’s both a challenge and an opportunity. Handled properly, feedback reveals exactly where things are and aren’t working. It tells support teams which moments frustrate. It tells product teams what’s missing, and it tells the C-suite what customers value enough to fight for.

That’s the real job of customer feedback management, turning scattered input into structured insight, then routing it to the teams that can actually do something with it.

The best CFM systems don’t just capture data. They:

• Map feedback across the full journey, not just surveys
• Spot trends early, before they show up in churn
• Connect insight directly to actions: faster support, better products, clearer messaging

In short, modern customer feedback management platforms give enterprises a new kind of muscle: the ability to listen deeply, move early, and improve continuously

What is Customer Feedback Management?

Customer feedback management is the discipline of collecting, interpreting, and acting on customer sentiment – not just from surveys, but from every channel where customers leave a mark.

That might mean tracking a drop in CSAT after a product update, combing through live chat logs, or decoding a two-star review on Trustpilot. In most enterprise settings, it means building a feedback loop that crosses teams: product, marketing, service, and operations all relying on the same source of truth.

The best customer feedback management software doesn’t just store responses. It translates them into structured insight, surfacing trends, routing complaints, and pushing alerts to the right place, fast. It’s the glue between listening and resolution.

To work at scale, feedback systems typically include:

• Multichannel ingestion: Web forms, support tickets, NPS, app reviews, even social DMs. Every signal matters, even if it’s unstructured.
• Theme detection and prioritization: Tools flag repeat issues or keyword clusters before they become reputational risks.
• Workflow integration: A refund complaint can notify finance. A delivery bug can trigger a ticket in product ops.
• Dashboards and reporting: With the help of AI systems, leaders get a filtered view of real insights by product line, geography, or channel.

Leading companies aren’t collecting feedback in a vacuum. They’re wiring it directly into CRM systems, contact center tools frontline workflows, so the right people can act without delay. The tighter the integration, the faster teams can respond, fix what’s broken, and strengthen customer relationships that last.

Where Feedback Fits: Feedback Management, VoC, and EFM

Feedback is only useful if it leads somewhere. That’s where terminology starts to matter. Voice of the Customer (VoC), customer feedback management, and enterprise feedback management (EFM) are often used interchangeably. They shouldn’t be.

Customer feedback management is the engine room. It handles collection, sorting, tagging, and routing. Think of it as the operational layer that turns raw input from surveys, ratings, and comments into tasks and decisions. This is where data moves from inboxes and dashboards into action plans.

Voice of the Customer (VoC) goes broader. It doesn’t just listen to what customers say, it listens to how they feel, how they behave, and where they’re frustrated or delighted without necessarily saying it outright. A good VoC program blends direct feedback with behavioral signals and sentiment analysis. It’s about seeing the full picture.

Enterprise feedback management (EFM) stretches even further. It includes employee and partner insight, compliance triggers, internal process reviews, and often sits closer to risk management than CX. In highly regulated or distributed organizations, EFM is essential infrastructure.

At enterprise scale, feedback management isn’t just a support tool. It’s part of the system of record: connected to customer data platforms, CRMs, business intelligence tools, and employee engagement systems (WEM tools).

Each of these frameworks adds something. The most mature organizations use all three as parts of one loop: listen, understand, and act.

What is Customer Feedback Management? Feedback Types

Customer feedback isn’t always a form or a star rating. It’s often informal, unstructured, or buried in systems where no one’s looking. Recognizing the different types is the first step toward building something that works across departments and channels.

• Direct Feedback: The most visible kind. Surveys after support calls. CSAT and NPS prompts. Product reviews submitted through apps or portals. It’s usually structured, timestamped, and easy to analyze. But it’s also the most filtered. The people who answer tend to be at the emotional extremes, either thrilled or annoyed. Everyone else stays quiet.
• Indirect Feedback: This is what customers say when they’re not talking to you directly. Tweets. Public forum threads. Online reviews. Complaints posted to third-party sites. In many organizations, this insight slips through the cracks. But today’s customer feedback management platforms use NLP and sentiment tools to bring these comments into view before they become brand problems.
• Inferred Feedback: This is the feedback customers don’t say out loud, but show in what they do. Dropping out halfway through checkout. Asking the same question in three different places. Bouncing between help pages without finding what they need.

On their own, these signals can be easy to miss. But together, they reveal patterns of frustration that direct surveys might never surface.

Why Customer Feedback Management Matters

There’s no shortage of dashboards in a modern enterprise. But few of them speak with the voice of the customer. That’s what feedback management changes. It shifts insight from lagging reports to live reality, focusing on the real-time pulse of what customers need, want, and expect.

For enterprise leaders focused on customer experience, this isn’t a soft metric. It’s operational. According to Bain & Company, companies that excel at customer experience grow revenues 4%–8% above their market. But growth doesn’t come from tracking satisfaction scores alone. It comes from turning those scores into action.

Here’s where feedback becomes a business driver:

• Alignment Across Teams: Sales hears one thing. Support hears another. Product has a third backlog entirely. When feedback lives in separate systems, teams solve different problems. When it’s centralized, patterns emerge, and teams move in the same direction.
• Early Signal Detection: A broken link on a signup form. A billing process that’s confusing in one region. A surge in cancellation requests. Customer feedback management platforms surface these issues before they hit churn reports. The earlier the fix, the lower the cost.
• Smarter Roadmapping: Feedback isn’t just a support signal, it’s a product roadmap tool. Tracking customer insights, linking them to outcomes, and activating responses leads to strategic action. Teams can prioritize features that drive loyalty.
• Competitive Advantage: Every brand says it listens. Few can prove it. Companies that consistently close the loop visibly earn trust. In a market where switching costs are low, trust is often the only real moat.

The case for customer feedback management software isn’t just about efficiency. It’s about agility, spotting the next risk or opportunity while competitors are still guessing.

How to Build a Customer Feedback Management System That Works

Enterprises don’t lack feedback. They’re swimming in it. The challenge isn’t collection, but coordination. Scattered responses, siloed ownership, and no clear plan for what happens next. That’s where customer feedback management becomes a system, not just a task.

1. Start with What You Already Have

Before adding new tools or channels, map what’s in play. Most enterprise teams already gather feedback across:

• Post-interaction surveys
• Help desk conversations
• Social and review platforms
• Product feedback forms
• Sales and account notes

But it’s often fragmented, or locked in spreadsheets, CRM fields, and third-party platforms. Start by listing every touchpoint where customers leave a trace. Then identify who owns that data, how it’s reviewed, and whether it drives action.

2. Build a Shared System, Not Just a Repository

A true customer feedback management system isn’t just a bucket. It’s a hub. One place where cross-functional teams can view, analyze, and act on insights. That requires more than storage. It needs structure. Look for tools that:

• Integrate with your CRM system and CDP
• Tag feedback by source, product line, sentiment, urgency
• Offer role-specific dashboards for ops, product, CX, compliance
• Allow for routing, escalation, and response tracking

Consider other integrations that might be helpful too, such as connections to your ERP and business intelligence platforms, or workforce management tools.

3. Design a Feedback-to-Action Pathway

Without clear ownership, feedback dies in the backlog. Teams need to agree on what gets prioritized, who responds, and how it loops back into service design, training, or product fixes.

The strongest systems:

• Flag urgent or high-impact issues automatically
• Route insights to the right teams (with deadlines)
• Track outcomes, not just volume
• Communicate resolution back to the customer

When that loop works, feedback becomes part of how the business runs.

How to Use Feedback to Improve Business Results

Most companies collect feedback. Fewer actually do something meaningful with it. In mature organizations, feedback isn’t just a sentiment report, it’s a driver of change. Done right, it informs strategy, sharpens execution, and reduces churn.

• Prioritize patterns over outliers: It’s easy to get caught up in the latest complaint or viral review. But high-performing teams step back. They look for volume, frequency, and trends, not just anecdotes. That could mean mapping repeat issues to product features, or tracking common service pain points over time.
• Feed insight to the right systems: Don’t keep customer feedback on a CX dashboard. Use it to inform product roadmaps, workforce planning, pricing models, training strategies, and anything else that impacts the customer experience.
• Expand your metrics: Go beyond NPS and CSAT. Think about customer effort scores, overall retention rates and churn. Determine the KPIs you want to keep track of in advance, and make sure everyone is watching them, including the C-Suite.

Choosing Customer Feedback Management Software

Customer feedback is everywhere. What separates good companies from great ones is what they do with it. That’s where the right customer feedback management software comes in, to make insights actionable, accountable, and accessible across the enterprise.

Start With the Business, Not the Tool

Software selection should begin with the problems it’s meant to solve. Are customers dropping off after onboarding? Or are service complaints slipping through the cracks? Are product teams getting insight too late to act?

Clear goals tend to point to the right tool:

• Real-time alerts for contact center agents?
• Text analytics for unstructured NPS comments?
• Trend reporting to inform product roadmaps?

Once those use cases are clear, it becomes easier to separate the platforms built for scale from those that just tick boxes.

Integration Over Isolation

In a modern tech stack, no system should sit alone, especially not feedback.

Customer insights gain power when connected to:

• CRM platforms, where individual records tell a full customer story
• Contact center solutions, where timing and channel matter
• CDPs, which consolidate behavioral and transactional data
• BI tools, for deeper cross-functional reporting
• Broader ERP, WEM, and business management tools

Make sure your platforms feed the systems powering decisions.

Think Long-Term: Governance, Scalability, and Fit

Even the most powerful platform will struggle without strong foundations. For enterprise buyers, that means focusing on operational readiness:

• Can the system support multiple teams and regions with clear permissions?
• Are escalation workflows and approvals built in?
• Does the vendor offer strong uptime guarantees and compliance controls?
• Is the reporting flexible enough to satisfy both executive leadership and front-line teams?

Ease of use matters too. If agents, analysts, and leaders can’t find value in it quickly, feedback won’t flow where it’s needed most.

Discover the best customer feedback management solutions:

Customer Feedback Management Best Practices

Technology may capture customer sentiment, but it’s what companies do next that separates good intentions from real improvement. At the enterprise level, feedback shapes products, and defines brand reputation, retention, and revenue.

Here’s what the most effective teams get right.

• Track consistently: Feedback isn’t a file to review later. It’s a feed that’s active and ongoing. Companies need to review regularly, discuss in depth, and build around it.
• Make feedback cross functional: Operations needs visibility into service complaints, marketing needs to know where messaging misses, and HR should see how poor feedback is affecting teams. Get everyone involved.
• Close the loop: Replying to feedback, or acting on it, is crucial. Customers want to know their input mattered, and teams want confirmation their fix was felt. Ensure that your action is clear, powerful, and visible.
• Read between the lines: Surveys are useful, but raw behavior can say more. Combine behavioral insights, structured survey data, and conversational analytics for a comprehensive view of what customers really feel, not just what they say.
• Make it easy to act: Help teams fix issues quickly. Check if workflows are in place for feedback routing, and whether CX agents can escalate recurring problems. Give people the tools they need to act.

Customer Feedback Management Trends

Customer expectations haven’t just shifted, they’ve splintered. Channels have multiplied. Responses move faster. The tools used to manage it all are catching up. Here’s what’s defining feedback management right now:

The Rise of AI-Powered Analysis

Enterprise teams spent years circling AI as a concept. Now it’s operational. The strongest feedback systems today don’t just categorize responses, they break them down by tone, urgency, and underlying cause.

Platforms like Medallia, NICE, and Sprinklr are using natural language processing and conversational analytics to surface issues before they mutate. Instead of waiting for quarterly survey analysis, teams can spot sentiment drops and recurring themes as they happen.

Feedback Is Becoming Embedded

Feedback used to live in standalone forms: a survey here, a rating box there. That’s changing. Leading platforms now capture signals from everyday interactions: chat logs, call transcripts, even app usage.

Feedback is moving closer to the moment. A delivery delay triggers a quick prompt. A cancelled subscription opens the door to ask why. Systems are listening all the time, and they’re getting smarter about what to listen for.

Structured Feedback Loses Traction

It’s not just about ticking boxes. The most valuable insights often show up in open comments, social threads, or long-form email replies. That unstructured data used to be hard to sort. Now, it’s where the action is.

Enterprises are investing in platforms that can handle nuance: that can understand sarcasm, spot emotion, and cluster feedback without a human reading every line. Forrester calls this shift “human insight at scale”, and it’s showing up as a core capability in nearly every customer feedback management platform leader.

Everything Connects Or It Doesn’t Work

Feedback is most valuable when it flows. Into support platforms, product roadmaps, agent scripts, and CX dashboards. But that only happens when systems talk to each other.

Leading tools now integrate out-of-the-box with CRMs, contact center systems, VoC platforms, and enterprise resource planning (ERP) solutions. That allows customer concerns to influence decision-making across the business, not just in service.

Privacy Remains Crucial

The line between “listening” and “surveilling” is thin, and enterprise buyers know it. In a post-GDPR, opt-out-default world, customer feedback strategies need to include transparency.

That means clear consent prompts. Data handling disclosures. Anonymization features. Especially in regulated sectors, ethics now sit beside analytics in the buyer’s checklist.

What is Customer Feedback Management? The Voice of CX

Customer feedback management It affects product decisions, shapes brand reputation, and drives loyalty at scale.

Done well, it connects dots across departments, from support and sales to marketing and operations. It puts real-time customer truth in front of the people who can do something about it.

But it only works when the systems are connected, the insights are trusted, and the loop is truly closed. That’s why enterprise teams are investing in modern customer feedback management platforms to operationalize input.

For companies focused on loyalty, innovation, and experience, the question isn’t whether to invest in customer feedback tools. The only real question is: which one will help you act faster, and smarter? CX Today is here to help:

• Join the Community: Be part of a dynamic CX-focused network. Swap ideas with thought leaders and elevate your feedback strategy.
• Test the Tech: Discover the top-rated platforms, meet vendors, and explore trends at live and virtual events.
• Plan Your Next Investment: Use our CX Marketplace to explore top vendors in feedback, VoC, CDP, and contact center tech.

Or visit the ultimate CX guide for enterprise experience leaders, for insights into how to build a better CX strategy, one step at a time.

A loyal customer isn’t just someone who comes back. They spend more. Stay longer. Recommend faster. They open emails, tolerate hiccups, and ignore your competitors’ ads. They’re also far cheaper to retain than any lead your sales team is chasing right now.

Loyalty isn’t a lucky break. It’s the outcome of moments that go right consistently, and often quietly. A first experience that flows without friction. A support interaction that resolves more than just the issue. A product that keeps its promise. Each of these moments builds equity in the relationship.

When those touchpoints connect  across teams, systems, and time something stronger than repeat business takes shape. Customers begin to trust. They stick around, not because it’s the easiest option, but because the experience earns it.

