They’re also a must-have in an era where first-party data has become crucial. In retail and eCommerce, CDPs now decide whether personalization feels seamless or invasive. For healthcare teams, they determine if data moves fast enough between portals, contact centres, and clinics to help patients instead of slowing them down. In finance, they’re becoming a line of defence -unifying records, flagging anomalies, and proving compliance to regulators.

What Is a CDP and Why It’s Not Just a CRM Upgrade

For years, the CRM has been treated as the central hub for customer data. But its design is narrow. It logs contacts, tracks deals, and manages service cases.

What it doesn’t do is unify every fragment of data a company holds – website visits, app behaviour, consent records, transactions, service interactions, marketing touches – into one, live profile that can be activated anywhere. That is the role of the Customer Data Platform.

A Customer Data Platform pulls first-party data from every corner – websites, apps, call logs, sales systems – and brings it into one place. The mess gets cleaned, duplicates are resolved, and what’s left is a living record of the customer that keeps updating. From there, it can do a lot: fuel AI models, trigger automated steps in the background, or simply give a frontline agent the context they usually waste time piecing together.

As Salesforce describes it, the platform moves data “from disconnected silos to real-time engagement.” Adobe takes it further, positioning CDPs as the only way to deliver “personalization at scale, powered by first-party data.”

For many CX teams, CDPs are now the foundation of any strategy for future growth. That’s part of why the market is growing so fast, at a rate of around 39.9% CAGR.

Measurable Customer Data Platform Benefits and ROI

Technology investments rise and fall on one question: do they pay back? In the case of Customer Data Platforms, the answer is increasingly clear. CDP benefits are measurable, and enterprises are using the data to justify spending at the board level.

The financial case is strong. A Forrester Total Economic Impact study of Oracle Unity found that companies achieved an ROI of 158% with payback in just seven months. The study pointed to efficiency gains in segmentation, campaign orchestration, and service response times.

The pattern repeats across industries.

• Telecoms: Spark NZ, working with Tealium and Snowflake, cut campaign delivery time by 80%. That speed translated into millions saved in media spend and higher response rates.
• Membership services: At AAA Washington, Salesforce Data Cloud unified data across channels to power faster, more relevant roadside support. The result was a jump in satisfaction scores and measurable cost savings as manual lookups disappeared.
• Retail: Klaviyo’s customers often cite faster payback than expected. At DKNY, Klaviyo helped to increase click rates and improve conversions by enabling end-to-end personalization.

But the benefits of a CDP often go further than expected, particularly in the age of AI and automation.

Customer Data Platforms as the Foundation for AI, Automation and Orchestration

Artificial intelligence and automation are boardroom priorities, but both depend on the quality of the data underneath. Without a trusted foundation, even the smartest models deliver the wrong outcomes. That is why CDP benefits now reach beyond marketing: they are powering AI decisioning and workflow orchestration across the enterprise.

Salesforce describes its Data Cloud as a “zero-copy CDP,” able to unify data across systems and activate it in real time. In practice, that means generative AI assistants like Einstein or Agentforce can draft responses, recommend actions, and even guide self-service troubleshooting – because the context is accurate. Adobe has taken a similar line, stressing that a CDP is the only way to make personalisation “real-time and scalable.”

Case studies bring this to life. Vodafone used Tealium to launch what it called an “AI-powered customer revolution”. By unifying subscriber data, the telecom giant improved cross-channel engagement by 30% and created new opportunities for automated retention campaigns.

Castore, a fast-growing sportswear brand, turned to Klaviyo’s CDP to scale its customer journeys and marketing campaigns, branching into four new SMS territories, and increasing click-through rates for AI-powered, automated campaigns.

Trying to automate on top of scattered data just makes the noise louder. With a CDP in place, orchestration feels sharper: actions run faster, responses land with more relevance, and journeys stay consistent. The same profile sits underneath everything – whether it’s an AI copilot, a bot handling routine work, or a self-service flow guiding a customer through a fix.

Customer Data Platform Benefits for Compliance, Security and Trust

Data is now under the same scrutiny as financial records once were. A misstep doesn’t just create headlines; it creates fines that hurt. Since GDPR came into force, regulators have handed out more than €5.6 billion in penalties, and the pace has only picked up in the last two years. For banks, insurers, and healthcare providers, fragmented data is a liability.

