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.

With global enterprises like BT, Deutsche Telekom, and EE already seeing results, the discussion explores how hybrid human-AI teams, composable experience design, and data-driven automation are shaping the contact center of 2026 — and how a unified CX platform can future-proof operations and drive measurable business value.

In this CX Today interview, Rob Scott sits down with Shrenik Jain, VP of Product Management for CCaaS at Sprinklr, to explore what’s next for contact centers and how Sprinklr is taking a platform-first approach to transform customer experience.

Jain explains why Sprinklr didn’t follow the legacy voice-first route, how unification enables smarter AI, and what the shift from assistant AI to agentic AI means for tomorrow’s CX workforce. If you’re rethinking your contact center strategy for 2026, this one’s worth a watch.

Key Discussion Points:

• The real reason CCaaS is saturated: Why traditional cloud migration is no longer enough, and what customers now expect.
• Connected intelligence over channel sprawl: How Sprinklr integrates social, voice, messaging, and AI into a single platform.
• The rise of agentic AI: What moving from reactive assistants to autonomous agents means for skills, roles, and workforce planning.
• Actionable insights, not just dashboards: How AI is shifting from descriptive to prescriptive, and even autonomous decision-making.

To explore Sprinklr’s unified CXM platform and how it enables smarter, scalable, AI-powered customer engagement, visit sprinklr.com

The AI startup will allow UJET to continue its AI roadmap for enhanced customer service solutions. 

This partnership will also address customer data analysis issues for UJET’s enterprise customers. 

This acquisition is set to further UJET’s AI roadmap vision by bolstering the company’s AI capabilities and addressing customer experience concerns. 

By highlighting these issues of visibility between customer and leader, organizations will be able to improve their customer issues before they reach escalation. 

In fact, UJET has reported that organizations that are unaware of these individual customer problems are losing approximately $5MN-$30MN in customer churn revenue. 

This can be linked to ignored or forgotten negative customer experience complaints, with organizations reportedly gathering only five percent of reported customer issues. 

According to UJET CEO, Vasili Triant, customer churn remains a blind spot for many enterprises, arguing that customer interaction analysis is not done effectively. 

He said: “Most companies can’t analyze interaction data at scale, leaving many common customer issues in the dark.” 

However, this acquisition provides enterprises the capabilities to view all customer conversations through unifying collected data. 

He added: 

“UJET’s acquisition of Spiral will provide businesses with a unified view of all customer conversations for more proactive, personalized service.”

This will also help enterprises locate blind spots in other areas of the business, such as product, other services, and the company itself. 

In conversation with CX Today, UJET VP Product Marketer, Matthew Clare, highlighted how other areas of companies can utilize this tool to understand their customers’ needs:

“This could be used by product teams to understand product and service issues – by marketing teams who want to understand what customers are saying about campaigns that are running.” 

Spiral’s AI Product 

Spiral is an AI startup specializing in conversational analytics to improve customer experience data. 

By leveraging AI, Spiral can be used to analyze customer interactions at scale to uncover pain points in customer experience, whilst also offering proactive recommendations to enterprises. 

The product can also be used to analyze various customer conversations across voice and chat channels, the internet, online reviews and surveys, and social media. 

Clare stated: “Anywhere customer conversations happen is a data source for this product.” 

Furthermore, this tool can be used to ask questions about customer churning and how enterprises can respond to these results through predictions to improve future customer experiences. 

“They are trying to solve the problems of customer conversations and customer feedback being spread across different teams and organizations,” he said. 

“How do you not only unify data but bring it together in a way that anyone in the organization can run deep research with a simple conversational AI agent?” 

This acquisition allows UJET to strengthen its status as a prominent CCaaS platform provider and offer customers an improved version of what is already available. 

Clare explained that the purchase will extend “UJET’s reach and gives us the ability to sell Conversational Analytics over the top of any Contact Center and CX software that may be in place, without having us need to position our end to end CCaaS platform.”

For Spiral, this acquisition will allow them to continue providing conversational intelligence alongside UJET’s AI service capabilities, rebranding as Spiral by UJET. 

Elena Zhizhimontova, Founder and CEO of Spiral, discussed how the acquisition will allow them to prioritize a customer-focused plan and continue to improve customer outcomes for a wider enterprise range. 

She said: “We built Spiral to take millions of customer conversations and turn them into clear, actionable insight,”  

“By combining Spiral’s AI with UJET’s cutting-edge CCaaS platform for modern-day customer service, Spiral by UJET will continue as the focused product our customers rely on, now with a more CX-driven roadmap and deeper integrations. 

“Together we can shine a brighter light on customer issues for more organizations worldwide, giving brands the clarity they need to spot issues sooner, address problems faster, and create better products, services, and experiences over the long term.”

Customer Feedback

This partnership will allow current and future customers of UJET to experience Spiral’s product integrally by improving its overall AI and product organization. 

Turo, a long-term customer of both UJET and Spiral, has reaped the benefits of both these companies’ approaches to solving customer issues, as well as having collaborated on a program with Spiral to improve its data collection method. 

Julie Weingardt, Chief Operations Officer at Turo, emphasized how both companies have enabled them to receive customer experience resolutions with reduced friction. 

She said: “Spiral’s AI transformed our approach and helped us build a Voice of the Customer program that is smart and strategic, by capturing structured feedback during the support journey.  