What is Customer Loyalty?

Customer loyalty reflects a decision: the conscious choice to stay with a brand when alternatives are just a click away. It’s not just about satisfaction, plenty of satisfied customers churn. Loyalty runs deeper. It’s emotional, earned through consistency, value, and trust built over time.

In practical terms, loyalty shows when customers return after a poor experience, because they believe it’s the exception, not the norm. It shines when existing buyers refer peers, opt into updates, or upgrade without needing a discount.

But for enterprises, this isn’t a soft metric. It’s measurable, in retention rates, customer lifetime value, and referral growth. In fact, increasing customer retention by just 5% can boost profits by 25% to 95% depending on the industry. Loyalty doesn’t just pay off; it compounds.

Now, it matters more than ever. With CX as a key battleground, loyalty becomes a lead indicator of business resilience, and a hedge against rising acquisition costs.

The ROI of Customer Loyalty

Customer loyalty used to be a feel-good metric. Now it’s a board-level priority.

Retaining a customer isn’t just cheaper than winning a new one, it’s smarter. The cost of acquisition has spiked over 60% in the last five years, especially across digital channels. Meanwhile, repeat customers spend more, refer faster, and support brands longer, even when things go wrong.

The return is measurable:

• CAC Down, Margins Up: Brands with strong loyalty programs don’t need to outspend rivals on ads. Their customers come back organically. Acquisition costs are up to 7x higher than retention costs, and rising. Loyalty brings those numbers down.
• Predictable Revenue: Returning customers are more consistent. They know the product, trust the brand, and often skip the comparison stage altogether. That makes forecasting easier, pipelines more stable, and marketing spend more efficient.
• Loyalty = Resilience: In downturns, loyal customers stick. They’re more forgiving of glitches and slower to churn. A loyalty strategy isn’t just about growth, it’s about survival when market headwinds hit.
• Better Intelligence: Good loyalty tools are also listening tools. They track not just transactions, but behavior: redemptions, preferences, referrals, and feedback. That kind of data can feed customer journey strategies and help pinpoint why loyalty is rising or falling.
• Cross-Functional Buy-In: Loyalty isn’t a marketing-only game anymore. When programs sync with CRMs and support channels, they empower every team that touches the customer and help break down the silos that usually hurt CX.

What is Customer Loyalty Management?

Loyalty isn’t a byproduct of good service; it’s the result of managing relationships with intent. For enterprises, customer loyalty management is the discipline of designing and maintaining systems that keep the right customers coming back, staying longer, and contributing more value over time.

Loyalty doesn’t come from running rewards programs on cruise control. It starts with clarity; knowing who your most valuable customers are, what keeps them engaged, and how to stand out even when competitors promise more for less.

The best loyalty strategies don’t operate in a silo. They’re part of the broader customer experience engine, connected to feedback, support, product usage, and behavioural cues. Managed well, these strategies turn loyalty into a dynamic input, not just a passive output. It’s not a metric at the end of a funnel, it’s something built and reinforced at every stage of the journey.

Loyalty Management Tools and Platforms

The strongest tools today aren’t just managing point balances or sending birthday emails. They’re helping organizations understand loyalty as a behavior, not a program.

At a basic level, these platforms centralize loyalty data: engagement patterns, redemption activity, repeat purchase signals, and more. But the more advanced systems go further. They apply machine learning to spot early signs of churn, flag disengaged segments, and recommend next-best actions in real time.

What sets the leading loyalty management platforms apart is their ability to fit inside a broader CX tech stack. That means:

• Integrating with CRM to unify customer context
• Connecting to feedback loops for real-time insight
• Embedding in messaging infrastructure like CPaaS to deliver hyper-personalized moments that actually land

Many also support predictive analytics, using behavioral data to calculate loyalty risk scores, tailor rewards dynamically, or prompt human intervention when relationships are at risk.

How to Measure Customer Loyalty

Loyalty isn’t a single number. It’s a pattern, and like most patterns in enterprise CX, it takes a mix of metrics to see the full picture.

Behavioral signals still lead the pack. Metrics like repeat purchase rate, frequency of interaction, average order value, and churn give a direct read on what customers are doing, and where that behavior changes over time.

Behavioural signals often say more than surveys. A customer who slows their spending, skips repeat purchases, or stops logging in is sending a message. Something has shifted, in the experience, the product fit, or the perceived value.

Behaviour tells you what happened. But it won’t tell you why. That’s where customer sentiment comes into play.

Tools like Net Promoter Score (NPS), Customer Satisfaction (CSAT), and Customer Effort Score (CES) dig beneath the surface, giving teams a clearer sense of how customers actually feel about their experience. When behavioural dips show up, they offer the context needed to act fast, and fix the root cause before it costs more.

For many organizations, this layer is captured across touchpoints with VoC tools, then analyzed over time to correlate sentiment with spend or attrition.

What’s changing now is the rise of emotional loyalty metrics. These tools look beyond direct feedback, using conversational analysis, sentiment trends, and inferred emotional cues to understand attachment, not just satisfaction. It’s especially useful for brands competing on experience, not price.

Taken together, these data points create a more reliable model. Not just who’s loyal today, but who’s likely to stay, spend, and advocate tomorrow.

How to Choose Loyalty Management Software

The wrong loyalty platform won’t break a business, but it will stall progress. What looks slick in a demo can crumble under pressure if it can’t sync with existing systems, surface usable insights, or grow with you.

Enterprise teams evaluating loyalty management software need more than a feature checklist. They need to know how the tool will hold up six months in, with multiple departments relying on it.

Here’s what separates the useful from the disruptive:

True Integration

No platform works in isolation. If loyalty data sits in a separate bucket from customer service, CRM, or analytics tools, there’s a problem.

That means:

• Real-time syncing with CRM systems
• Alignment with VoC platforms
• Integrations with Business intelligence solutions

Most loyalty management platforms also seamlessly connect with CCaaS platforms, conversational analytics tools, and ERP software.

Dashboards That Get Used

Too many platforms surface metrics. Fewer tell you what they mean.

The strongest systems flag what matters: declining engagement from a once-loyal segment, a regional drop in redemption rates, churn triggers hiding in feedback. Ideally, these insights feed into broader customer intelligence tools.

Ask the vendor: When loyalty starts to dip, how will your platform show it, and who will know?

Scalability

Will it handle loyalty across multiple brands? Markets? Languages? Can it adapt to tiered models, emotional loyalty, partner programs?

Look for:

• Configurable logic, not hard-coded structures
• Clean admin interfaces for rule management
• Role-based controls that keep compliance teams comfortable

If it takes a developer to adjust a points rule, it’s not enterprise-ready.

Discover who’s driving results in the loyalty management software market here:

Best Practices for Improving Customer Loyalty

Loyalty doesn’t just emerge from a points program or a fun campaign. For enterprises, it’s a byproduct of consistent, intentional experience design, built into service flows, product strategy, data models, and frontline decision-making.

Build Feedback Loops That Actually Close

The fastest way to erode loyalty? Ignoring input – or worse, asking for it and doing nothing.

Instead of measuring feedback volume, measure action: How many product updates were driven by complaints? How often are support teams looped in to resolve themes emerging from surveys? Connect your loyalty program to customer feedback management tools that can drive real changes, not just reporting.

Use Tiering: But Don’t Let It Turn Transactional

Tiered loyalty still has its place, but only when it’s designed with purpose. Value shouldn’t just reflect spend. It should acknowledge engagement in all its forms. Early adopters, advocates, testers, even those who provide consistent feedback – they’re all part of the loyalty equation.

In B2B especially, tiers work best when they reflect mutual success. Think retention milestones, shared KPIs, or collaborative innovation, not just contract size.

Let AI Do More Than Segment

Yes, AI can slice customer cohorts faster. But real value comes when it flags what’s slipping before it shows up in churn.

Modern loyalty management tools increasingly come with predictive features: surfacing customers at risk of disengagement, nudging reps to check in, or adjusting loyalty offers based on sentiment and behavior patterns. Don’t just use AI to automate, use it to alert.

Tie Service Quality to Loyalty Outcomes

When loyalty starts to dip, it’s often not marketing’s fault, it’s a missed service expectation, or a support gap that never got escalated.

Bring loyalty and service metrics closer together. Track whether NPS dips after a long resolution time. Monitor whether loyalty program members get faster assistance, and whether that’s noticed.

Reward the Behavior You Want More Of

Discounts create habits, and not always good ones. If you reward spend alone, you build deal-seekers, not advocates.

Instead, reward the moments that drive growth:

• Referrals
• Feedback submitted
• Community contributions
• Self-service engagement
• Event participation

Loyalty isn’t a transaction, it’s a signal. Recognize the signals that drive real business value.

Localize Where It Matters

For multinational brands, loyalty can’t be global by default. Preferences shift by market, so should campaigns.

Consider:

• Local holiday-based promotions
• Regional tier naming conventions
• Local influencers or ambassadors

Global strategy. Local flavor. That balance keeps loyalty human.

Customer Loyalty Management + Service: The Critical Link

Loyalty doesn’t just live in a dashboard or a rewards app. It’s won or lost in moments that often feel small: a delivery delay, a billing dispute, a misunderstood policy. The way a brand responds in these moments is often more influential than any discount or points tier.

And that makes customer service a cornerstone of customer loyalty management.

When Service Is Seamless, Loyalty Feels Earned

Customers don’t demand flawlessness. But they do expect clarity, speed, and respect when things go wrong. Loyalty isn’t tested during moments of delight, it’s tested when something breaks. Support teams who can see a customer’s history, loyalty status, and previous interactions don’t just fix problems faster. They solve them with more context, more care, and often, more impact.

This is where integration matters:

• CRM systems should surface loyalty data
• CPaaS platforms can enable proactive outreach
• Ticketing systems can reflect VIP status or churn risk

Proactive Service = Preventative Loyalty Loss

The best loyalty moves aren’t reactive. They’re invisible, because the problem was handled before the customer noticed.

For example:

• Flagging shipping delays and sending apologies before the complaint
• Alerting high-value customers when products they love are low in stock
• Following up after negative sentiment is detected in chatbot interactions

This requires orchestration. But the payoff is reduced escalation volume, increased trust, and loyalty built on more than transactions.

Empower Agents Like They’re Brand Ambassadors

Loyalty lives or dies with the agent experience. If the frontline team feels unsupported, overworked, or stuck with legacy tools, they can’t deliver the kind of service that loyalty depends on.

Modern workforce engagement platforms are helping here, giving agents better training, clearer knowledge bases, and visibility into customer journeys. This isn’t just an ops upgrade, it’s a loyalty investment.

Customer Loyalty Management Trends to Watch

Enterprise loyalty strategies evolve with the customer, and the customer continues to change.

Over the past two years, loyalty has shifted from tactical marketing add-on to boardroom-level priority. Why? Because retention has become the fastest route to stable revenue.

Here’s what’s changing right now.

• Loyalty Is Getting Smarter: Rather than shouting about rewards, top brands are building invisible loyalty, systems that work behind the scenes, adjusting experiences based on behavior, purchase history, and product use. The loyalty isn’t in the point balance. It’s in the recognition. AI and predictive analytics are playing a bigger role here, helping teams act on churn signals before the customer ever says a word.
• Emotional Loyalty Takes the Lead: Price cuts don’t build loyalty. They build expectations. Enterprise buyers are shifting from transactional incentives to emotional loyalty strategies, things like exclusive experiences, consistent service, and values-based alignment. In B2B markets, that might look like strategic co-development, VIP access to product roadmaps, or account-based reward systems.
• Loyalty Hardwired Into CX: The strongest loyalty programs don’t operate in isolation. They’re woven into the wider customer experience stack, touching CRM, CPaaS, contact center platforms, and data systems. This allows brands to reward customers in real time, based on meaningful actions, not just spend.
• Consent-First Design: The days of collecting data “because we can” are over. Modern loyalty programs are being rebuilt around trust and transparency. That means clear value exchanges, upfront permissions, and control for the customer. Loyalty is no longer about how much data you can gather, it’s about how responsibly you use what you have.

Customer Loyalty Management Beyond the Transaction

Customer loyalty isn’t a finish line. It’s an ongoing, intentional outcome earned across every interaction, reinforced with every decision, and protected by every system put in place.

For enterprise teams, managing that loyalty means more than launching a rewards program. Managing loyalty well means making it easier for customers to stay than to leave. That’s not about discounts or perks, it’s about designing experiences that feel effortless, relevant, and personal.

Whether the goal is improving retention, boosting lifetime value, or gaining a clearer view of customer behaviour, the right strategy starts with the right tools, and the right insights.

CX Today offers a range of resources to help enterprise teams build loyalty systems that actually move the needle:

• Explore the Marketplace: Compare top loyalty management vendors with features tailored for growth, data integration, and security at scale.
• Join the Community: Learn how CX and marketing leaders across industries are evolving loyalty strategies in the CX Community.
• Track What’s Changing: Follow new developments in AI-powered loyalty, cross-channel experience design, and customer journey intelligence with research reports.

See how loyalty fits into the broader CX ecosystem. Visit our Ultimate CX Guide for a practical deep dive into the people, platforms, and processes driving customer-led growth.

This new partnership will have both companies co-developing AI-focused strategies to market to global customers. 

This partnership will also allow both to expand AI productivity on their respective platforms. 

ServiceNow and NTT DATA have begun their joint plans to market AI-driven solutions, including developing and selling these products to transform how AI is used in the workplace. 

These are set to include various enterprises, commercial companies, and mid-market segments. 

This new strategy emphasizes the companies’ previous partnerships, focusing on their commitments to advise other enterprises to adopt and execute AI into their businesses. 

ServiceNow also intends to use the expanded partnership to place NTT DATA as a delivery partner in its services to guide customers in safely deploying AI-powered automations and enhance operational efficiency. 

Amit Zavery, President, COO, and CPO at ServiceNow, highlighted how this new partnership development will improve AI across businesses, stating:

“ServiceNow and NTT DATA are expanding access to AI-powered automation across any industry and any geography to achieve measurable business impact for organizations at every stage of the AI journey, 

“Together, we’re transforming how the world’s leading enterprises operate, making work simpler, smarter, and more resilient with the ServiceNow AI Platform.”

NTT DATA will be using the partnership to escalate the ServiceNow AI platform to its business to improve its levels of productivity, efficiency, and make improvements to its customer experience across the enterprise, by adopting its AI agents and Global Business Services. 

Abhijit Dubey, President, CEO, and Chief AI Officer at NTT DATA, emphasizes how the partnership can benefit both NTT DATA and other enterprises. He said:

“Expanding our partnership with ServiceNow is a key milestone in our mission to build the world’s leading AI-native services company,”  

“By combining ServiceNow’s agentic AI platform with NTT DATA’s global delivery scale and industry expertise, we’re enabling enterprises to accelerate innovation, enhance productivity, and achieve sustainable growth.” 