This is where a Customer Data Platform earns its keep, allowing enterprises to build compliance into the data layer itself. Every profile carries its own consent state. Every interaction can be logged against that consent. Sensitive fields can be masked automatically before they ever reach a campaign or a dashboard. The result: marketers can move quickly, while legal and risk teams know the audit trail is intact.

There are practical examples. Legal & General uses its CDP to improve real-time engagement, but compliance was part of the business case from the start. Data policies are enforced centrally, so every department works from the same set of rules.

A CDP doesn’t guarantee compliance on its own, but it gives organisations the framework they need to protect customers, and themselves.

Improved CX: Personalization and Omnichannel

Most people don’t notice a database. What they do notice is the experience: the email that lands with the wrong name, the app that asks them to log in again, the service agent who doesn’t know what happened last week. A Customer Data Platform exists to stop those seams from showing. That’s where some of the clearest CDP benefits come through.

The promise is simple enough: take signals from across the business, stitch them into a live profile, and feed them back into every channel. In practice, it means fewer repeated questions, less wasted spend, and more relevant offers. Analysts at Aberdeen have noted that organisations with a CDP in place see campaign response rates more than double.

An example? L’Oréal turned to Tealium to power personalization and improve media efficiency worldwide. The CDP became the bridge between consented first-party data and campaigns running in dozens of markets, ensuring local teams could tailor messages without compromising privacy.

Fisher and Paykel used the CDP from Salesforce to improve customer experience in another way – by giving clients a more efficient self-service experience. Agentforce now handles 65% of the company’s interactions, and 45% of customers book directly through AI. The company also benefits from a 50% reduction in call handling times, that means agents have more time to focus on other tasks.

CDP Benefits for Employees and Service Teams

Customer Data Platforms are usually sold on their marketing value, but the upside for employees is just as important. When data is scattered, staff spend time chasing records, re-entering details, or trying to match information between systems. It drags down productivity and morale. Unifying that data is one of the simpler benefits of a CDP, yet it can be the most visible inside the organisation.

For agents on the service desk, a unified profile means they no longer need to piece together a caller’s history from multiple screens. Instead, they see the journey in context – recent transactions, open tickets, even preferences collected elsewhere. Handle times drop, but so does frustration on both sides of the line.

There are clear examples. AAA Washington turned to Salesforce Data Cloud to give service agents a single view of member profiles. The organization described how AI agents could act on those profiles to dispatch roadside help faster and more accurately, without the risk of burnout.

Customer Data Platform Benefits for Business Leaders: Unified Insights and ROI

For executives, the challenge is rarely a lack of reports. It’s the opposite. Every department has its own dashboards, each with different numbers, often telling different stories. Decisions slow down because no one is sure which version of the truth to trust. This is where one of the more overlooked benefits of a CDP comes in: a single, reliable view that leadership can use with confidence.

There’s a strategy angle too. Once unified profiles start feeding into AI, executives can pick up churn risks before they hit the numbers, forecast with more certainty, and shift spending based on what customers are actually doing right now. It cuts down the boardroom surprises – and avoids the frantic catch-up when forecasts and reality don’t match.

The Adecco Group is a case in point. By implementing Salesforce Data Cloud across its global workforce solutions business, the company gave executives access to a 360-degree view of both clients and candidates. Its Chief Digital & Information Officer explained that AI now powers recommendations across the business, backed by trusted data. The CDP benefits in this case weren’t limited to marketing metrics; they reshaped how Adecco planned and delivered strategy.

The Customer Data Platform Benefits Enterprises Can’t Overlook

Much of the discussion around CDP benefits centers on personalization or marketing efficiency. Important, but not the whole story. Some of the biggest advantages are the ones that don’t always make it into vendor slides.

One is data quality for AI. Models are only as strong as the information they’re trained on. A Customer Data Platform acts as a safeguard, filtering personal data where it shouldn’t be used and ensuring inputs are consistent. That makes AI outputs more reliable – and less risky when it comes to privacy or bias.

Another is collaboration. Increasingly, organizations are using data clean rooms – neutral environments where they can share insights with partners without exposing raw records. CDPs can plug directly into these environments, allowing a retailer and a brand, or a hospital and a research partner, to coordinate using anonymised datasets.

Governance often gets left until last, but a CDP brings it right into the data layer. Consent tags travel with the customer wherever their information is used. If someone withdraws permission, that state follows them, blocking future use automatically.