“Spiral AI’s platform allows us to analyze customer conversations and commentary, pinpointing areas where we can improve proactively. 

“We’ve used these insights to refine our self-service options, hone our knowledge base, and help better guide quality agent responses.”

Despite the acquisition, Spiral has confirmed that it will continue to work with its existing customers and products however with UJET integrations.

Spiral was acquired by UJET for an undisclosed amount.

Christian Draeger, who runs passenger experience there, talks about it in a way that’s surprisingly down-to-earth. “We’re not just starting at the airport door,” he says. “We’re already looking at customers, how they can get prepared for their travel, even days ahead of the actual travel plans.”

That’s a different way of thinking about travel, one where the airport is part of the journey, not a pause in it. Draeger’s rule is simple: “Put the passenger in the center.”

That idea is becoming more important. Around two-thirds of travelers now use AI tools to plan their trips, and most say they want services that adjust to them, not the other way around. Berlin’s answer is to mix technology with empathy, using automation to remove hassle, not humanity, and turn the everyday airport routine into something that actually works for people.

Understanding & Designing for the Modern Traveler

Christian Draeger has spent a lifetime around airports. More than thirty years in aviation have given him a deep sense of how people move, wait, and connect. During his time with Star Alliance, he helped shape what millions of passengers now recognize as the modern travel experience. When he joined Berlin Brandenburg Airport, he came in ready to rethink that experience from the ground up.

Berlin handles around 25 million passengers a year, so it’s big enough to be busy, but small enough to still care. “We also operate our premium services: two business-class lounges and an ultra-premium lounge where you get à la carte dining and a chauffeur service to the aircraft,” Draeger said.

That same care for detail extends to the parts of the journey most people barely notice. The airport also took control of its own security operations, because, as Draeger puts it, “We felt that the mandate of the federal police didn’t provide enough attention towards the passenger experience.”

Now there are 32 security lanes, 24 fitted with advanced CT scanners, so passengers can keep laptops in their bags and carry small amounts of liquid without delay. “It’s about having a consistent experience across the whole area of the airport,” he says.

Every choice is made with the passenger in mind. “It starts really by knowing our customers,” Draeger says. “If we have a family that’s traveling once a year on holiday, their prerogatives are different from a business-class customer focused on getting through as efficiently as possible.”

That balance, efficiency for some, discovery for others, is at the heart of personalization in travel, and it’s essential. A recent study found that 93 percent of travelers now expect some form of tailored service. Berlin’s approach proves those numbers translate into real-world design decisions: better security flow, less queuing, and even duty-free areas reimagined as “specialized marketplaces.”

Dual-Terminal Strategy: Two Philosophies, One Vision

A walk through Berlin Brandenburg Airport reveals something a bit different. Its two terminals don’t just separate airlines; they reflect two completely distinct types of travelers. One is designed for comfort, the other for speed. Together, they show how personalization in travel can be built into the physical space, not only into digital systems.

“The level of automation that you will find with low-cost carriers is more in focus than with a legacy carrier,” says Draeger. Terminal 2 is the efficient, minimalist one: smaller, sharper, and geared toward travelers who value simplicity and price over perks. “Terminal 2 is geared to simplicity and generating additional revenues through add-on services,” he explains.

Think self-service kiosks, intuitive wayfinding, and a layout that helps people move quickly from curb to gate. “The utilization of busses is less, you have more walk boardings,” he adds.

Terminal 1, meanwhile, is a different rhythm altogether. “It’s about efficiency and comfort, both guided by digital tools.” Business and frequent flyers pass through airport automation that’s designed to make the process seamless. Over a hundred self-service kiosks are spread across the terminal, complemented by digital signage and premium lounges.

It’s the physical version of a digital truth: no two passengers want the same thing. Some want to breeze through with a coffee and a boarding pass on their phone. Others want time, space, and a glass of something cold before they fly. Both deserve an experience that feels intentional.

That’s what Berlin is building, a new kind of airport customer experience where infrastructure itself becomes a form of personalization. Different terminals, different tools, same philosophy: know who’s traveling, and design accordingly.

AI and Automation Enhancing Personalization in Travel

Like most airports, Berlin once relied on a traditional call center. It worked, but just barely. “We were looking at our call center and we weren’t completely happy,” says Draeger. “It was limited, inconsistent, and expensive.”

That frustration turned into an opportunity. Berlin decided to replace its call center entirely with a generative AI-powered system. The result was “Berry”, Berlin’s always-on virtual assistant.

“Customers can call the AI hotline and have a conversation just like we’re having right now,” Draeger says. It took just six weeks to build and launch, and within a few months, the results were striking: satisfaction above 85 percent, costs down 65 percent, and service available 24/7.

The human element didn’t vanish; it just found a new home. Instead of waiting in phone queues, travelers get answers right away. Lost something? Need flight details? Berry, the airport’s AI agent, takes care of it and loops in a person if the question needs a human touch. It’s simple to use too: one phone number on Berlin Airport’s website connects straight to Berry.

Building the AI Layer with Berry

Behind the scenes, Berry learns fast. “After six to eight weeks we reached an acceptable level… then you could see week-to-week improvements as GenAI learned,” Draeger explains. His team fed the system with real passenger questions and prioritized the most urgent topics first, like the classic “I left my laptop on the aircraft.” “We prioritized major customer concerns to ensure correct routing from day one,” he says.