Who is NTT DATA?

The technology services company provides enterprises and governments with responsible innovations for cloud, AI, security, data centers, connectivity, and application services. 

This latest partnership allows NTT DATA to access ServiceNow’s generative AI and workflow automation, enabling it to supply improved offerings to its customers by integrating more complex solutions, positioning itself as a leader of enterprise AI transformation within the industry. 

NTT DATA can also use this opportunity to expand its market reach by co-developing AI tools with a well-established company, especially in the US and Europe, where ServiceNow holds strong brand recognition. 

What This Partnership Means

This partnership expansion reflects the increasing intensification of AI-led transformation investments amongst current major vendors. 

The collaboration allows both companies to become more central in their position as leaders in enterprise software strategy development, highlighting to other vendors where they stand to build better relationships instead of developing capabilities independently. 

By fully aligning operations such as products and delivery services, more companies can join the competition and adapt to trends cost-effectively. 

In boardrooms today, CRM automation has become a talking point for a different reason. Companies are wrestling with rising service costs, slower response times, and customers who are quick to walk away if their needs aren’t met. A CRM that simply records activity isn’t enough anymore. Leaders want a system that works in the background, qualifying leads, flagging risks, even nudging teams toward the next best action, without being told to.

This shift explains why investment in automated CRM platforms is climbing fast. The recent $2 billion Verint takeover is a reminder of how central automation has become to customer experience. It’s no longer just about streamlining internal tasks. These tools are now being used to cut customer drop-off, close the gaps in fragmented journeys, and reduce the cost of serving each interaction.

What Is CRM Automation?

There’s a simple way to think about CRM automation: it’s the part of your CRM that takes care of the repetitive work nobody really wants to do. Instead of a salesperson spending half an afternoon updating contact records, or a service agent chasing down the right person to handle a ticket, the system just does it.

An automated CRM keeps things moving in the background. A new lead comes in and gets routed to the right team without delay. A prospect clicks through a campaign, and the follow-up email is sent automatically. When a service rep opens a case? The system pulls up a full customer history, so they don’t have to start from scratch.

The tools are getting smarter, too. It’s not just about logging data anymore. With AI decisioning built in, CRMs can spot patterns, recommend actions, and even warn when a customer looks likely to churn. That’s why Salesforce’s recent move to acquire Bluebirds – described as a step toward “agentifying the enterprise” –  caught so much attention. It’s a signal that CRMs are shifting from being passive databases to active participants in customer experience.

Today, CRM automation benefits come from letting the system take care of the background noise so people can focus on the conversations and decisions that actually build relationships. It’s the difference between a CRM that feels like a filing cabinet and one that feels like a team member.

The Bigger Picture: CRM Automation ROI and Why It Matters

What’s the real payoff from CRM automation? For most companies, it comes down to three things: saving time, cutting costs, and making customer journeys less disjointed.

Time is the most immediate gain. Sales reps don’t need to spend their mornings updating spreadsheets. Service agents don’t waste minutes hunting for records. Marketing teams don’t manually build follow-ups.

Automated CRMs do the background work, so staff can focus on actual conversations. Research suggests automation cuts lead research and response times by more than 60%.

Money follows quickly. The ROI of advanced CRM tools, like Microsoft Dynamics, with built-in AI, can be massive – around 324% over three years, according to a 2024 Forrester Study. One company, Holmes Murphy, achieved a saving of $6.9 million in operational costs, using AI and automation to streamline renewal processes and give teams more time to focus on retention.

Then there’s consistency, the kind customers actually notice. When marketing, sales, and service share one automated system, follow-ups don’t get lost. A buyer isn’t bounced between teams. Problems aren’t repeated three times to three different agents. Journeys feel smoother, which usually means customers stick around longer.

The Benefits of CRM Automation Across Departments

Marketing is one of the first places where CRM automation benefits become obvious. Campaigns move faster, targeting improves, and teams can finally break free from the grind of repetitive tasks.

Think about the usual bottlenecks. Building lists. Scheduling emails. Tracking engagement. It’s all essential, but none of it should need constant manual effort. With automated CRM tools, those actions happen in the background. A customer clicks on a product page? The CRM can trigger a follow-up offer automatically. A prospect engages with an ad? The system routes them into the right nurture flow without anyone having to lift a finger.

The Holmes Murphy story makes the numbers real. The insurance brokerage used AI inside its CRM to study prospect behavior and adjust outreach. It wasn’t just about sending more emails – it was about sending the right message at the right moment. By also using automation to flag renewal risks early, the company gave teams more time to protect relationships before clients drifted away. The result: 44,000 staff hours saved and $6.9 million cut in costs.

There’s another benefit that marketers rarely admit but often feel: less burnout. When the CRM takes over repetitive scheduling and data entry, teams can spend more time on creative strategy and testing ideas. That makes the work more rewarding and usually leads to campaigns that land better with customers.

CRM Automation Benefits for Sales and Onboarding

Sales teams live or die by how quickly they can identify, qualify, and convert opportunities. That’s where CRM automation makes one of its biggest impacts.

In a manual setup, leads trickle in and someone has to sort through them, decide who gets priority, and make sure follow-ups happen on time. With automated CRM tools, the system scores leads based on behavior, routes them to the right rep, and can even recommend the best next step.

Panasonic Asia Pacific is a clear case in point. With operations spread across ten countries, the company needed a single source of truth for customer data. By automating its CRM processes, sales teams gained a consolidated view of every account and could work together across borders. The payoff was higher productivity and stronger win rates.

Elsewhere, AI Bees used a combination of Pipedrive CRM automation features and AI tools to boost their growth rate by over 2000%, aligning data and deploying more personalized sales strategies.

For onboarding, the story is similar. Automated CRMs can trigger welcome campaigns, schedule calls, and surface key documents automatically. Instead of juggling multiple systems, new customers are brought into the fold quickly – and reps spend less time on setup and more time on building trust.

The next step is “agentifying” the enterprise: building CRMs that can execute decisions on behalf of sales teams, something Salesforce is already working on.

CRM Automation Benefits for Customer Service and Support

Service is where people tend to notice CRM automation most. Few customers enjoy retelling the same issue to multiple agents or waiting days for an answer. The benefits here are obvious: quicker responses, less frustration, and lower costs.

Simple queries are picked up by chatbots, leaving staff to focus on the tougher cases. AI tools can draft replies, pull in the right knowledge articles, and create summaries of each interaction. Automation also ensures tickets land with the right agent the first time, cutting delays.

At Wiley, the publishing company that faces heavy seasonal spikes, automation replaced the need for extra temporary staff. With AI chatbots taking on common queries, cases were resolved faster, seasonal hires were trained quicker, and the company reported an ROI of more than 200%.

Wayfair provides another example. By automating its contact center with Verint, the retailer scaled workloads without ballooning costs. Instead of customers waiting in long queues, service was distributed more evenly, boosting both satisfaction and efficiency.

Then there’s Aviva. By using Verint’s speech analytics as part of their service automation strategy, the insurer didn’t just handle calls faster – they also improved compliance and raised NPS scores by 85%.

CRM Automation Benefits for Executives, HR, and Product Teams

Not every benefit of CRM automation shows up in sales charts or service dashboards. For executives and other team members, automation advantages appear in other ways.

For executives, the value is clarity. Automated reporting and AI-driven insights give leadership teams a real-time view of pipelines, revenue forecasts, and customer health. Instead of waiting on static reports, they can see problems coming and opportunities forming.

Look at RBC Wealth Management. Advisors there used to spend three to four hours preparing for a client meeting, pulling data from 26 different systems. With one automated CRM, they now have a single view and AI-driven alerts for next best actions. The time saved goes back into serving clients, not searching for files.

For HR and operations, automation smooths employee onboarding and workload allocation. Reps can be set up with workflows, permissions, and guided processes on day one. Seasonal staff can be brought online faster, as Wiley’s experience proved. With fewer repetitive tasks, attrition drops because employees spend more time on meaningful work.

For product teams, CRM automation turns customer feedback into action. Automated surveys, sentiment analysis, and issue tracking feed directly into product roadmaps. The insights don’t sit in silos; they reach the people who need them.

The Future of CRM Automation: What’s Coming Next

The next chapter of CRM automation is already taking shape, focusing on autonomy, intelligence, and trust.

• AI-native platforms: Older CRMs are quickly being replaced. New systems are rolling out in a fraction of the time often 70% faster, and ownership costs are dropping by more than a third. The difference is that automation is part of the core design from day one, rather than something added on afterwards.
• Agentic AI: This is where things get interesting. Instead of just recommending actions, CRMs are beginning to execute them. Salesforce’s push to “agentify” the enterprise with its Bluebirds acquisition is a clear sign we’re heading in this direction. NiCE and Microsoft are following similar paths, building intent-based AI agents that can handle entire workflows.
• Autonomous contact centers: Customer service is often the proving ground. Microsoft’s new “Intent Agent,” potentially shows how CRMs will soon be able to resolve end-to-end cases without human intervention. For many enterprises, this will mean lower costs and faster responses – but also a rethink of when and where human empathy should be reserved.
• Governance and guardrails. The promise of CRM automation benefits comes with risk. Automation works best when human oversight is built in. Guardrails are essential: setting permissions for AI-driven actions, maintaining compliance in regulated industries, and making sure “machine customers” don’t operate unchecked.

CRM Automation as a Core Enterprise Strategy

The role of CRM automation is changing fast. What began as a way to tidy up admin work has become a driver of customer experience strategy. Companies aren’t investing just to save time, they’re investing because smoother journeys and quicker responses build loyalty in ways that spreadsheets never could.

The next wave is already forming. Agentic AI, autonomous contact centers, and AI-native CRMs are shifting what “automation” even means. It’s now about systems that can act, decide, and collaborate alongside teams.

The enterprises that win here won’t be the ones that automate the most. They’ll be the ones that automate wisely, with clean data, clear guardrails, and a focus on where human judgment still makes the difference.

If there’s an issue on a brand’s site, it aims to flag it before customers report the problem.  

Earlier this month, Contentsquare shared its intention to expand its platform by snapping up Loris AI, a conversational intelligence solution deployed in contact centers.  

The solution comprises AI and machine learning models that analyze what customers are saying, without asking them directly.  

By bringing Loris into the fold, Contentsquare takes a unique step in merging digital analytics with conversational intelligence. 

That helps expand the scope of customer journey analytics beyond isolated digital analytics, customer feedback management, and contact center intelligence tools. 

By doing so, Contentsquare hopes to enable a deeper understanding of where customer journeys break and possible solutions. 

As Jonathan Cherki, CEO and Founder of Contentsquare, explained: 

CX is shifting fast, and conversations are becoming an essential part of how people interact with businesses. With Loris, we’re giving our customers the capabilities they need to lead this transformation – to understand and optimize conversations, and connect them to the broader digital journey.

Alongside this deeper understanding of where customer journeys break, Contentsquare is helping businesses prepare for a future where AI becomes evermore present across digital channels. 

That AI includes third-party conversational assistants, channels Gartner predicts will handle 70 percent of customer interactions, from start to finish, by 2028.  

As more interactions shift to these digital assistants, brands need to capture that conversational data and pool it. If not, they’ll only secure a partial view of how customers engage and where those AI-led interactions broke.  

By wrapping conversational analytics around live and AI agent conversations, Contentsquare can centralize that intelligence with broader journey context and derive new insights. 

Etie Hertz, CEO of Loris AI, shared his enthusiasm for joining Contentsquare’s mission. “AI agents and effortless brand engagement are unleashing a conversation revolution,” he said. “The companies that harness this conversational intelligence will win in this new world.

Combining Loris and Contentsquare connects digital interactions, AI responses, and customer conversations seamlessly with real business outcomes like satisfaction, retention, and lifetime value.

The combination also elevates Contentsquare’s vision to become a platform all customer-facing teams can plug into, not just a digital owner or contact center leader.   

Zeus Kerravala, Principal Analyst at ZK Research, applauds this approach.  

“I really appreciate organizations that think about CX holistically, the entire customer journey,” he said. “Traditionally, the contact center has been viewed as a cost center rather than a profit driver, since most customers only end up there when something goes wrong. Before that, they’re interacting on the website or in a store. 

That’s why platforms like ContentSquare are so valuable: they provide a complete view of the customer lifecycle.

“This acquisition of Loris signals a deeper focus on AI and analytics to capture and understand those interactions more comprehensively,” he summarized. “I’m excited to see how they build on this.”

However, Contentsquare is far from the only big brand to make an exciting, recent acquisition in the customer experience space.  

Most recently, private equity firm Thoma Bravo snapped up Verint, planning to merge the vendor with its workforce engagement management (WEM) rival Calabrio.  

Meanwhile, NiCE rolled up Cognigy to converge its Mpower CXone contact center platform with a leading conversational AI solution.  

Much like Contentsquare’s acquisition of Loris AI, these moves highlight a consolidation trend that may just reshape the customer experience landscape. 

Voice of the Customer (VOC) platforms and tools empower companies to learn more about what their customers really want, need, and expect. These tools have evolved far beyond simple solutions for sending traditional post-interaction surveys to customers.

Today’s platforms are smart, AI-powered ecosystems that capture feedback across every channel: voice calls, live chat, emails, social media, and even silent signals like click patterns or customer behavior. So which tools are leading the way in 2025?

Here are some of the top vendors in the VOC space, and what they have to offer.

The Top VOC Solutions

• • Qualtrics
  • Medallia
  • Sprinklr
  • PG Forsta
  • Chattermill
  • Alchemer
  • Verint
  • Concentrix
  • Caplena
  • SMG
  • NICE
  • SurveyMonkey
  • Pisano
  • Alida
  • QuestionPro
  • Dovetail
  • XEBO
  • CustomerGauge
  • SurveySparrow
  • AskNicely
  • Cresta
  • CallMiner
  • Observe.AI
  • Invoca
  • Genesys

The Top VOC Solutions for Deeper Customer Insights

This list highlights the most impactful Voice of the Customer (VOC) solutions in 2025. It’s built on a mix of trusted research and real-world insight, including the latest findings from the Gartner Magic Quadrant for VOC Platforms, Forrester Wave evaluations, recent product announcements, and internal analysis of emerging trends across the CX space.

Each solution in this list stands out for a different reason. Some lead with powerful AI, others with seamless integration or exceptional usability. All of them reflect where VOC technology is headed, and how businesses are using it to listen, learn, and lead in customer experience.