These Customer Data Platform benefits aren’t flashy like a dashboard or a campaign, but they carry more weight. They shape whether AI scales responsibly, whether data partnerships work, and whether trust with customers holds firm.

They’re running on static journeys, and disconnected data. Context that should guide the next move gets trapped in silos. Customers end up repeating information to different agents, something more than 70% say businesses need to fix.

Delays are expensive. They make support lines longer, drive costs up, and quietly chip away at loyalty. It’s why real-time customer journey orchestration (RTJO) is moving to the heart of customer experience work. The idea isn’t complicated: watch what’s happening right now, match it with what you already know about the person, and act before the moment slips.

What Real-Time Customer Journey Orchestration Means

“Real-time” gets thrown around often, but in customer service it has a very specific meaning. It isn’t about answering a phone a little faster. It’s about noticing a customer signal the instant it happens, matching it to a live, unified profile, and deciding what to do before the customer has to ask.

Think of a failed card payment. A traditional system might flag it overnight, adding the customer to a recovery email list. Real-time journey orchestration (RTJO) does something very different: it sees the decline, checks recent interactions, weighs account value and risk, and can trigger an SMS with a retry link or route the next contact to an agent who already knows the issue. The action happens while the customer is still engaged.

That ability rests on three pillars:

• Unified identity and context: A customer data platform or connected CRM keeps every click, call and payment tied to one profile, even if the person has shifted from anonymous browsing to an authenticated account.
• Intelligent decisioning: Rules and AI models balance relevance with compliance and cost – choosing whether to push self-service, escalate to a skilled agent, or pause other messaging.
• Omnichannel activation. Whether it’s an email, app push, proactive chat, or direct hand-off to the contact centre, the response must travel through the right channel instantly – with full context for the human who picks it up.

For service teams, the change is dramatic. They’re no longer scrambling after a problem has exploded. They can spot it as it happens, adjust, and solve it while the chance to keep a customer happy, and avoid another expensive follow-up, is still alive.

Benefits of Real-Time Customer Journey Orchestration

When service teams can read what’s happening in real time and act on it, the rewards show up fast. Real-time customer journey orchestration cuts service costs, protects revenue, and keeps customers from abandoning a brand when frustration peaks.

The clearest way to see the impact is by looking at the “moments” where speed and context matter most. Each represents a chance to either save a relationship or lose it.

Rescue moments: failed payments, abandonments, and stuck self-service

Few situations create friction faster than a transaction failure or a dead-end in self-service. Traditional systems may capture the error but act too late, often following up hours later with an email that the customer ignores. Real-time journey orchestration (RTJO) turns those critical failures into a save opportunity.

When a payment declines, the platform can instantly attempt an alternate payment rail, trigger a push or SMS with a retry link, or, if the customer calls, route them to an agent who already sees the failure and possible fixes. In self-service channels, if a chatbot loop or authentication issue stalls progress, orchestration tools can escalate to a human before the customer abandons the journey.

For instance, HSBC implemented a real-time system, and cut abandonment rates by 48%, reduced average handle time by five minutes per interaction, and lowered transfers by 32%. Supervisors also gained about two extra hours each day thanks to live insights and routing improvements.

Disruption moments: travel changes, outages, and service incidents

Unplanned events like a flight delay, a broadband outage, or a medical service surge can overwhelm service channels if handled slowly. Batch notifications or static IVR menus simply can’t keep up when thousands of customers need help at once.

Real-time journey orchestration lets organizations push clear, timely updates and adapt routing rules as conditions change. Instead of customers flooding phone lines blind, they can get personalized alerts, self-service options, or direct access to specialized support. Some companies even use insights to stop issues before they happen.

IC24, a leading U.K. healthcare provider, once reviewed barely 2 percent of patient interactions by hand. Today, it analyzes every single one through a real-time analytics platform. That shift has meant faster, safer decisions during sudden demand spikes (including the intense waves of COVID) and slimmer IVR paths that get patients to the right care without delay.

Value moments: catching opportunity while it’s live

Some moments aren’t about fixing what’s broken – they’re about recognizing a chance to add value before it slips away. A customer lingering on a premium product page, an account edging toward a usage cap, a family planning a major purchase. These signals fade fast if a brand waits until the next scheduled campaign.

With real-time journey orchestration (RTJO), service and sales teams can react while interest is still warm. Decision engines weigh browsing behavior, account history, and risk markers, then trigger an action that feels helpful rather than pushy.