Now the airport is preparing for the next step, chat. “We want to also offer the ability to get in touch with our AI agent through chat functionality,” says Draeger. QR codes will soon appear throughout the terminals, linking passengers directly to Berry via chat, integrated into the website and app. “If you’re standing in the arrivals hall, we’ll know based on the QR code where you are, and tailor the information accordingly.”

The idea is to build truly contextual assistance: a passenger in departures might ask about gate directions or restaurants, while someone at baggage reclaim could get help locating transport or lost luggage. “Customers can switch between voice and chat depending on environment or age. My children would prefer to talk; someone in a crowded terminal might prefer to chat,” Draeger says.

Operational AI and the Quest for Seamlessness

A lot of what makes Berlin Brandenburg Airport work isn’t something you can see. It happens on the tarmac between the terminal and the runway, where planes turn around for their next flight, and timing is everything.

“We also have others more on the ramp side,” says Draeger, referring to a system the airport now uses to track ground operations in real time. Cameras watch every stage of the turnaround, feeding data to an AI that predicts how long the process will take and where it might go wrong. “They can predict turnaround durations and steer additional resources if required,” he explains. “If a baggage belt is missing upon arrival, they can autonomously act on that and resolve bottlenecks.”

This is the kind of work that truly shapes the airport customer experience. When flights leave as scheduled, lines move faster, and connections fall into place without drama. Most travelers never think about the coordination behind it all. Yet every new piece of technology adds a layer that must fit perfectly with the rest.

But every new layer of technology brings its own challenge. “We always want to have this seamless experience for our customers,” Draeger says. “As we introduce more technology, we’ll have the challenge of combining it with legacy systems.”

Airports, after all, are built to last, and that means old baggage systems, decades-old software, and miles of wiring that can’t just be swapped overnight. “Traffic is increasing significantly, and we have limited infrastructure,” he adds. “We need simpler processes and better technology to absorb growth.”

Behind the polished front end of any airport automation project lies a balancing act: new tools talking to old systems, innovation working around concrete and cables.

The Future for Personalization In Travel: Digital Handholding

When asked what he thinks the future of travel looks like, Christian Draeger doesn’t mention drones or driverless terminals. He talks about something far simpler: help that is steady, thoughtful, and personal. “We always like to call it digital handholding,” he says. “A digital entity that’s completely informed, taking the customer by the hand and guiding them through the journey.”

Many agree that this is exactly where AI in the travel industry is heading. Gartner predicts that more than 80% of all customer interactions will be AI-assisted by 2029. The difference now is how personal that assistance can become.

“In the future, we see customers having their own personalized digital agents,” Draeger says, “on mobile, VR glasses, or other interfaces.” Those agents will be able to do a lot. “They’ll be able to rebook flights, change hotels, handle issues,” he explains. “We’ll need to provide them with the knowledge base and interconnectivity so they can act.”

He describes a world where these personal assistants talk to each other. “We’ll see a marketplace developing for agent-to-agent interaction,” he says, a network where your digital travel companion can speak directly to an airline, a hotel, or even the airport itself to smooth out the details before you notice them.

Some of that is already visible in small ways. Berlin is already imagining using augmented reality to help people find their way through the terminal. “If you come to Berlin Airport, sometimes you’ll find too many information boards,” Draeger admits. “Imagine augmented reality guiding you through the airport.”

It’s easy to see where this leads: toward an airport customer experience that blends technology with intuition. The idea isn’t to overwhelm passengers with data, but to take away the stress of travel entirely.

Personalization in Travel and Airports as Experience Ecosystems

Christian Draeger talks about air travel the way some people talk about music, not as noise and movement, but as rhythm. Airports, he says, are meant to keep that rhythm steady. When they do, everything else feels effortless.

“It’s all about making travel easier,” he says. “Like when you take a train, you just arrive and go, that’s the overarching ambition.”

Mostly, Berlin Brandenburg Airport is just pushing for a calmer travel experience. From the moment a traveler checks in to the moment they leave the gate, the goal is to take away the small frictions that make airports stressful. Berry, the AI voice agent, is part of that. So are the self-service kiosks, the CT-scan security lanes, and the quiet bits of software that keep aircraft turning on time.

“It’s not about one technology: Gen AI, robotics, biometrics, or AR,” Draeger says. “It’s about combining them to make travel much simpler.”

That line sums up Berlin’s whole approach to personalization in travel. It isn’t about showing off what technology can do; it’s about how little the traveler has to notice it.

That’s the real future of airport customer experience: an ecosystem that looks complicated underneath but feels beautifully ordinary on the surface, the kind of simplicity only achieved when someone’s been obsessing over every detail on your behalf.

Retailers are moving quickly to integrate these intelligent agents into their e-commerce platforms, aiming to deliver faster recommendations, more personalized deals, and seamless checkout experiences just in time for the busiest shopping season of the year.

Shoppers are also warming up to the idea of AI-powered assistance. Early adopters plan to consult AI to search for gift ideas, specifically citing ChatGPT as a tool, according to survey data from Bread Financial.

Those users are likely to continue their holiday shopping journeys online, through marketplaces like Amazon, social media platforms, or retailer apps.