Qualtrics

Qualtrics won “Best VoC Solution” at the CX Awards 2025, thanks to the completeness of its vision, rapid feature release cadence, and its extensive base of global enterprise clients.

One notable new release within its XM for Customer Experience suite is its Experience Agents. These AI-driven assistants proactively resolve problems, personalize follow-up, and even tweak website interactions on the fly.

Another is its Conversational Feedback capability, which helps generate two times more detailed responses, enhancing insight quality without reducing completion rates.

Qualtrics also introduced various solutions for omnichannel insights, such as its Location Experience Hub (for frontline teams) and Qualtrics Assist for CX.

Plus, the company announced Qualtrics Edge, a market intelligence platform for blending AI, synthetic insights, market research data, and even expert advisory services.

Lastly, Qualtrics has developed strategic partnerships and co-innovations with major brands like KFC, which have driven measurable results.

Medallia

Medallia has further distinguished itself in the VoC space by adding 100+ AI-powered features since the beginning of 2024, turning omnichannel data, including contact center and digital customer interaction data, into real-time, actionable insights.

The vendor’s assistant, Athena, is a notable addition, delivering instant customer intelligence to key business stakeholders and reducing analytical workloads.

Meanwhile, Medallia helps aggregate feedback from 35+ systems, leveraging advanced text analytics and cohort tracking for deep personalized insight.

Interestingly, strategic acquisitions and a strong focus on unstructured data somewhat position Medallia as a system of record for customer signals, acting almost like a CRM or CDP platform.

By blurring the lines between VoC and these CX software categories, Medallia can differentiate not only via a focus on collecting richer data, but also by acting on it with layered workflow tools for dissatisfied customer follow-ups, front-line coaching recommendations, and more.

Sprinklr

Sprinklr benefits from its broader ecosystem of social media management, conversational AI, and contact center solutions. In tying these offerings with VoC solutions, the vendor enables capabilities that differentiate its Sprinklr Insights platform.

For instance, it doesn’t only track brand mentions on social media. Instead, it takes other actionable intelligence, such as trending topics on specific social channels, to help brands engage in more conversations that matter to their business and glean insight from them.

As a result, Sprinklr extends the scope of VoC and passes new insights across the business with proprietary AI and ML routing engines. These insights may then trigger campaigns, alerts, and support responses instantly.

In terms of its core VoC proposition, Sprinklr impresses with its conversational survey capabilities, AI-driven user interface, and customer community.

Yet, the integration of VoC capabilities within the Sprinklr Unified CXM platform, with cross-departmental workflow triggers, makes Sprinklr a standout VoC option.

PG Forsta

PG Forsta made a splash with its May 2025 acquisition of InMoment, bringing together two industry leaders to create a new VOC solution powerhouse.

With InMoment’s Experience Improvement (XI) Platform, PG Forsta secures advanced AI analytics features, including the ability to offer prescriptive recommendations on how to improve an individual’s experience based on their feedback.

Additionally, the VoC solutions vendor offers PG Forsta mature predictive analytics capabilities and a deep base of professional services partners, which can champion its brand.

Meanwhile, PG Forsta has many pre-existing strengths, likes its industry-specific innovation and expertise, which extends across highly-regulated sectors, including healthcare and financial services.

Meanwhile, the VoC provider can offer advanced market research, journey visualization, and front-line employee feedback solutions.

Chattermill

Chattermill offers a VoC solution leveraged by brands including Uber, Booking.com, and E.ON.

Its proprietary AI, Lyra, is a key platform capability, transforming unstructured data – from support chats to app reviews – into actionable insights that guide strategic decisions across the front office, product teams, and beyond.

Those actionable insights can underline specific pain points and growth opportunities, which funnel through to the relevant teams.

Real-world impact includes a 144 percent NPS increase in its work with E.ON, with the case study showcasing how Chattermill turns feedback into business transformation.

Yet, Chattermill typically only works with brands that seek experience-led growth, as they can ensure cross-functional buy-in that enables the provider’s platform to shine.

Alchemer

Recognized by both Gartner, and the Forrester Wave reports, Alchemer upgraded to a “Challenger” position in this year’s magic quadrant. This company’s easy-to-use platform offers a flexible survey builder and empowers businesses to gather feedback from the web, mobile, and in-app surveys

Alchemer provides an intuitive platform that centralizes flexible survey tools across web, mobile, and in-app channels.

A notable feature of its platform is Alchemer Pulse, which adds AI-powered text analytics for real-time sentiment, intent, and thematic insights, while integrations with CRMs and support systems drive action from feedback.

Its 2023 acquisition of Apptentive has also bolstered the platform, strengthening its mobile feedback. Meanwhile, its Chattermill partnership boosts its AI-driven text mining capability.

Across verified review sites and industry reports, Alchemer also differentiates via its free proof of concepts (POCs) and highly-rated customer experiences.

Verint

Verint remains a highly-regarded vendor across the contact center space, and its VoC solutions typically excel in equipping service leaders with new customer insight.

With its adjacent enterprise data hub, brands can consolidate that insight and align it with conversational analytics, workforce engagement management (WEM), and other key contact center data sources.

In terms of Verint’s more flashy features, unique capabilities like customer effort detection, advanced data mapping, and AI-led outreach triggers, based on social sentiment, stand out. These tools help expand Verint’s reach beyond the confines of the contact center, as does its rage detection functionality.

Nevertheless, it’s a provider best suited to businesses looking to primarily boost the performance of their customer service teams.

Concentrix

Though it slipped into the niche player quadrant for the 2025 Garter VOC Magic Quadrant, Concentrix still has a strong presence in the market.

Concentrix stands out for not only delivering a VoC platform but also having expert-led service teams work closely with customers to deploy its technology across their operations.

That said, its solution does boast several nifty capabilities. For instance, its AI Data Explorer empowers any team member, from the frontline to executives, to instantly extract insights from structured and unstructured data, with no data scientists necessary.

New AI tools also assist in crafting ad-hoc pulse surveys tailored to specific needs in minutes.

Alongside that, Concentrix claims to help brands unlock three to five times ROI within 12 months by taking on much of the logistics and enabling CX leaders to focus on what matters: driving change.

Caplena

Caplena uses a mix of generative AI and statistical methods in VoC solutions to analyze survey responses, reviews, and other unstructured text.

Yet, what sets it apart is its tools to keep users in the driver’s seat. For instance, they can fine-tune AI-generated topics in real time, with built-in quality scores providing confidence in the output. They can also select from 31+ languages and import data via CSVs and out-of-the-box APIs.

Dashboards with a native AI assistant also help teams explore and share results quickly, with unlimited user access across the organization. Indeed, anyone can engage with the data from frontline teams to leadership and uncover what matters most to customers.

Finally, Caplena partners with over 200 companies – including Lufthansa, Kia, and Bosch – to make sense of millions of pieces of feedback and drive better customer experiences.

SMG

SMG combines VOC solutions with insights into employee experience, and brand experience. SMG excels in specific industries, like retail and consumer goods, and also in how it combines VoC with VoE (voice of the employee) solutions to empower customer-facing teams.

Other notable features include its advanced mobile app, benchmarking, and intuitive report-building, all aiming to aid VoC analysts with deeper insights.

The vendor is also highly-regarded for its service-oriented approach, beyond the initial deployment, utilizing its market heritage to help brands deploy VoC platforms thoroughly and at maximum value. Via this last point, SMG reveals its true differentiator: market understanding and execution.

NICE

Nowadays, NICE primarily focuses on the CCaaS and WEM markets. Yet, it has heritage in this space with NiCE Satmetrix.

Now, that solution is named NICE Feedback Management Surveys, and it still boasts many advanced features, especially for brands seeking a contact-center-oriented VoC product.

For instance, its multichannel surveys include automations to boost response rates, its analytics features smart CSAT/NPS analysis, and its ecosystem comprises a roster of oven-ready CRM integrations and flexible APIs.

Plus, thanks to its contact center prowess, NICE can connect VoC data with WEM, conversational analytics, and other CCaaS data sources for a more comprehensive customer view.

SurveyMonkey

SurveyMonkey is firmly focused on VOC solutions for CX teams, with over 260K organizations using AI‑infused tools for survey building, feedback collection, and analytics.

SurveyMonkey isn’t just a survey creation tool for SMBs. Instead, it has an enterprise offering that harnesses AI‑infused tools for survey building, feedback collection, and analytics.

One standout feature is “Build with AI”, which lets teams draft surveys via voice commands or text. Another is “Connect”, a library of no-code quick actions to connect survey data with popular business applications.

In terms of its analytics, SurveyMonkey can offer multi-survey analysis, benchmark customer experience with industry-standard metrics, and enable TURF analysis to help determine the best combination of products, capabilities, or messages to reach more customers.

SurveyMonkey also offers a tight integration with Salesforce, embedding VoC capabilities directly into Salesforce workflows.

Pisano

According to verified customer reviews on Gartner Peer Insights, Pisano leads the VoC space in its integration and deployment experience (as of July 2025). It’s even above Qualtrics and Medallia!

In this regard, the platform benefits from its lightweight, plug-and-play VoC solutions. Yet, its robust AI-driven text analysis is also notable. Thanks to this capability, Pisano can identify sentiment, thematic trends, and predictive insights across mediums to help teams anticipate customer needs.

Built for mid-market organizations, Pisano combines simplicity with depth, with its dashboards delivering quick insight “without complexity”.

Pisano also offers a unified experience for capturing and acting on feedback, making it ideal for businesses that want fast deployment and advanced analytics in an accessible package.

Alida

Alida’s platform stands out for its “beyond customer experience” focus, as it pulls relevant customer insights for specific stakeholders, from researchers to user experience (UX) design teams.

In doing so, it offers differentiative VoC data collection tools, which support customer interviews, community panels, and even usability tests.

Moreover, it offers an array of integrations with CRM, ticketing, and BI systems, through which it can share discovery data from across the customer lifecycle.

Ultimately, Alida is more of a unique solution within this VoC solutions vendor mix, which may help teams from across the business contribute further in shaping next-generation customer experiences.

QuestionPro

QuestionPro is a VoC platform that is well-utilized within midmarket and growing businesses thanks to a survey-first design that enables fast, flexible feedback collection.

It’s also cost-effective and relatively simple to utilize, as teams may create, launch, and optimize their VoC programs while leveraging several advanced features.

Perhaps most notably, these features include journey tracking, generative AI assistants, and multi-channel distribution across the web, email, mobile apps, and social. Yet, there’s also geolocation logic and collaborative testing.

Lastly, while it may not match Qualtrics or Medallia for feature depth, it can deliver accessible, actionable insights with much of the power and polish of higher-end systems.

Dovetail

Leveraged by the likes of Amazon, Spotify, and Starbucks, Dovetail is a VoC vendor that’s quickly rising up the ranks, with its platform designed to help teams create more customer-friendly products and services.

How? By collecting feedback from a myriad of sources – user feedback, service tickets, sales calls, etc. – and funneling them into a customer insights hub. It then makes all that insight searchable, so critical stakeholders from across the business can unlock new knowledge via prompts.

The solution can also help create action plans based on stored insights, generate VoC reports “with one click”, and translate across 75 languages.

Lastly, Dovetail doesn’t rely only on large language models (LLMs) and natural language processing (NLP) for innovation. It even features trusty old AI tech like optical character recognition (OCR) to support various VoC activities.

XEBO.ai

XEBO.ai is a newcomer that earned a spot in Gartner’s 2025 VoC Magic Quadrant thanks to its pure AI-native approach.

Rather than bolting on AI as a feature, XEBO.ai embeds it at the platform’s core, analyzing direct and indirect feedback sources in real time to extract emotion, intent, and predictive insights.

Its platform is also designed for scale and flexibility, offering secure local hosting, video-to-text feedback, and customizable workflows.

With strong uptake in telecom and retail, XEBO.ai is already making waves as a new entrant, while its robust international support is also impressive, given how the company was only founded in 2018.

Other standout strengths include robust social listening and a go-to-market strategy that’s helped it outpace more established players.

CustomerGauge

CustomerGauge serves the B2B market, with powerful tools for combining customer insight with revenue data to identify churn risks, upsell opportunities, and loyalty drivers.

The Netherlands-based provider also offers market benchmarking, industry-specific scoring, and proactive outreach to help businesses use insights to actively retain customers, build better relationships, and upsell.

Additionally, the company is hands-on, offering playbooks to customers so they can run new VoC initiatives and bolster their broader strategies.

That serves its vibrant community, with the brand frequently running new educational activities to help keep its customers up to date with all its latest activities.

SurveySparrow

SurveySparrow offers a conversational, survey-first VoC solution, priding itself on the diversity of survey options, its platform ease of use, and ecosystem of 1,500+ integrations.

On the former, it can offer “chat-like” surveys to encourage participation, alongside classic, online, NPS, and various other templated surveys.

The vendor then applies its CogniVue analytics engine to dig into open-text responses, surfacing trends and key themes.

However, SurveySparrow’s range of customer survey tools sets it apart, enabling versatile tools for spot checks, pulse assessments, and more.

AskNicely

AskNicely takes a fresh, frontline-first approach to customer experience by focusing not just on measuring customer experience retrospectively, but improving it in real time.

Indeed, the company describes its solution as a pocket-sized coach for frontline employees, delivering instant feedback, recognition, and coaching after every customer interaction.

The mobile-first platform scales easily across customer-facing teams, taking the voice of the customer and making it instantly actionable.

Lastly, the vendor scores highest out of all experience management software providers on G2 in terms of ease of use (as of July 2025). That’s a big accolade for a relatively small brand.

Cresta

Cresta is boosting its presence in voice-based VOC solutions with innovations designed for contact centers. The Voice Virtual Agent is a conversational AI that handles complex calls 24/7, learning from humans and identifying upselling or retention opportunities.

It combines LLM flexibility with deterministic logic to ensure compliance and empathy. On the analytics side, Cresta’s Conversation Intelligence tracks human and AI interactions in real time, offering sentiment analysis, quality management cues, and coaching recommendations.

The new AI Analyst lets teams ask natural-language questions like “Why did CSAT dip last week?” and get evidence-based answers in minutes.

Companies can also dive deeper into factors that define agent authenticity, empathy, and human-like content production.

CallMiner

CallMiner holds a strong position in conversation intelligence for VOC, recently named a Leader in Forrester’s Q2 2025 Wave.

Its Eureka platform scored top marks for insight exploration, topic classification, signal extraction, and coaching tools. There are also tools for curated categorization, sentiment analysis, secure redaction, and predictive scoring.

The recent acquisition of VOCALLS adds voice, chat, messaging, and email AI to its existing analytics toolset.

The platform excels for mature contact centers aiming to turn every interaction into actionable feedback. It supports automated follow-up, agent coaching, and overarching CX improvements, helping businesses scale VOC solutions beyond individual teams and into strategic decision-making.

Observe.AI

Currently engaging in some strategic acquisitions, Observe.AI is doubling down on its position in VOC solutions with the latest GenAI Insights update.

The platform now analyzes 100% of customer interactions, voice, chat, email, and surfaces turn‑by‑turn sentiment shifts, key causes and top contact drivers instantly.

Every team can access these insights via “AskObserve,” a conversational AI that responds to natural-language queries like “Why are calls about billing trending up?” with structured, data‑backed insights.

There’s also a dedicated solution specifically designed for sales teams, to help them understand objections and churn metrics.

Observe.AI also includes built-in agent coaching tools such as real-time guidance, auto‑QA, next-best-action suggestions and instant call summarization, all powered by GenAI.

Invoca

Invoca takes a marketing-to-revenue approach to VOC solutions by pulling voice call data into its automated analytics engine.

Its Signal AI Studio uses unsupervised machine learning to tag conversation topics, outcomes, and conversion signals from phone calls automatically.

The platform then connects those results to marketing channels, CRM, and bid-management platforms, turning every call into a driver for marketing and sales decisions.

In June 2025, Invoca earned the “Strong Performer” designation in Forrester’s Conversation Intelligence Wave for bridging pre-call digital signals with post-call voice analysis. Users rave the platform’s ability to score calls for revenue-relevant outcomes.

Genesys

Genesys Cloud has seen fast adoption with its AI-powered Experience Orchestration and VOC analytics. The system analyzes empathy display, sentiment, and channel switches in real time across voice, chat, and digital.

Businesses can react instantly via alerts, training prompts, or automated workflows, thanks to in-depth contact center solutions for both outbound and inbound conversations.

During FY2025, Genesys added over 150 AI features, covering AI-driven virtual assistants, real-time sentiment analytics, and post-call summaries. The platform boasts deep CRM integrations through AppFoundry and supports broad orchestration via its AI copilot and routing layers.

The Top VOC Solutions in 2025

The market for VOC solutions in 2025 is more dynamic and powerful than ever. From AI-powered conversation intelligence to real-time action platforms that close the loop automatically, today’s VOC solutions go far beyond basic surveys. They tap into every customer touchpoint, whether it’s a phone call, chatbot, online review, or mobile app interaction, and turn raw feedback into strategic decisions.

Ready to learn more about the benefits of analyzing, tracking, and using the voice of the customer for enhanced CX? Check out this guide to what’s next in the VOC space.

Or dive into these resources for help planning your next move:

• Download the research: Explore innovative reports exploring all of the latest trends and opportunities in VoC technology.
• Join the Community: Connect with CX leaders, strategists, analysts, and thought leaders in the thriving CX community.
• Meet the vendors: Visit upcoming events for an opportunity to test the tech, speak to the vendors, and learn about the latest trends.
• Learn about the market: Discover everything enterprise leaders need to know about VoC solutions, and customer experience.

Today’s enterprise customers are more vocal than ever – sharing insights about their needs, priorities, and pain points. All business leaders need is the right way to listen.

Today’s enterprise CX teams aren’t just measuring sentiment or tracking NPS. They’re turning real-time data into decisions, across every touchpoint, team, and region. From personalized journeys to live service escalation, analytics is driving everything.

Many of the top data and analytics experts are even helping organizations embrace future trends, ensuring they can build optimize, and effectively deploy cutting-edge AI models. They help companies combine customer signals from CRM, call recordings, feedback loops, support tickets, and even third-party data. They connect the dots, then help automate what happens next.

So, which service providers are really worth watching? This guide offers a snapshot view of the top companies in the CX Today Data & Analytics marketplace, chosen for their impact on CX teams.

Top Data and Analytics Service Providers

• • Accenture
  • Deloitte
  • HCL Technologies
  • EY
  • KPMG
  • IBM
  • TCS
  • PwC
  • Infosys
  • Capgemini
  • Cognizant
  • Wipro
  • Atos
  • NTT DATA
  • Genpact
  • Tech Mahindra
  • DXC Technology
  • EPAM

The Data Analytics Service Providers Supporting CX Teams

Customer data is everywhere. The real challenge is getting it to work in sync.

This list covers 18 providers helping enterprise teams get more from their data, whether that means building a smarter CDP, running more predictive analytics, or helping frontline teams see what’s happening in real time.

Some vendors on this list lead with technology, others with advisory expertise. Most offer both, often wrapped in industry-specific accelerators or AI-ready frameworks.

These aren’t ranked. They’re selected based on relevance, CX focus, and the ability to deliver measurable impact.

Accenture 

Accenture doesn’t try to compete on tools alone. It competes on execution. That’s what makes its data practice: Cloud First Data & AI, stand out in a crowded field.

Rather than dropping in a generic platform, Accenture helps organizations build full-stack data ecosystems that actually support how teams work. For CX, that means connected touchpoints, automated insights, and analytics that don’t just measure satisfaction but predict where it’ll drop.

Accenture can assist with everything from generative AI consulting, to data transformation, SynOps, and business process analytics. Companies can even take advantage of applied intelligence solutions, which embed AI capabilities into their existing tools and platforms.

Add in partnerships with all the big names like AWS, Microsoft, Google Cloud, Databricks, Salesforce and it’s clear why Accenture stands out among data analytics service providers.

Deloitte 

With years of experience in the analytical landscape, Deloitte is a company committed to helping member firms design, build, and optimize insight-driven organizations.

Its Data & Analytics practice focuses on helping businesses treat information not just as an asset, but as something that has to be defensible, to regulators, boards, and customers alike. For teams working in finance, health, energy, or government, that lens is critical.

CX-wise, Deloitte helps clients architect data flows that support customer intelligence in real time, including consent tracking, journey scoring, and predictive churn modeling. It doesn’t sell a one-size-fits-all CDP. Instead, it tailors architecture and tooling to the use case, whether that’s integrating legacy CRMs, deploying AI, or cleaning up fragmented data lakes.

There’s also growing attention on responsible AI helping companies deploy algorithms they can actually explain, to customers and other leaders.

HCL Technologies 

Otherwise known as HCL Tech, HCL Technologies is a vendor of digital solutions for cloud migration, and digital transformation. The data analytics services offered by the organization ensure companies can recognize opportunities for top-line and bottom-line growth, and implement powerful strategies for CX (customer experience) transformations.

Its Data and AI Services focus heavily on pre-built accelerators designed to ingest, cleanse, and activate customer data faster than traditional consulting setups. That includes built-in templates for CDP rollouts, AI-powered analytics for contact centers, and plug-ins for CRM platforms like Salesforce and Dynamics.

What makes HCL’s offering feel different is its focus on operational data, not just marketing signals or sales touchpoints. Teams can bring in ticket resolution times, product telemetry, field service data, and see how those operational inputs affect CX in real time.

HCL also supports multi-cloud flexibility, so teams aren’t stuck inside a single ecosystem. It plays well with Google Cloud, Azure, AWS, and hybrid architectures.

EY 

EY, or Ernst & Young Global, is a multinational professional services partnership, and leading accounting firm. The company’s wide range of consulting services include dedicated solutions for data and decision intelligence, powered by artificial intelligence.

In 2025, EY’s analytics work is tightly connected to customer and brand strategy, with teams helping enterprise clients understand where value is created, and where it’s leaking.

At the heart of EY’s approach is Intelligent Data Fabric. It’s a framework,  built to help companies unify structured and unstructured data, then layer in machine learning and predictive modelling on top.

EY also brings strong capabilities in risk-aware analytics,  an increasingly important edge for industries under pressure to explain their data use. From data privacy to AI governance, the firm works closely with teams to build strategies that hold up under scrutiny.

KPMG 

KPMG knows the value of in-depth data insights, and what they mean for growing companies. To ensure organizations can make the right decisions, the company offers comprehensive consulting and advisory services, covering everything from auditing to deal advice.

KPMG’s teams help build models that explain why a customer is acting a certain way, not just what they clicked on or where they dropped off. That’s crucial for organizations trying to map out journeys, forecast satisfaction, or predict service needs.

Like some of the other top data analytics service providers, KPMG is investing heavily in data ethics and sustainability metrics, helping companies understand not just CX outcomes but broader stakeholder impacts.

Plus, for organizations investing in new forms of digital transformation, KPMG offers an opportunity to leverage specialist software testing and integration services, alongside technology guidance.

IBM 

Part of the broad range of digital services and solutions offered by IBM, the company’s data analytics services support companies with a range of use cases. With IBM, companies can gain assistance with planning analytical strategies, forecasting, and even predicting opportunities.

The combination of Watsonx, IBM Consulting, and deep industry models puts the company in a strong position to help enterprise CX teams get more from their data.

What stands out most is IBM’s ability to combine AI with data governance. It’s not just about showing customer behavior, it’s about building systems that explain, predict, and adapt in real time. That includes everything from automated next-best-action models, to forecasting churn, to guiding human agents with in-the-moment insights.

IBM also offers industry accelerators, which give CX teams a head start on use cases like proactive customer service, retention analytics, and journey scoring.

TCS 

Recognized as a leader in data analytics services, TCS, or Tata Consultancy Services, gives companies the insights and support they need to unlock the true value of their data. The company specializes in delivering bespoke and customized services to assist with business decision-making.

Companies can work with TCS on enterprise data management, managing and disseminating insights for all applications and processes.

At the heart of its CX offer is TCS Cognix, a library of pre-built use cases, AI models, and automation blueprints. It’s not a packaged platform, but a way to accelerate delivery without reinventing every layer of the stack.

TCS is also known for its industry lens. Whether it’s banking, telecom, or retail, it doesn’t just offer templates, it brings context. That includes KPIs, compliance guidance, and integration support for legacy systems that still run core processes.

PwC 

Specializing in the world of insights and discovery, PwC delivers a host of solutions to companies investing in the benefits of data analysis. With solutions like the Frontier Data Lab, gives companies a collaborative environment where they can bring their data to life in unique and immersive ways.

Companies can leverage the services offered by PwC to assist with data quality management and protection, as well as reporting, visualization, and machine learning.

Plus, PwC has its own data intelligence platform offering in the cloud, which can automatically ingest, interpret, and report on a range of unstructured and structured data types.

The firm’s strength lies in translation. It helps teams move from metrics to priorities. Because the work is grounded in business performance, there’s always a through-line back to ROI, not just analytics for its own sake.

Infosys 

Offering a broad range of data analytics options, Infosys combines expertise with AI and automation, to give companies full access to a holistic range of insights. As one of the top data analytics service providers, Infosys helps businesses quickly and efficiently modernize their data stack.

Its programs tend to focus on unblocking the basics first, getting clean, connected data flowing into the right systems, before layering in more advanced capabilities. From there, Infosys brings in tools like Topaz, its generative AI suite, to help teams model churn, forecast demand, or personalise digital experiences at scale.

Infosys also offers a range of advisory services, from data maturity assessments, to strategic roadmap definition and technical consultancy. Plus, clients can tap Infosys to get support with predictive modelling and enrichment, workflow automation, and experimental design (A/B testing).

Companies can also leverage a range of additional services, from the Infosys Information Grid to self-service data preparation tools.

Capgemini 

Known for their intuitive market reports and insights, Capgemini offers a range of data-driven services and analytics solutions to companies. The organization’s approach to enterprise data analytics services covers a wide range of business needs. With Capgemini, companies can tap into data strategy development solutions, and intelligent process and performance analysis

For CX teams, the Insights & Data portfolio stitches together fragmented platforms, building a foundation for first-party data, and setting up customer models that can evolve with behavior. There’s a strong focus on data trust making sure internal users actually believe the numbers they’re seeing.

The Capgemini Research Institute can also work with companies to assess market factors and develop deeper understanding of specific topics. Capgemini’s services are scalable and customizable to suit businesses from all industries.

There are also dedicated services for EX insights, data-driven finance, risk, and compliance, and consulting for intelligent workflow processes.

Cognizant 

Using their data analytics services, Cognizant helps organizations reimagine processes, modernize technology, and improve customer experiences. They were the first IT service provider to achieve ISO 42001:2023 certification in 2025.

Its Neuro AI platform is a big part of what makes Cognizant one of the top data analytics service providers. Designed for enterprise use, Neuro brings together automation, data orchestration, and embedded intelligence in one architecture.

One standout area is real-time decisioning. Cognizant helps clients use live data to personalise content, redirect journeys, or trigger service workflows based on customer intent. This is all built with transparency in mind teams can trace how decisions were made, and adjust logic without writing code.

The company also offers a range of data testing services, migration support solutions and DevOps solutions.

Wipro 

Focusing on empowering enterprises with comprehensive intelligence, Wipro helps companies unlock the information they need to make intelligent growth decisions. Wipro’s range of services and solutions cover everything from reporting capabilities, to strategic advisory services, insights transformation, and data engineering.

The firm’s approach for CX teams centers on connected customer journeys. That means tying together data across sales, marketing, and service, and giving each team a clearer picture of where things are working. Its use of AI accelerators helps shorten setup time, especially for common use cases like churn prevention or next-best-offer suggestions.

Wipro is also strong on infrastructure. For enterprises juggling on-prem systems and multiple clouds, its teams are used to working inside hybrid environments. That includes integrating with tools like Salesforce, Adobe Experience Cloud, and Microsoft Dynamics.

Atos 

Recognized by analysts like Gartner for its data analytics services, Atos helps companies from all industries unlock opportunities for digital transformation, and customer experience optimization.

Its Data and AI services are built to give organizations more control over data pipelines, and how decisions get made from them. That includes everything from real-time customer intelligence to predictive maintenance and behavioral modelling.

The broad Atos data and analytics portfolio also includes a modern data architecture system, to help companies build and optimize data architecture. The company can also assist companies with more specific data strategies, like leveraging opportunities to implement AI and automation into workflows.

Atos also stands out for its infrastructure muscle. The company supports hybrid and edge computing models, with deep partnerships across Google Cloud, Azure, and AWS. That gives teams options.

NTT DATA 

Supporting companies across a range of industries, NTT DATA helps companies transform and improve through consulting, industry solutions, managed services, and IT modernization. The company’s end-to-end data and intelligence services give organizations a framework for building unique experiences, and unlocking opportunities for growth.

The approach is modular. Some clients need a full CX analytics overhaul. Others just need a better way to surface journey insights or unify customer records. Either way, NTT DATA starts with strategy, aligning technology with outcomes that actually matter to the business.

With NTT DATA, companies can gain assistance with everything from implementing AI into their ecosystem, to upgrading their technology infrastructure. There are solutions for responsible governance, reporting and business intelligence, and managed services.

Moreover, NTT can help companies take advantage of new technologies, like NLP or computer vision.