“For the 2025 holiday season, AI-assisted search is positioned to be the first step in a shopping journey that begins and ends online,” Bread Financial notes, adding that data-savvy retailers optimizing for tools like ChatGPT could gain a competitive edge.

AI agents can shift the shopping journey from reactive to proactive, anticipating customers’ needs by learning from their behavior and predicting intent.

Unlike traditional chatbots, which answer questions in a transactional way, AI agents can reason, make decisions, and act on a shopper’s behalf. They bring together data from large language models (LLMs), real-time data, user preferences, and contextual insights, learning and improving with each customer interaction.

“We’re at the very start of the Agentic Web — where AI assistants don’t just find information on the web for us, they navigate it with us — and it will dramatically alter how we do things every day,” including shopping, said Dave Anderson, VP of Product Marketing at Contentsquare, adding that AI is already transforming online shopping behaviors:

“Intelligent AI agents are starting to compare prices, automatically apply coupons, and even complete purchases on their own. Customers are learning how to ‘set it and forget it,’ and letting agents do all the work for them.”

Retailers Turn to AI Agents to Power Smarter Shopping

Retailers are taking note, with Walmart emerging as a high-profile example.

The U.S. retail giant is leaning fully into “agentic commerce” this holiday season, rolling out five new AI-powered tools to help in-store and online shoppers find gifts, organize celebrations, or spruce up their homes to welcome guests.

The In-Store Savings feature in Walmart’s app lets customers find the best Black Friday, Rollback, and clearance deals as they navigate the aisles, with options to filter items, compare prices, and locate products in-store. Saved wish lists can be sorted by aisle for faster shopping.

AI-generated audio summaries for more than 1,000 premium beauty products make gift-buying easier on the go, while Sparky, Walmart’s GenAI-powered assistant, can now curate party supplies and recipe ingredients in real time.

For a more immersive experience, the retailer is also inviting customers into its augmented reality 3D showrooms using its Retina platform, where users can explore holiday-themed spaces and add products to their carts directly from interactive scenes.

Walmart hopes these features will encourage shoppers to engage with its app for their holiday purchases, as “when they use the app while they shop in stores, they spend 25 percent more on average than on trips when they don’t use the app,” Tracy Poulliot, SVP of Shopping Experiences at Walmart U.S., said in the announcement.

Behind the scenes, Walmart is deploying AI to enhance efficiency and freshness. Its Agentic AI for Freshness helps teams predict demand, reduce waste, and keep shelves stocked, while a multi-agent delivery system optimizes driver routes and delivery timing.

Other upgrades include a GenAI customer support assistant, dynamic real-time delivery windows, and digital twins that pre-empt equipment failures.

Walmart has embraced various forms of AI-first shopping, recently partnering with OpenAI to let customers complete purchases directly within ChatGPT using Instant Checkout.

Doug McMillon, Walmart’s President and CEO, framed the shift:

“For many years now, e-commerce shopping experiences have consisted of a search bar and a long list of item responses. That is about to change. There is a native AI experience coming that is multimedia, personalized, and contextual.”

Other retailers are also gearing up to deliver agentic e-commerce for the holiday season.

At the recent Salesforce Dreamforce event, homewares retailer Williams Sonoma announced its use of Agentforce 360 and Data 360 to bring AI agents into its online shopping experiences.

Alongside a customer service agent that delivers personalized responses, the retailer is developing a “sous chef” agent on Agentforce called Olive to help customers plan menus and discover products on its website ahead of the holiday season.

Olive will draw on data such as past purchases to infer intent and create customized Thanksgiving plans, complete with menus, shopping lists, and recommendations for Williams Sonoma cookware, ingredients, and table décor.

Similarly, Denmark-based jewelry retailer Pandora is gearing up for the holiday season with the debut of its shopper-facing AI agent Gemma, built on Salesforce’s Agentforce Commerce platform.

Unveiled during Dreamforce, Gemma was created to bring personalized service to the company’s digital channels. The jeweler typically increases its staff during peak holiday demand, but capacity can be stretched even with the additional support.

Traditional chatbots handled basic “Where’s my order?” questions, but Gemma aims to replicate the brand’s in-store service online, drawing on order history, product details, and research insights to guide gift selection.

A companion agent, Clara, handles post-purchase requests and FAQs, freeing up human staff to focus on higher-value customer interactions.

AI Traffic to Retail Sites Surges

Data underscores the growing impact of AI on retail. In its online shopping forecast for the holiday season covering the November 1 – December 31 period, Adobe predicts a 520 percent year-on-year rise in AI traffic to U.S. retail sites, following the first material surge of 1,300 percent seen last year.

Its survey of 5,000 consumers found that one-third have used AI for online shopping, and of those around 30 percent have used it for gift inspiration, while 36 percent were looking for deals, and 40 percent sought product recommendations.

Retailers of all kinds are increasing their use of AI beyond basic chatbots, data from Talkdesk’s third annual AI Holiday Shopping Report shows.

Among retailers that have already adopted AI, 85 percent are now using it for predictive analytics, up 24 percentage points from last year, and 83 percent have deployed virtual agents into their shopping experience, also up 24 points.

They are slightly more cautious about AI agents in customer service, reflected by an increase of 20 points to 79 percent.