Genpact 

Genpact doesn’t try to own the entire CX stack. Instead, it works across systems to bring clarity, using data to help teams see what’s working, what isn’t, and what to do next.

Its Analytics and AI services are centered around decision intelligence. That means helping companies design journeys based on signals, not just channels. Genpact’s teams embed into operations, working closely with stakeholders to align KPIs, build repeatable models, and integrate insights into the platforms teams already use.

A lot of its analytics work as one of the leading data analytics service providers is focused on frontline enablement. That means arming agents, marketers, or service leads with the data they need in real time. That includes churn indicators, sentiment scoring, and conversion insights pulled from live interactions.

There are also dedicated solutions for financial analysis, supply chain analytics, machine learning operations, and more.

Tech Mahindra 

Multinational technology services and consulting company Tech Mahindra, offers access to a range of innovative data-driven solutions, from the Nxt.Now platform for building, managing, and exploring business models, to the digital engineering services.

The company’s NXT.Now offering includes a comprehensive cloud-based platform, blockchain technology, and tools for cyber security, to help preserve and protect data.

Its Communications Analytics offering is built around vertical-specific data models. These are designed to track service quality, billing issues, churn risk, and even location-based patterns. That makes it easier for teams to detect friction points and respond in real time.

Like many of the top data analytics service providers, Tech Mahindra is also focusing on AI operations, helping businesses automate end-to-end playbooks with intelligent tools.

DXC Technology 

DXC Technology approaches data and analytics with a builder’s mindset. Its Analytics and Engineering services are built for organizations that need to modernize without unnecessary complexity.

DXC Technology combines human-centric strategic design, with automation, generative AI, DataOps, and MLOps, and offers companies opportunities to hyperscale data management. With DXC, companies can address skill shortages, increase margins, and boost employee satisfaction.

DXC supports hybrid deployments, cloud migrations, and multi-system orchestration, helping teams make sense of data no matter where it lives. One key strength is data product engineering, building reusable data assets that plug directly into business workflows.

That includes CX use cases like customer lifetime value, journey scoring, and proactive service triggers.

EPAM 

EPAM blends product thinking with deep technical execution and that’s what makes its Data and Analytics Services different. Combining consulting, training solutions, and technology, the organization specializes in intelligent automation and growth opportunities.

EPAM also helps organizations embrace the power of AI and develop comprehensive strategies for data governance, migration, and management. Agile data architecture means CX teams can pull in customer signals from any source, and use that to trigger personalization, improve retention, or even redesign journeys on the fly.

EPAM also supports embedded analytics. Instead of adding another dashboard, its teams help integrate insights directly into frontline tools. For support agents, that could mean real-time churn scoring. For marketers, AI-generated segmentation built right into the campaign workflow.

The Top Data Analytics Service Providers: Enlightening Teams

There’s no shortage of analytics partners out there. The hard part isn’t finding one, it’s knowing which one fits the way your business actually works.

Some companies need a full-stack transformation. Others just need a partner who can untangle the data they already have. Some are focused on modernizing infrastructure. Others want to unlock better CX performance next quarter. Every team’s starting point is different, and the best vendors understand that.

What’s consistent is the shift away from isolated reports. Leading organizations aren’t just collecting data. They’re operationalizing it, making it part of the customer journey, the service layer, and even the revenue strategy, particularly with the help of AI.

Data isn’t just a system to manage. It’s a lever to lead with. The right partner can help enterprises turn disconnected signals into decisions that improve customer experience, unlock efficiency, and drive growth. Here’s how CX Today helps you get there:

• Go deeper with data. Our latest research covers the trends shaping the future of analytics, CDPs, and customer intelligence.
• Tap into the CX Community. Learn from IT leaders and decision-makers solving real problems with data every day in the CX Community.
• See it all live. Explore upcoming events, product demos, and vendor showcases, online and in-person.
• Buy smarter. Use the CX Buyer’s Guide to make sure every decision is aligned with business outcomes, not just buzzwords.

The future of customer experience will be data-driven, not just in theory, but in how every journey, conversation, and decision takes shape. With the right strategy and the right support, that future starts to look a lot more practical.

It listens to every word, every silence, every sentiment shift, and turns it into something useful. A trend, training insight, compliance flag, or an alert that something isn’t landing the way it should.

It’s not just for sales either. 89% of marketers even say intelligence from phone calls is crucial to staying competitive. For CX leaders, conversation intelligence offers a way to stay ahead of customer preferences, and expectations.

At enterprise scale, the cost of not knowing is too high. That’s why CI is becoming critical infrastructure.

What Is Conversation Intelligence?

Most platforms can tell companies when a call started and how long it lasted. That’s easy. What matters more is what was said, and what wasn’t.

Conversation intelligence refers to the process of analyzing real conversations, spoken or written, using AI, speech recognition, and natural language processing. That includes calls, video meetings, emails, chat threads, and even ticket logs.

Good CI software doesn’t just capture. It categorizes, detects, and flags. It recognizes when a rep talks over a customer. When a competitor gets mentioned. When frustration starts building but hasn’t yet turned into a complaint.

The best systems go further. They link that insight back into CRMs, customer data platforms, QA workflows, and business intelligence dashboards, creating a closed loop from frontline interaction to executive decision.

Notably, conversation intelligence isn’t the same as conversational AI.

• Conversational AI runs the conversation (chatbots, virtual agents).
• Conversation intelligence analyzes it afterward, or increasingly, during.

The value for enterprises isn’t just insight. It’s consistency. One shared understanding of what’s happening in customer conversations, across teams and time zones.

What is Conversation Intelligence Software?

A lot gets said during a call. Some of it’s useful, some is noise. What matters is knowing the difference before the conversation ends.

That’s where conversation intelligence software comes in.

At its simplest, it’s a tool that listens to live or recorded conversations and pulls out the signals that actually matter. Not just who said what, but how it was said, when the tone shifted, and whether something important got missed.

• A rep forgets to mention next steps. The system flags it automatically.
• A customer says “I’m not sure this is worth the price.” That line gets highlighted, scored, and tracked.
• A manager pulls up a dashboard and sees that across 38 calls this week, one phrase keeps showing up: “I need to talk to my boss.”

Conversation intelligence software typically runs on a mix of real-time transcription, sentiment detection, keyword analysis, and machine learning. Most tools integrate directly with CRM systems, contact center platforms, or sales engagement tools.

Some tools work live, nudging reps with reminders or prompts in real time. Others run after the fact, surfacing trends across dozens or hundreds of conversations at once. Either way, the goal’s the same: make better use of what’s already being said.

Call Tracking vs Conversation Intelligence

Most enterprise teams already track calls. They know when they happened, how long they lasted, and who was involved. But that’s just the outer shell. It says nothing about what actually took place inside the conversation.

Call tracking is metadata. Caller ID, duration, routing path. It tells leaders where a call came from, not what came out of it. Conversation intelligence, on the other hand, goes inside the call. It listens, learns, and flags what matters. It can pick up on emotion, silence, repetition.

Put simply:

• Call tracking helps with attribution.
• Conversation intelligence software helps with action.

Most modern platforms now include both under the hood, call tracking for logistics, conversation intelligence software for performance, visibility, and strategy.

How Does Conversation Intelligence Software Work?

According to Gartner, only 14% of companies have a full 360-degree view of their customers. A common reason is that brands simply aren’t capturing the correct information. Conversation intelligence software allows companies to capture behind-the-scenes insights from each discussion.

Some solutions are offered as a standalone service that integrates with companies’ existing communication platforms. Others are delivered as part of a comprehensive CCaaS and CX platform. For instance, companies like NICE and Dialpad bake conversation intelligence into their contact center toolkits.

At the core, conversation intelligence software follows a simple process:
Capture → Transcribe → Analyze → Surface → Integrate.

1. Capture the Interaction

The software connects directly into communication channels like voice calls, video meetings, chat platforms, messaging tools, support tickets. This works across:

• Phone systems
• Contact center platforms
• CPaaS environments
• CRMs with integrated telephony

Tools that sit within or beside unified platforms like Salesforce, Zendesk, or Microsoft Teams often enable easier capture.

2. Transcribe in Real Time or Post-Call

Once captured, speech recognition engines take over. These transcriptions don’t just turn voice into text, they break it down by speaker, timestamp, and turn.

The better systems also adjust for:

• Accents
• Background noise
• Low audio quality
• Multilingual input

This makes the software reliable in places where it matters, like support floors, warehouse headsets, even call centers handling inbound traffic from multiple countries.

3. Analyze the Content

Using natural language processing (NLP) and trained AI models, the platform parses:

• Emotional tone
• Topic changes
• Key phrases (e.g. “cancel my account” or “unauthorized charge”)
• Silences, overlaps, talk-time ratios
• Escalation signals or missed handoffs

It doesn’t just flag keywords. It reads the room.

4. Surface What Matters

After analysis, the software highlights what deserves attention:

• Coaching moments
• Compliance gaps
• Repeat questions
• Emerging complaints
• Promoters and detractors

Managers don’t need to dig through 500 calls. They get a shortlist of the 12 that matter, already tagged, summarized, and scored.

5. Integrate Across Systems

Finally, CI software syncs into:

• CRMs (auto-logging notes, next steps, and keywords)
• CDPs (feeding voice-of-the-customer data)
• QA systems (auto-grading reps or flagging calls)
• Business intelligence tools (showing macro trends)

This makes conversation intelligence part of a larger enterprise data strategy.

What is Conversation Intelligence Software Used For?

What makes conversation intelligence software valuable across an enterprise isn’t just the data it captures. It’s the flexibility. Whether the goal is to close more deals, reduce call escalations, train new hires faster, or spot product issues earlier, CI tools pick up the same thread: real customer language.

Customer Service and Contact Centers

Support leaders use CI to track common friction points. If “can’t log in” jumps in frequency over a week, it shows up. If one region’s agents are over-talking customers, QA sees it. That means teams can fix patterns before they become reviews.

Common service-side use cases:

• Auto-QA and compliance tracking
• Sentiment scoring for escalations
• Coaching triggers (e.g., missed empathy or policy adherence)
• Script adherence and tone consistency

Sales and Revenue Operations

Sales leaders track pricing objections, competitor mentions, and top-performer language across thousands of conversations. CI tools surface what separates strong reps from average ones, then build coaching around it.

Common use cases:

• Identifying buyer hesitation earlier in the sales cycle
• Comparing messaging impact across geos or personas
• Flagging “stall” language or trigger phrases
• Creating highlight reels for new hire ramp-up

While sales teams were early adopters of CI, today’s tools have moved well beyond scripts and playbooks.

Marketing and Product Teams

Marketers spend weeks A/B testing copy. Meanwhile, support teams hear how customers describe the product every day.

CI bridges that gap.

Use cases for marketing/product:

• Harvesting real customer language for landing pages or ads
• Surfacing feature requests directly from support calls
• Identifying language that correlates with conversions
• Testing new positioning in live sales calls

The feedback loop shortens. Instead of waiting on survey data, teams get instant input from the field.

To expand that loop further, marketing teams often integrate CI with CDPs and VoC platforms.

CX, Strategy, and Executive Leadership

CI tools create executive-level dashboards showing what’s happening across teams without digging into every interaction. Instead of relying on anecdotal reports, leaders can track real data from real customer language.

Use cases for executives:

• Trend dashboards showing shifts in sentiment or churn drivers
• Monitoring compliance or script adherence across teams
• Tracking campaign or product feedback in live conversations
• Aligning training investments with actual coaching gaps

This creates alignment across the C-suite. Marketing hears what sales hears. Product sees what support sees.

The Benefits of Conversation Intelligence Software

At scale, conversation intelligence software is a feedback engine, coaching assistant, compliance layer and a strategy map. It doesn’t ask teams to change how they work; it plugs into what they’re already doing, then sharpens it.

Faster, Smarter Coaching

One of the reasons conversational intelligence software is becoming so popular in the modern world is that it can help to enhance agent and rep training. AI solutions can capture information from every conversation in the business landscape and determine “best action” strategies for different use cases.

This can lead to better training opportunities for customer service reps, who might need help navigating complex problems with customers. It can also empower companies to create more efficient sales professionals with step-by-step coaching and guidance for closing deals.

Many solutions now plug into WEM tools too, so companies can get real insights into the impact of training initiatives.

Real-Time Customer Insight

Forget surveys. Conversation data is live. Teams can track sentiment trends, spot emerging complaints, and identify product confusion before it spreads.

It’s a faster route to Voice of the Customer feedback, and it’s based on what customers say unprompted. Conversation intelligence software allows companies to dive into the intent, sentiment, and guiding elements behind what customers say. They can monitor conversations in virtually any channel and use words, tone, and dialect to unlock insights.

Improved Customer Experience

Conversation intelligence software doesn’t just provide a behind-the-scenes view into customer intent and sentiment. It can also track trends and patterns in the customer journey.

With the right tools to help companies discover common customer pain points, purchase cycle friction, and consumer goals, teams can develop a more compelling customer journey map. Business leaders can determine how to structure conversations to drive better outcomes.

It’s even possible to use the data gathered from conversation intelligence software to build more effective self-service tools. Intelligent IVR systems, chatbots powered by generative AI, and virtual assistants can all be enhanced with the data teams collect.

Risk and Compliance Coverage

Conversation intelligence solutions are excellent at rapidly recognizing keywords and phrases in a discussion. This makes them perfect for improving compliance in the contact center environment. Companies can use tools to track non-compliance instances during conversations.

For instance, a solution could track whether an agent reads a statement related to GDPR before collecting personal information from a customer. AI tools can automatically remind agents to issue notifications or alert supervisors when they don’t.

By creating simple summaries and transcriptions, these tools also make it easier for companies to search through content for compliance issues during auditing sessions.

Improve productivity and efficiency

CI software can work automatically behind the scenes. It captures information in real-time, reducing the strain on team members to collect data and make notes. With conversation intelligence software, companies can automatically create summaries, action items, and notes for their agents.

The right tools can transform complex transcripts into easy-to-follow snippets of text, which help businesses rapidly identify customer pain points and issues. These AI solutions can notify business leaders and teams about changing customer trends.

Conversation intelligence solutions can keep team members on track during calls, with virtual assistants offering real-time coaching, next-best-action guidance, and support. Some tools can even surface historical information during a call or discussion.

Top Features to Look for in Conversation Intelligence Software

Enterprise buyers are looking for systems that reduce manual effort, improve visibility, and connect the dots between teams. The best conversation intelligence software isn’t just feature-rich. It’s frictionless. Here’s what matters most when evaluating platforms:

• Real-Time and Post-Call Transcription: Transcripts should be accurate, speaker-separated, and context-aware. Look for tools that handle heavy accents, background noise, or mixed languages without breaking. Real-time transcription is key for live coaching and support. Post-call is useful for deeper QA and trend analysis.
• AI-Powered Sentiment and Intent Detection: Basic keyword tracking isn’t enough. Teams will want systems that understand tone, pacing, hesitation, sarcasm and silence. These tools should flag frustration during a call, missed empathy from an agent, and customer confusion or withdrawal.
• Coaching and Performance Feedback: Look for tools that can score reps automatically based on tone, or missed steps, recommend personalized coaching strategies, provide real-time advice, and compare team performance over time.
• Workflow Integration: The best CI software doesn’t create another destination. It pushes insights directly into where people already work, whether that’s Salesforce, HubSpot, Zendesk, or Microsoft Dynamics. It should connect with BI, CDP, WEM, and contact center solutions without friction.
• Compliance and QA Monitoring: In regulated industries, businesses need customizable rulesets to flag when legal language is missed or processes aren’t followed. This includes call grading against internal QA benchmarks, detection of compliance phrases, and more.
• Flexible Deployment and Customization: No two businesses run the same workflows. ACI solution should let companies adjust scoring models, build custom triggers, and choose different setups based on needs.

Examples of Conversation Intelligence Software

Conversation intelligence software is a growing landscape with various tools. The best conversation intelligence software for any business will depend on the goals they want to accomplish. For instance, in the customer experience landscape, solutions include:

• CallMiner: CallMiner’s collectionof conversational analytics and intelligence tools help companies to automatically score and transcribe conversations from chat, email, and more. The toolkit provides valuable insights into every discussion with automated metrics.
• Verint:Verint’s speech analytical tools come built into its contact center platform, helping companies to categorize and learn from calls. The solution can even score customers “at risk” in the purchasing cycle, reducing the risk of churn.
• NICE: NICE combines real-time speech analytics, transcription, and recording tools with innovative new solutions in generative AI. Companies can use behind-the-scenes insights into sentiment analysis, real-time agent coaching, and more.
• Observe.ai: The Observe.ai agent enablement platform is powered by voice AI, helping companies to analyze calls, evaluate agents, and coach teams. It also ensures teams can maintain complete visibility into the entire customer journey.
• Dialpad: Dialpad’s AI-powered UC and contact center tools come with artificial intelligence built-in. They offer real-time coaching, transcription, recording solutions for every channel, and automated analytics and dashboards.

Other companies focus on the sales and marketing landscape. For instance, HubSpot offers promotional teams a comprehensive marketing conversation intelligence toolkit.

How to Choose the Right Conversation Intelligence Software

The wrong CI tool can feel like another dashboard no one checks. The right one transforms how entire teams listen, coach, and make decisions. Across industries, the most successful CI deployments have one thing in common: alignment. The platform fits the business.

Here’s how to get there.

Start with Use Cases, Not Features

Before comparing vendors, lock down the problem to solve. Common enterprise-level goals include:

• Increasing first contact resolution in contact centers
• Shortening onboarding and improving rep ramp-up
• Reducing regulatory exposure with automated compliance
• Tracking competitor mentions across regions
• Improving NPS, CSAT, or VoC alignment

Map those needs back to workflows, not just departments. For example, if sales, service, and product all use different CRMs or call tools, integration and data normalization will matter more than sentiment accuracy alone.

Check Compatibility with Existing Systems

Any friction here becomes a cost later. Ask:

• Does it integrate with the current CRM, WEM, or contact center platform?
• Can it share data with CDP or BI tools?
• Does it work with voice + chat + video?

Make sure IT is involved early especially if the team is running legacy telephony, hybrid cloud, or strict compliance environments.

Prioritize Data Security and Compliance

• Especially in sectors like healthcare, finance, or government, leaders need to dig into:
• Regional data residency options
• Encryption protocols (in transit and at rest)
• Retention policies and audit logs
• Certifications (e.g., SOC 2, ISO, HIPAA)

Don’t treat this as a bolt-on. Make it a first filter.

Think Scalability and Future Use

Today’s team might only use CI for QA. A year from now, product and marketing could be building strategy from it. Make sure the tool can grow:

Multi-language support

• Role-based access and permissions
• Modular pricing models
• API access for custom workflows

If long-term CX transformation is the goal, scalability is key.

Best Practices for Rolling Out Conversation Intelligence Software

Technology rollout is rarely the hard part. The hard part is getting people to use it, not just log in, but trust it, rely on it, and change how they work because of it.

That’s especially true for conversation intelligence software. The benefits are real, but they don’t show up automatically. Success depends on how the rollout is planned, who’s involved, and how the insights get shared.

• Involve End Users Early: One of the fastest ways to kill adoption is to treat CI like a backend install. This is a frontline tool. Bring in sales leads, support managers, QA coaches, even legal early. Pilot with teams who understand the conversations firsthand. Get their input on tagging logic, scoring criteria, and what “good” actually sounds like.
• Define What Success Looks Like: CI tools can generate hundreds of insights. But if teams don’t know what to look for, they won’t act on them. Set 3–5 clear goals tied to business outcomes. For example: Reduce average handle time by 12%. Build reports and dashboards around those goals.
• Integrate, Don’t Isolate: The biggest rollout mistake? Making CI “just another tool.” Instead: Auto-push call summaries into CRM records. Feed coaching tags into WEM or LMS. Connect keywords to VoC dashboards or ticketing systems
• Turn Insights Into Action Quickly: Don’t let insights sit in reports. Use clips in coaching sessions. Highlight wins in all-hands meetings. Show how one flagged phrase got a customer to stay, or led to a closed deal.
• Start Small, Scale Smart: Don’t flip the switch across all regions on day one. Run a 30- to 60-day test with one team. Learn what works. Adjust scoring models, tweak integration logic, refine tags. Then scale with confidence

What’s Next for Conversation Intelligence Software?

The evolution of conversation intelligence software isn’t about new features, it’s about new roles. CI is moving from a back-office tool to a frontline co-pilot, embedded in real-time workflows and used across entire organizations, not just sales floors or support desks.

Here’s where the tech is heading:

• Real-Time Guidance, Not Just Post-Call Analysis: Until recently, most CI platforms worked in the rearview mirror. Today’s tools offer in-call coaching, pop-up suggestions, and auto-generated prompts as conversations unfold. Whether it’s reminding a rep to verify compliance language or suggesting a next-best action based on sentiment change, CI is becoming an active participant not just a passive observer.
• Deeper AI Personalization: With generative AI in the mix, CI platforms can now summarize calls in natural language, highlight emotional cues, and even recommend what to say next. These summaries are tailored to a user persona, context-aware, and multilingual. Expect to see even greater use of LLMs to personalize scripts, refine training, and coach based on conversation outcomes.
• Omnichannel CI and Non-Voice Integration: Conversations don’t just happen on phones anymore. Messaging, chat, email, and even internal comments all carry signals worth analyzing. Next-gen CI platforms will unify voice and digital channels, and track context across asynchronous interactions.
• More Enterprise-Grade Security and Data Controls: As CI becomes a system of record, the pressure to meet security, sovereignty, and compliance standards increases. Expect to see zero-trust architecture, configurable access permissions, and AI governance frameworks.
• Tighter CX Ecosystem Integration: The smartest CI platforms won’t just report issues, they’ll trigger workflows across platforms. In this world, CI becomes the connective tissue across CX, CRM, BI, and customer feedback management stacks.

Conversation Intelligence Software: From Listening to Leading

Every team talks to customers. Few really listen.

Conversation intelligence software changes that. It filters every interaction for what matters, then puts those insights where they can drive change: in front of agents, managers, strategists, and executives.

It’s a framework for unlocking insights, improving performance, protecting compliance, and elevating every customer touchpoint.

For enterprise teams that want to move faster, operate smarter, and compete in a market shaped by real-time experiences, the question isn’t whether to adopt conversation intelligence. The only question is: Which platform will lead that transformation?

Ready to upgrade? CX Today is here to help:

• Join the Community: Connect with CX professionals, share insights, and shape the future of conversation intelligence.
• Test the Tech: Meet top vendors, explore the tools that drive value, and keep up with the innovations reshaping how teams listen and lead at industry events.
• Plan Your Next Investment: Navigate the CX Today Marketplace for curated insight into the most trusted vendors in CI, CCaaS, CDP, and more.

Or start with the big picture: Explore The Ultimate CX Guide for everything enterprise leaders need to know about modern CX strategy, technology, and transformation.

The right software ensures businesses don’t just collect voice of the customer insights every once in a while, with the occasional survey. These systems pull in signals from different parts of the business, support tickets, call transcripts, reviews, web sessions, and help teams make sense of it all.

As the market for feedback software continues to accelerate, growing at a rate of 11.7% CAGR, it’s time for business leaders to evaluate which vendors can help them better understand their customers. Here are some of the top vendors offering feedback management software in the market today.

The Top Feedback Management Software Vendors

• • Medallia
  • Qualtrics
  • InMoment
  • Concentrix
  • NICE
  • Verint
  • Forsta
  • Alida
  • SMG
  • Avaya
  • Enghouse Interactive
  • NiceReply
  • HubSpot
  • UserTesting
  • UserVoice
  • Chattermill
  • Sprinklr
  • Usersnap
  • Listen360
  • Sogolytics
  • Simplesat
  • Apptentive
  • Outgrow
  • HappyOrNot
  • AskNicely
  • SurveyMonkey
  • TypeForm
  • SurveySparrow
  • Zonka Feedback
  • Survicate

The Top Feedback Management Software Vendors in 2025

There are a lot of platforms in this space. Some are built for enterprise IT teams, others are more hands-on for marketing or CX leads. What they all try to do is solve the same problem: how to take a mess of incoming feedback and turn it into something useful.

The ones listed here stood out for different reasons. Some are stronger on real-time alerts. Some offer deeper integrations. Others are introducing cutting-edge AI. But each one brings something solid to the table, whether the goal is improving retention, closing the loop faster, or just getting clearer visibility into what customers are actually saying.

Medallia

Medallia doesn’t just helps companies build the infrastructure for turning feedback into action, and not just in the call center. Whether it’s a shopper tapping “unhappy” on a kiosk, a customer venting on social media, or a hotel guest filling out a mobile survey, Medallia pulls it all together in one place.

The Experience Cloud is at the center of that. It takes structured and unstructured feedback, from web, voice, video, messaging, and more, and gives teams the tools to actually do something with it. Managers get real-time alerts when things go sideways. AI models pick up on emotion, urgency, or recurring issues before they blow up. And case management tools help teams close the loop, quickly.

For big enterprises juggling global teams, Medallia keeps things flexible. It integrates cleanly with CRMs and service platforms, and offers native support for privacy and compliance across markets.

Qualtrics 

Qualtrics has become one of the first names that comes up when companies talk about experience data. It’s not just a feedback platform; it’s an entire system for understanding how people feel, why they feel that way, and what to do next.

The platform connects different pieces of data from across the customer journey. It brings together survey responses, support interactions, reviews, even operational data, then layers on natural language processing and predictive analytics to help teams make sense of it.

The full XM solution can introduce insights into employee engagement, customer satisfaction, and brand awareness, combining them into a central view. Qualtrics also puts a lot of focus on making feedback visible to the right people. There are tools to build custom dashboards, set up automated alerts, and even link feedback to frontline KPIs.

InMoment 

One of the top feedback management software vendors focusing on the full experience ecosystem, from employee, to customer experience, InMoment offers a powerful platform to business leaders. Named a major player in conversational intelligence and analytics by IDC, InMoment forms part of the Forsta ecosystem.

With the platform, companies can connect feedback from surveys, reviews, digital interactions, and support channels, all in one place. But where InMoment really stands out is in how it handles unstructured data. Its text analytics tools dig into comments, transcripts, and social mentions to pull out the stuff that actually matters, without burying teams in noise.

There’s also a strong focus on actionability. The platform doesn’t just flag issues, it guides users toward what to do about them. That might be a recommendation for a store manager to follow up with a customer, or an alert to the product team about a recurring issue.

Concentrix 

Concentrix takes a different angle on feedback. Instead of focusing just on surveys or scores, it’s more interested in how the entire customer journey feels, and where it breaks down. The iX product suite uses artificial intelligence to clarify every element that impacts experience.

Their platform, ConcentrixCX, pulls feedback from all the usual channels, web, email, messaging, in-store. But what stands out is how the data ties into the bigger picture. Companies don’t just see what went wrong. They see when it happened, where in the journey it started, and what team’s responsible for fixing it.

It’s built with operations in mind. There are tools to route issues, track resolutions, and flag repeat complaints early. Teams can zoom in on individual problems or step back and see trends across products, stores, or regions.

NICE 

NICE has been around long enough to know where feedback fits in a contact center. It’s not something you look at once a week. It’s something you act on in real time.

Their CXone Feedback platform is built to do exactly that. It pulls in survey responses across channels and connects them to what’s happening inside the operation. That might be call wait times, escalation rates, or agent notes.

Enlighten AI is where it starts to go deeper. It scans responses for urgency, flags issues with high emotional weight, and surfaces patterns before they show up in your metrics. It can even trigger follow-up workflows automatically, so teams aren’t stuck reacting after the fact.

Verint 

CX and contact center innovator Verint offers a comprehensive toolkit to businesses in search of feedback management solutions. The platform supports multichannel surveying, to help businesses capture input across a range of platforms. Businesses can develop multi-modal campaigns, and utilize conditional logic to boost the chances of receiving relevant insights.

One feature that stands out is Open Feedback. It gives companies a way to capture unsolicited input, things like chat logs, forum comments, or in-app messages, and blend it with formal surveys. It’s especially useful for teams that want more than NPS trends.

Verint’s tools also align with other components of the Verint toolkit, from the agent copilot system, to the platform for in-depth business analytics, workforce engagement, and knowledge management.

Forsta 

Forsta is a software company committed to helping organizations access and leverage the voice of the customer. The digital feedback platform allows brands to use their website and company apps to build real-time views of digital customer journeys.

Forsta’s solutions are now aligned with the tools offered by InMoment, but there are plenty of other features to explore too. Forsta can mix structured and unstructured data into enlightening reports, and visualize patterns across customer journey.

There’s a big emphasis on presentation too. Dashboards, journey maps, and reports can be tailored for different teams, from the C-suite to frontline ops. Forsta also integrates easily with a range of other systems through open APIs and pre-built connectors.

Alida 

VOC company Alida specializes in total experience management, giving businesses the tools they need to collect insights from both employees and customers at the same time. The all-in-one toolkit comes with access to survey creation tools, allowing businesses to build branded surveys which focus on collecting data about specific KPIs and CX metrics.