Nearly two-thirds are leveraging AI to deliver personalized pricing and promotions to customers. Confidence in the technology is rising just as quickly, as 80 percent of retailers believe AI will help boost holiday sales and sharpen their competitive edge, and 79 percent expect it to strengthen customer loyalty, according to the survey.

Talkdesk’s data shows that retailers already using AI are widening their competitive gap with laggards.

“While retailers can’t stop that shift, they can study and leverage it,” ContentSquare’s Anderson said.

“It’s crucial to step into this next era of digital commerce by getting back to important basics: building analytics that capture how customers are using AI, like agent-powered traffic, search patterns, and conversion metrics.”

Still, transparency remains a sticking point, as Talkdesk’s survey shows 84 percent of consumers want to know when AI is involved, and most expect stronger oversight. While many are open to sharing preferences or basic personal details in exchange for more tailored experiences, few are comfortable disclosing sensitive data.

To earn that trust, retailers will need to balance personalization with privacy, offering meaningful value in exchange for data, such as discounts or loyalty points, and clearer communication about when AI is at work.

“Revenue and customer loyalty are going to be driven by how well brands prepare for a future where human and AI shoppers share the same carts,” Anderson said. “It’s not just about optimizing for Google anymore — it’s about optimizing every system that defines the future of digital experiences.”

As AI agents become part of the holiday shopping journey, retailers that deliver seamless, personalized features will set the bar for how consumers spend in 2026 and beyond.

“AI-assisted search is almost certain to grow in holidays to come,” Bread Financial noted, a trend that suggests agentic commerce may soon become a standard expectation rather than a novelty.

The nights are drawing in, the temperature is dropping, and CX analysts from across the globe are dusting off their crystal balls.

While you can expect an onslaught of predictions over the coming months, very few will have the prestige of Forrester, a leading global research and advisory firm with expertise in the CX space.

In a blog post discussing the current and future state of customer experience, Maxie Schmidt, VP and Principal Analyst at Forrester, described 2025 as “another tough year for CX teams.”

She believes that “many CX teams are drifting dangerously close to the event horizon of metric obsession” and are “circling the black hole of measurement without meaning.”

While Schmidt’s remarks sound troubling at best, and downright alarming at worst, she also offers reasons to be optimistic, stating that “2026 marks a critical inflection point.

“Some [organizations] will break free — modernizing, upskilling, and repositioning CX as a catalyst for business value. Others will cling to legacy practices and risk being pulled beyond the point of no return, where CX loses relevance and credibility.”

The predictions not only outline the challenges and roadblocks that CX teams might face in 2026, but they also offer guidance and advice on how to combat them.

Below are Forrester’s top five customer experience predictions for 2026.

Forrester’s 2026 Customer Experience Predictions

1. Metric Obsession Pushes CX Teams Toward a “Death Spiral”

Forrester warns that flat budgets and mounting pressure to prove value will tempt around 15% of CX teams into what it calls a “death spiral.”

These teams will double down on collecting and reporting survey data in an effort to justify their existence, but without real insight or business impact, their dashboards will amount to little more than noise.

The antidote? Shift from measurement to meaning.

Forrester believes the savviest teams will invest in advanced analytics and AI fluency to move from reactive scorekeeping to proactive problem-solving, embedding CX data directly into the AI models that power customer interactions.

2. AI-Led Research Will Spark Major Scandals

As more organizations hand over customer research to AI, Forrester predicts at least two major scandals will hit the headlines in 2026.

The rush to automate insight generation through synthetic audiences and AI-moderated interviews will leave some firms exposed when the tech’s limitations become painfully clear.

Forrester’s message is fairly simple: don’t sideline human expertise.

The research firm advises combining AI-driven insight with proven qualitative methods such as interviews and user testing to ensure that findings remain reliable, ethical, and grounded in reality.

3. Poorly Deployed GenAI Will Undermine Self-Service

Three in ten firms will damage their “Total Experience” growth in 2026 thanks to poorly implemented AI self-service.

Overconfidence in GenAI’s capabilities, paired with cost-cutting pressure, will see chatbots and virtual agents launched before they’re ready, leading to customer frustration and brand erosion.

CX teams must work hand-in-hand with service leaders to define where AI belongs, ensure transparency when it’s used, and closely monitor automated systems that influence customer outcomes behind the scenes.

4. Journey Mapping Faces a Crisis of Credibility

Once a cornerstone of CX strategy, journey mapping is rapidly losing its shine.

Forrester expects two-thirds of CX teams to abandon the practice altogether after years of producing maps that fail to drive meaningful change.

Too often, journey mapping has become a static exercise disconnected from real business impact.

To turn it around, CX leaders must evolve from mapping to managing journeys. Forrester advocates for prioritizing the moments that matter most, linking insights to operational improvements, and securing budgets for both quick fixes and breakthrough innovations.

5. Design Systems Will Become CX’s Secret Weapon

Finally, Forrester sees 2026 as the year design systems go mainstream.

With new accessibility regulations on the horizon and AI now influencing everything from interfaces to workflows, organizations will increasingly rely on design systems to keep experiences consistent, compliant, and on-brand.

Indeed, the research firm expects 80% of companies to invest heavily in this area, treating their design systems as products in their own right – complete with dedicated budgets, cross-functional ownership, and measurable business outcomes.

Those companies that get it right will build a strong foundation for safe, scalable, and customer-centric innovation.

The CX Inflection Point

Forrester’s 2026 customer experience predictions might not be the rosiest, but they are certainly clear on one point: the CX profession is at a crossroads.

As Schmidt explained, some teams will evolve – embracing AI responsibly, connecting insight to impact, and redefining their role as engines of business value; while others will cling to old habits, chasing metrics and managing maps as the world moves on without them.

Those who choose the former path will be well positioned not just to survive the turbulent times ahead, but to thrive.

These teams and departments will have the capacity to lead their organizations into a new era in which CX is a discipline woven into every decision that shapes the overall business.

As someone who has felt the pain of clunky handoffs and fuzzy diagnostics, I care about tools that make customer journeys clearer and kinder. Maestro is Operata’s most ambitious step yet. It expands CX Observability from a primarily Amazon Connect footprint to 50+ CCaaS, Voice AI, AI customer service, CPaaS, and CRM platforms. It introduces a unified Customer Journey Trace, a smarter CX Copilot that uses AWS Bedrock and OpenAI GPT-5.0 for natural language analysis, and an open approach for developers that includes an Insights Library and the first MCP server for CX Observability.

John Mitchem, Co-Founder & CEO at Operata: “We launched Operata to solve observability in voice and contact centres. You can’t fix what you can’t see, especially now that AI agents and human agents share the same customer journey.”

Why This Matters: Observability Is the New Control Plane for AI-Era CX

Modern contact centres are multi-platform and AI-augmented. Voice bots hand over to humans. Carriers, IVRs, CCaaS, CRMs, and LLMs all sit in the flow. Without end-to-end visibility, leaders are left guessing where quality drops, latency spikes, or handoff failures occur. Customers feel it first, NPS follows.

Mitchem again: “Start with your observability platform. Put the tools in place to judge whether new services reduce friction or create it. This has been true in IT for years, and it should be no different for your customers.”

The Maestro Release: Three Pillars

1) The Global Platform for CX Observability

Maestro supports 50+ platforms across CCaaS, AI Customer Service, Voice AI, CPaaS, and CRM, including Amazon Connect, Genesys Cloud, NICE CXone, Zoom, Talkdesk, 8×8, Twilio, PolyAI, LiveKit, Pipecat, Salesforce, ServiceNow, and Zendesk.

A new “Verified” designation flags ready-to-use data collection and integrations, with a one to three day path to verify additional supported platforms.

Why it matters: Most enterprises are hybrid and multi-vendor. Maestro gives IT and Operations one consistent view across providers, today and tomorrow.

2) One Picture Across CX Services

Customer Journey Trace presents a single, visual flame-graph timeline for every interaction, spanning telephony, IVR, CCaaS, AI agents, and human agents. Teams get span-level metrics, logs, and context in one place.

The new CX Copilot lets users ask natural-language questions, see visual results, save prompts, and trigger next-best actions, grounded in their own Operata data.

“Leaders need the whole story, not just the symptoms. Journey Trace exposes transfer delays, AI-to-human mis-handoffs, and downstream latency, the places where customer trust quietly erodes.” — John Mitchem

Ask questions like, “Where are transfers breaking,” or “Which ISPs will impact voice next week,” and get answers rooted in operational truth.

3) Open Standards for Developers, AI, and Data Teams

Maestro aligns open data collection and pipelines to industry standards for interoperability and scale.

• Insights Library: 50+ critical, real-time CX insights, from atomic signals like low MOS or high latency to composite outcomes like abandonment, rolled into CX Risk ratings.
• Operata MCP Server: the first Model Context Protocol server for CX Observability. It lets LLMs and agentic AI query Operata insights and dashboards directly, securely, and with the right context.

Why it matters: As Voice AI and agentic workflows scale, context is everything. Structured, queryable CX context helps AI return relevant answers and actions, not guesswork.

Built for IT & Ops, and Now for Data, AI, and CX Leaders

Observability has lived in IT. Maestro broadens the impact. Operations can spot issues before they hit NPS. CX leaders can see real experience impact across journeys. Developers and Data or AI teams can integrate Operata’s signals into their own systems and copilots.

“There is no one-size-fits-all AI. Diversity of models matters, but the context you feed them matters more. Operata provides journey context across platforms so your AI can answer the two questions every leader asks: what went wrong, and how do we fix it?” — John Mitchem

AWS Roots, Broader Reach

Operata’s growth has been propelled by deep work with Amazon Web Services and the Amazon Connect ecosystem. Maestro keeps that strength and extends it across ecosystems such as Genesys, NICE, Zoom, Talkdesk, Twilio, and more.

“We became popular with vendors because we help their customers succeed. It is not only finding what is wrong, it is proving what is working, and enabling rollouts with confidence.” — John Mitchem

Availability

• Insights Library: Generally Available from 22 October 2025
• All other Maestro features: Preview for existing and new customers
• Preview access: Registration required
• Amazon Connect customers: upgrade to Operata AWS Collector for Preview

The CX Today Take

This feels like a category moment. Monitoring was a safety net. Observability is now the operating system for CX, especially as AI agents join human agents in live flows. With Maestro, Operata is staking a claim as a neutral layer of truth across a fragmented stack. If you are evaluating CCaaS, Voice AI, or Customer Service AI, instrument first. The winners will see across domains in real time, correlate what matters, and act before customers feel the pain.