The core of the system is a mix of survey tools, digital intercepts, and always-on feedback channels. But what makes it different is how it connects that feedback to actions. Users can tag ideas, vote on priorities, or track the progress of their suggestions through a branded portal.

Alida offers solid analytics and reporting too. Teams can slice feedback by customer type, location, or product line, and push results into CRM or support tools through native integrations. For product teams, it’s a clean way to spot patterns. For CX leaders, it’s a fast read on what’s improving, and what’s not.

SMG 

Experience and feedback management software vendor, SMG gives brands the tools they need to track customer experiences, and map buyer journeys. The platform offers insights into everything from customer sentiment to pain points, ratings, and reviews across a variety of channels.

They system collects data through short, mobile-friendly surveys, usually triggered right after a visit or transaction. The goal is to keep response rates high and get results in quickly. Store managers and frontline teams get daily alerts, so they’re not waiting weeks for head office to flag an issue.

The SMG platform comes with a comprehensive reporting and analytics kit too, marrying CX data with business intelligence, benchmarking, and AI-native text analytics. Companies can utilize role-based reporting tools, sort through data using API-centric open architecture, and even leverage real-time views of metrics with a mobile reporting app.

Avaya

Avaya’s been known for decades as a leading contact center vendor. But in recent years, they’ve put more energy into customer experience, and feedback now plays a bigger part in that.

Their voice-of-the-customer tools are integrated into the broader Avaya ecosystem. That means companies using Avaya for customer service don’t need to bolt on separate survey tools, they can trigger feedback requests automatically based on call outcomes, chatbot conversations, or agent interactions.

The platform supports voice, SMS, and digital surveys, with basic analytics and response tracking. It’s not as advanced as some of the standalone tools, but it’s tightly connected to contact center workflows, and workforce management strategies.

Enghouse Interactive

Enghouse keeps things straightforward. Their survey management tools are designed to plug directly into the contact center, so companies can gather feedback without adding a new system or changing how agents work.

It supports surveys across voice, email, and web, and lets teams build rules around when and how those surveys go out. That might be after a resolved case, a missed SLA, or a completed call. The feedback flows into dashboards where supervisors can review trends and drill into individual interactions. Enghouse plays well with existing systems too.

It integrates with Microsoft Teams and other enterprise tools, making it easier for hybrid and remote teams to stay aligned. Plus, the company also offers a voice of the customer (VoC) tool that aims to take customer listening to the next level.

NiceReply 

Leading customer experience and feedback management software vendor NiceReply offers a simple way to collect, manage and understand customer feedback. The company’s platform delivers access to a range of survey templates designed to assist organizations in tracking customer satisfaction scores, NPS, and more.

Business leaders can use NiceReply to send post-resolution, and in-signature email surveys, survey links, and other requests for feedback to clients in various channels.Most teams use it to track things like CSAT or NPS inside their helpdesk. The big draw is how well it fits into tools like Zendesk, Intercom, or Freshdesk.

There are some great reporting tools for teams that want to track trends or filter by agent or team. Leaders can also get alerts when something goes off track, like a drop in satisfaction or a spike in negative comments.

HubSpot 

Software as a service company HubSpot produces various flexible solutions for marketing, sales and service teams. As part of the organization’s comprehensive Service Hub, business leaders can access simple customer feedback software.

The solution includes tools for creating customer feedback surveys and sending them to clients across numerous channels, such as web links and email. Teams can send out NPS, CSAT, or CES surveys by email or display them on a website. The setup is quick, and responses go straight into contact records, so reps can see a customer’s history and recent sentiment in one view.

HubSpot’s automation features are excellent too. Companies can trigger surveys after a ticket closes, or start a workflow when someone leaves a low score.

UserTesting 

UserTesting gives you something most platforms don’t: context businesses can actually see and hear. Instead of asking customers how they feel, it shows organizations what they do and what’s getting in their way.

Businesses can set up a task, like using a new feature or finding information on a site. Then they pick an audience, and within a few hours, they’ll have screen recordings of real people going through the process, talking out loud as they go.

Teams can learn fast what’s working, what’s confusing, and what’s just broken. It’s especially useful for product and UX teams trying to catch issues early, before they ship. The platform also works for things like onboarding flows, email tests, or internal tools.

UserVoice 

UserVoice is built for one specific job: helping product teams understand what customers actually want, and giving them a way to act on it. It’s not a generic survey tool. It’s more like a shared suggestion box for growing companies.

Users submit requests, vote on features, and leave comments. Teams can sort through it all, group similar ideas, and track what’s picking up steam. There’s a workflow for tagging requests by customer segment or priority, and a feedback status feature to show which ideas are being reviewed, planned, or already launched.

Companies can even leverage an in-app feedback widget for their existing SaaS solutions. Built-in analytics capabilities make converting raw data into actionable insights easier too.

Chattermill 

Chattermill helps companies make sense of unstructured feedback at scale. Instead of looking at one channel at a time, it brings together reviews, survey comments, support tickets, and social posts, then runs them through natural language models to surface themes and patterns.

Teams get alerts when a new issue starts trending, or when sentiment drops around a specific product or region. AI systems can also automatically surface common trends and pain points. Chattermill’s platform can pull various customer comments and survey responses into one environment.

The machine learning models categorize feedback automatically and provide suggestions based on insights. Plus, companies can leverage built-in translation features and intelligent filters to help them sort through data.

Sprinklr

Sprinklr isn’t just a feedback management software vendor. It’s more like a full-blown CX stack for companies with large digital footprints. But buried inside that stack is a solid set of feedback tools that help track what people are saying across dozens of public and private channels.

It’s especially strong on social and digital listening. Teams can monitor conversations across platforms, while also pulling in reviews and customer support transcripts. Feedback gets sorted by theme, urgency, and even emotion, using built-in AI models.

What sets Sprinklr apart is how feedback connects with everything else. You can link insights to marketing campaigns, sales initiatives, or support operations.

Usersnap 

Usersnap is a specialist feedback management software solution provider focused on helping businesses make better decisions for growth. It concentrates mainly on highlighting insights connected to how customers use digital products.

Mostly, this platform attracts product and engineering teams that need to spot bugs, flag usability issues, or gather quick input during development. When users click a feedback button, they can annotate the screen, leave a comment, and submit it, all without leaving the page.

Companies can build branded portals for beta testers of products, visualize data with graphs and charts, and use AI to prioritize fixes and updates by impact. The platform also integrates seamlessly with tools like Jira, Slack, and Microsoft Teams.

Listen360 

Customer engagement and feedback management software vendors, Listen360 support brands in capturing actionable feedback from consumers throughout the customer journey. The suite of tools helps companies to keep quality consistent across every branch, partner, or location.

The platform sends short, post-interaction surveys to users right after a customer visit or service. Results come in quickly, and managers get real-time alerts when someone leaves a negative score or mentions a specific issue.

What’s helpful is how the data rolls up. Local teams see their own results, while head office can monitor trends across the entire network. There are tools for flagging problem areas, benchmarking locations, and even triggering follow-ups when someone leaves a comment worth chasing.

Sogolytics 

Software vendors Sogolytics design a host of tools for companies across various industries, from government groups to financial services. To help organizations take advantage of the benefits the voice of the customer can offer, Sogolytics embeds a range of feedback management capabilities into its platform.

Brands can use the technology to collect customer feedback across multiple channels and then automate responses for quick follow-up and resolution. There’s a built-in engine for digging into patterns, so you’re not just looking at response rates, but what’s driving them.

The Sogolytics platform also has built-in ticket management functionality to help professionals pinpoint which customer conversations they need to follow up with faster. Plus, analytics and reporting tools are available to assist business leaders in tracking trends.

Simplesat 

Built to help companies track, monitor, and improve their customer satisfaction scores, Simplesat is a straightforward software solution for feedback management.

Most teams embed Simplesat surveys directly into emails or ticket signatures. Customers rate the experience with one click, and the feedback shows up instantly in dashboards. It works with tools like Zendesk, Help Scout, and Intercom, so there’s no complex integration work.

The reporting is straightforward. Businesses can filter by agent, customer, or team, and set alerts when scores drop below a certain level. There’s also a handy testimonial feature that lets you turn positive feedback into social proof.

Apptentive (Alchemer Mobile)

Alchemer Mobile—previously known as Apptentive, specializes in in-app feedback. The platform supports brands in capturing messages from customers across various mobile channels. Teams can gather insights from customers when they’re using a product, in real-time. Everything happens in context, with minimal friction for the user.

The platform includes targeting tools to make sure feedback prompts only show up when they’re relevant, based on behavior, location, or time in-app. On the backend, product and marketing teams get a clear view of sentiment trends and response rates.

The system also offers tools for quizzes, polls, exams, and questionnaires. Plus, the company promises end-to-end security and compliance with ISO 27001, SOC 2 type 2, and GDPR.

Outgrow 

Outgrow is a little different from most platforms on this top feedback management software list. It’s not strictly a feedback tool; it’s more of a content builder that helps businesses engage people through interactive experiences like quizzes, calculators, polls, and forms.

Companies create short, dynamic surveys that don’t feel like traditional feedback forms. Organizations can collect customer preferences, reactions, or satisfaction scores through personalised flows, and embed them directly on websites, landing pages, or in emails.

It’s especially popular with marketing teams that want to turn passive visitors into active participants, and get a bit of insight in the process. There’s built-in logic, so users get different questions based on how they respond, and results can be routed into CRM or analytics tools.

HappyOrNot 

Most people have seen HappyOrNot terminals before, four smiley-faced buttons at checkout counters, airports, or public service desks. Behind those buttons is a platform built to help businesses understand how customers feel in the moment, without needing them to fill out a full survey.

The system is built for high-traffic, in-person environments. Feedback is anonymous, fast, and easy for anyone to give. HappyOrNot transforms data into visual graphs and reports, which users can easily share with members of their team. The platform also supports a variety of use cases, allowing brands to embed feedback functionality into apps and websites, touchscreen displays, and terminals or kiosks.

Real-time notifications and alerts even help to keep staff members on the same page. Plus, data gets rolled up into dashboards with hourly and daily trends, so managers can see performance patterns and make staffing or operational adjustments on the fly.

AskNicely 

AskNicely is focused on frontline teams. The platform is built around one idea: happy employees make for happy customers, and feedback should flow both ways.

It starts with fast, simple surveys that are typically tied to specific service moments. Customers give a quick rating and a short comment, which shows up instantly in team dashboards. Those insights are surfaced in real time, with the option to recognize high performers or coach around recurring issues.

AskNicely also includes goal-tracking tools and workflows that help teams close the loop. Companies can trigger follow-ups, track improvement over time, and share wins across locations. The flexible platform can connect with more than 50 leading tools, such as Microsoft Dynamics and Freshdesk.

SurveyMonkey 

Focused on the area of survey software, SurveyMonkey supports businesses in asking more relevant questions of their target audience. The platform aims to streamline the quest for customer feedback by allowing teams to build surveys faster and more efficiently, using convenient templates with pre-written questions.

Depending on the package the business chooses, SurveyMonkey’s technology can also include access to collaboration tools for teams. Within all plans, the SurveyMonkey service helps brands to manage multiple users, gain insight into customer sentiment, and preserve confidential data.

Additionally, automation systems, APIs, and powerful integrations help to align crucial customer data in one easy-to-follow workflow. There’s also built-in AI to make finding trends and opportunities across marketing, HR, product, and CX easier.

TypeForm 

Typeform is a feedback management software solution built around conversational forms. It helps businesses gather insights one question at a time, with clean, straightforward and interactive experiences, and a focus on keeping users engaged from start to finish.

The platform is ideal for marketers, product teams, and UX researchers who want to collect feedback without losing people halfway through. Companies can customize the look and flow, embed surveys on your site, and route answers to existing tools. In fact, Typeform integrates with more than 300 business apps.

According to the company, 95% of their clients gather data more easily after integrating their tools, and 87% say they end up with better insights into their target audience.

SurveySparrow 

Supporting companies in building more human, conversational relationships with customers, SurveySparrow is an omnichannel experience management platform. The solution comes with a built-in Business Intelligence system where teams can track KPIs and metrics related to core goals and campaigns. Plus, users can also leverage case management tools in the same place.

With solutions for automating customer interactions across a variety of channels, SurveySparrow supports companies in better understanding their audience’s journey. Plus, with a convenient survey builder, teams can rapidly design forms for clients to fill in minutes without the need for any coding or design knowledge.

SurveySparrow’s platform also includes tools for unlocking insights with AI, building trust with reputation management, and even service ticket routing.

Zonka Feedback 

Omnichannel survey software vendor Zonka Feedback prioritizes helping companies to improve customer satisfaction scores. Powered by AI, Zonka transforms unstructured feedback form chats, tickets surveys and more into actionable intelligence.

Companies can analyze customer service themes, score sentiment, and even use agentic AI to resolve issues and improve interactions in real-time. There are also customizable dashboards which allow businesses to deliver role-based insights to each department.

Plus, the straightforward platform also allows staff to export and share data easily. Zonka Feedback also helps businesses with listening to the voice of the employee, with employee feedback monitoring and surveys for tracking eNPS.

Survicate 

Survey and NPS software vendor Survicate provides businesses the tools they need to create custom surveys and learn more about their target audience. There are no survey limits or time limits on any of the plans offered by the company, ensuring teams can get a comprehensive view of customer sentiment and perception.

The platform supports email, link, and in-app surveys, with a library of templates for CSAT, CES, NPS, and feature requests. Companies can also segment results by user data, which makes it easier to spot patterns across customer types.

The data visualization tools are excellent, allowing companies to break down results into comprehensive dashboards with color coded insights.

Unlocking Insights with the Top Feedback Management Software

Every platform in this guide solves a slightly different problem. Some are built for frontline teams, others for product managers or digital teams. A few try to cover everything. But all of these systems make feedback easier to collect, understand, and act on.

The right fit depends on what kind of feedback matters most to each enterprise. Some companies need real-time alerts when something goes wrong. Others need long-term trend data to guide product decisions. Some just want a clean way to capture input across multiple locations without drowning in noise.

There’s no perfect platform. But there are smart, focused tools that can help businesses get closer to your customers. For those still struggling to make the right decision, CX Today offers a range of resources to drive progress forward:

• Dig into the data: Get exclusive insights from proprietary market research and reports, designed for CX leaders.
• Join the conversation: Learn from peers and thought leaders in the dynamic CX Community environment, and discover new ways to solve complex problems.
• See the tools live: Visit upcoming events and conferences where business leaders can put the latest software and systems to the test.
• Prepare a purchasing plan: Use our CX Buyer’s Guide to map out the next steps for every CX-focused investment strategy.

For enterprises ready to unlock the full value of surveys, polls, audience and employee data, CX Today is here to make the process easier, more strategic, and more valuable, one step at a time.