The Bottom Line

In a world where AI and humans share the same journey, visibility is power. The future belongs to teams that see clearly, act quickly, and learn continuously. Are you one of them?

Join the Conversation

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Press Ganey Forsta, often referred to as “PG Forsta”, is a rising force in the voice of the customer (VoC) space, rivaling Qualtrics.

Indeed, it recently placed as a Leader in the market’s latest Gartner Magic Quadrant for VoC.

In doing so, PG Forsta ranked alongside InMoment, which it later rolled up in May.

As such, this latest acquisition brings together three of the VoC space’s biggest brands.

Yet, Qualtrics is one of the market’s two most prominent names, with Medallia the other.

The acquisition will extend its market leadership and help consolidate the space.

Nevertheless, it will also boost Qualtrics’ industry-specific offerings, with PG Forsta widely deployed in the healthcare space and other highly-regulated sectors.

Across these industries, it offers advanced journey visualizations and templates, simplifying feature adoption.

PG Forsta is also well-known for its strong support services and differentiated AI solutions for front-line, customer-facing employees.

As such, it can offer many more bows to Qualtrics’ quiver, with the deal marking the VoC giant’s largest investment since it was taken private by Silver Lake in 2023.

“Bringing Qualtrics and Press Ganey Forsta together will accelerate the adoption of AI and create the most comprehensive platform for improving the human experience,” said Zig Serafin, CEO of Qualtrics.

Combining Qualtrics’ AI platform with Press Ganey Forsta’s trusted analytics and deep expertise creates an opportunity to deliver exceptional value and measurable outcomes for our customers.

The combined companies are expected to generate nearly $3BN in annual revenue. The cash and stock transaction is expected to close in the coming months, and the two companies will continue to operate independently in the meantime.

But beyond size, Patrick T. Ryan, Chairman and CEO of Press Ganey Forsta, stressed that the real differentiator is the ability to turn massive data into smarter, faster decisions powered by AI.

“AI is rapidly transforming every industry, and organizations need proven, innovative solutions grounded in deep expertise to move from insight to impact faster,” he said. This investment ignites our ability to deliver.”

Qualtrics has already been making strides in AI with tools like Conversational Feedback, Qualtrics Assist, synthetic research platform Edge Audiences, and Experience Agents. According to the company, more than one-third of customers have adopted these AI features, and 90 percent of their top 50 enterprise clients are already using them.

Now, with Press Ganey Forsta’s benchmarking data and advisory services in the mix, Qualtrics aims to help clients move from insights to impact faster.

As Bill Staikos, Founder and Managing Partner of Be Customer Led, put it in a LinkedIn post:

In the quickly consolidating CXM space, this is the loudest signal yet that ‘experience’ is more and more about data fidelity and industry depth. PG’s healthcare footprint is enormous, and the combined company also recently picked up InMoment. So this is data scale + vertical credibility + AI (and AI training) in one package.

That massive healthcare footprint sees Press Ganey Forsta work with 41,000 providers across 30 countries. As it does so, Press Ganey Forsta’s Human Experience (HX) Platform brings together customer experience, employee experience, patient experience, and market research. Yet, its influence is expanding.

Jim Davies, Co-Founder and Executive Partner at Actionary, summarized the move by telling CX Today:

The PG Forsta acquisition strengthens Qualtrics’ healthcare and VoC capabilities, expanding its portfolio and reinforcing its market leadership in experience management. The next frontier will be proactively embedding insights directly into operational workflows to shape customer experiences in real time.

What Does the Deal Mean for Qualtrics’ Rivals?

“The combo locks up healthcare for Qualtrics, as they’ll now have a massive inventory of longitudinal patient and clinician signals, wrapped in compliance workflows and integrations, that most horizontal platforms simply don’t have,” according to Staikos.

For Medallia, it brings both real pressure and hidden opportunity. The pressure is clear, as the narrative is shifting hard toward platforms that offer high-signal, trusted, industry-specific data and the ability to drive meaningful action within existing systems. But the opportunity lies in leaning into its strengths: blue-chip clients, strong service delivery, and a foothold in industries like financial services, travel, and telco, Staikos wrote.

Yet, what about other market competitors Sprinklr and Verint?

“[T]his is a green light [for Sprinklr] to lean into their “unified front-office execution,” continued Staikos. “They already own care, social, and marketing workflows; the move now is to prove closed-loop activation with measurable cost-to-serve and revenue lift using the signals they already collect.”

For Verint, which will merge with its rival Calabrio after its recent acquisition by Thoma Bravo, “the path is ‘interaction + intent + outcome’. They can bind VoC to interaction analytics and WEM so leaders can remove failure demand, versus just putting it on a dashboard.

“In the end, if you’re not going to be the data-plus-vertical incumbent, you have to be the activation engine that lives natively in CRM, CCaaS, EHR, POS, and ERP. Vertical depth, packaged outcomes, first-party data leverage, and ruthless proof of value in quarters, not years, is the winning message.

The VoC market has been heating up with consolidations and AI innovation. All eyes will be on how quickly the combined company can integrate its capabilities and deliver on its promise to turn better data into better human experiences at scale.

The benefits for businesses are clear. AI chatbots and agents are always on, never tired, and cost a fraction of a human support team, promising speed, scale, and efficiency. But many consumers simply don’t want to talk to robots, and, worryingly for brands, this is threatening customer loyalty as well as sales, Qualtrics found in its Customer Experience Trends 2026 report.

The survey found that 95% of UK consumers would prefer not to deal with chatbots at all.

The reason is rooted in trust. Consumers remain skeptical about interacting with AI across their customer experience, with around 80% responding that they haven’t dealt with AI-based customer service help or support recently.

While some AI chatbots have improved considerably, there’s still a widespread perception that AI can’t match the nuance or empathy of a human conversation.

Around 33% of UK customers don’t trust the information provided by AI, while just 35% globally say AI customer support actually solves their problem, Qualtrics found.

AI service tools have yet to close the gap between brands’ expectations that they will help improve customer interactions and consumers’ concerns that they won’t.

More than half of UK consumers worry they won’t be able to reach a human to resolve their issues when companies automate their interactions with AI.

After all, around 46% of UK customers cite convenience as the main reason they choose a particular brand over another. So the idea that AI won’t deliver a smooth experience is enough to push consumers away from brands that rely on it too heavily.

What’s more, communication breakdowns are still one of the biggest reasons customers walk away unhappy, causing 42% of all bad experiences in the UK.

But businesses may not get the insights they need to understand churn and improve the experience for the customer. Around 31% of UK consumers do not communicate with a company directly after they have a poor experience. But with 44% of bad experiences leading customers to reduce their spending with the company, brands are losing loyalty — and revenue — without being able to understand why.

As Isabelle Zdatny, Head of Thought Leadership at Qualtrics XM Institute, told CX Today:

Silence from consumers is one of the biggest challenges for UK brands right now as they try to manage shifting customer expectations and needs.

“Increasingly, customers don’t tell companies about bad experiences – they just act, with roughly half reducing their spending. Companies can be left guessing where they went wrong,” Zdatny said. “Brands need to recognize that every missed signal, whether it’s a dropped call, an abandoned shopping cart, or a negative social post, identifies an area for improvement.”

Companies need to stay tuned in to the warning signs. When customers start showing frustration, it signals that something is off in the experience, and brands need to move to fix it fast.

The solution isn’t necessarily to ditch chatbots entirely, but to deploy them thoughtfully. Brands need to focus on seamless handoffs from AI to humans, making it clear from the start that help is available in whatever form the customer needs.

“Addressing these issues as they appear helps build consumer trust, which is the currency of customer experience. AI can help connect those dots, but only if companies are listening with the intent to act,” Zdatny said.

The Loyalty Fallout

Customer loyalty doesn’t just hinge on solving problems. It’s also about feeling heard and valued. When a consumer reaches out to a brand with a concern or question and they’re met with a chatbot that dodges the issue or fails to escalate properly, that loyalty takes a hit.

And in the wake of several high-profile data security breaches this year in the UK, the trust stakes are especially high.

While 63% of UK consumers prefer to buy from brands that provide personalized experiences, 36% are uncomfortable with their information being used for personalization, Qualtrics’ survey found, and only 40% trust companies to use their data responsibly.

That aligns with the findings of PwC’s 2025 Customer Experience Survey, which indicated that while executives tend to assume customers are willing to share their data for personalized services, consumers are reluctant to share detailed personal data for an improved experience.

Just 39% of the respondents to Qualtrics’ survey believe the benefits they receive from sharing data with brands are worth the privacy trade-off.

UK consumers are some of the most concerned in the world when it comes to hackers potentially stealing their information, with 28% citing data breaches as their biggest fear when companies collect their personal information, compared with 23% of global consumers.

The recent cyber attacks on UK retailers have sharpened those fears and left many questioning whether sharing data is worth the risk, Qualtrics noted.

“As brands scale AI solutions across the customer experience, they must do this with authenticity and transparency. People want reassurance that the tools designed to make their lives easier won’t erode their privacy or block access to real support,”  Zdatny said.

When companies deploy AI that actually resolves issues — not just deflects them — while protecting customer data and maintaining clear paths to human support, that’s when trust starts to grow. Anything less feels like a cost-cutting exercise.

The research points to a way forward, as around 44% of UK consumers say they would be prepared to share more of their data if companies were transparent about what they collect. And 47% want greater control over how their information is used.

As AI becomes more embedded in customer experiences, brands need to achieve a fine balance. If they rely too heavily on AI, they risk alienating their customer base. But if they ignore its potential, they could fall behind on efficiency and innovation. At the same time, given consumer concerns about the way their data is being used, strong privacy practices are as important as the technology itself.

If brands can find that sweet spot bringing together smart automation, human availability, and clear communication, they might just keep cynicism at bay and loyalty intact.

In this exclusive CX Today interview, we sit down with Sanas to explore the cutting-edge world of AI-powered accent translation.

From improving customer experience to tackling ethical concerns, we dive deep into the implications of reshaping the way we communicate.

Join us as we discuss:

• How AI accent translation enhances global communication
• The ethical debate around voice modification and identity
• Real-world applications for CX and business operations
• What does AI-driven accent translation mean for the future of customer experience?

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