For example, at Ambuja Neotia, an Indian real-estate group, instant lead scoring and agent-assist tools mean the most engaged prospects go straight to the right rep. Hot-lead conversions jumped from 40% to 80%, doubling the impact of each marketing dollar.

Effort moments: smooth handoffs when automation stalls

Self-service has its limits. Voice systems mishear names, bots loop endlessly, and authentication can fail at the worst possible moment. What drives customers away isn’t automation itself – it’s having to start over once they finally reach a human.

Real-time journey orchestration keeps that from happening. The system watches for friction, then hands the case to a live agent with everything intact: menu selections, transcripts, account context. The customer moves forward instead of back to square one. Employees get guidance, too.

For instance, brokerage Angel One tied all service channels into one platform and gave agents guided workflows in real time. The payoff: first-call resolution climbed by 18–20% and average handle time dropped 30%, even as remote work reshaped its contact centers.

Experience moments: listening live and improving fast

Great service isn’t just about reacting to obvious events. It’s also about spotting friction before it turns into a complaint. Every digital tap, survey response, or call recording is a clue if it can be processed fast enough to drive change.

Real-time journey orchestration (RTJO) gives service leaders that ability. Feedback and behavioral signals flow in as they happen; analytics engines flag patterns; orchestration tools adjust messaging, routing, or self-service flows the same day instead of weeks later.

Example: Spanish bank ABANCA uses live feedback across contact centers and digital channels to spot pain points and act quickly. The approach has fueled higher acquisition conversion and sped up process improvements.

By treating every click and comment as a potential signal and closing the loop immediately, brands move from reactive fixes to continuous improvement. Agents benefit just as much. Broken workflows get fixed quickly instead of forcing customers to call again and again.

Implementing Real-Time Customer Journey Orchestration

Acting in the moment doesn’t happen by chance. It takes planning – linking identity, live events, decisioning, and every service channel into one fast, connected loop. For customer service teams, getting this right means fewer escalations, lower handle times, and a journey that actually feels connected.

The most important thing? The right architecture. Teams need building blocks for:

• Identity and consent. A customer data platform (CDP) or connected CRM becomes the single source of truth. It keeps track of who the customer is — even as they move from anonymous browsing to an authenticated session — while respecting consent rules.
• Event fabric. Systems need a live feed of signals: failed payments, app errors, delivery updates, usage spikes. Standardizing those feeds keeps triggers reliable.
• Rules and AI models decide what should happen next. They balance urgency, relevance, and compliance – for example, suppressing a marketing email while routing a payment failure to an agent.
• Once a decision is made, the action must happen instantly: an SMS, app push, proactive chat, or a fully contextual hand-off to the contact center. Modern CCaaS platforms increasingly build this natively for instance, check out Genesys Cloud’s journey management capabilities and NICE’s orchestration innovations
• The leaders in orchestration keep a close eye on first-contact resolution, transfer rates, abandonment, containment in self-service, and how much effort customers actually spend. They add voice-of-customer sentiment to see whether journeys feel easier.

Building this doesn’t require a massive, years-long overhaul. Many teams start small: tie together identity and event data, launch a few high-impact triggers, and grow once the results prove the value

The Future for Real-Time Customer Journey Orchestration

Real-time orchestration today is mostly about reacting well when something happens. The next wave will go further: predicting and preventing friction before the customer ever feels it.

One driver is agentic AI – systems that don’t just suggest next steps but quietly reshape journeys in the background. These tools will summarize interaction history, recommend compliant responses, and update rules when patterns shift. Instead of waiting for analysts to re-map journeys, the platform itself will fine-tune flows as new behaviors emerge.

Another change is predictive service. By combining journey analytics with machine learning, platforms can spot early signs of trouble – like unusual app activity or network data that hints at a looming outage – and trigger preemptive outreach. Customers might get a helpful notification or an alternative payment option before they even know there’s a risk.

Governance will matter more, too. As orchestration engines start to make proactive decisions in regulated industries such as banking, healthcare, and utilities, companies will need transparent audit trails and clear consent management. Decisioning can’t be a black box when compliance and trust are at stake.

For customer service leaders, this shift means fewer angry calls and lower costs, but it also means new skills: journey scientists who tune models, CX strategists who weigh risk and reward, and operations teams ready to roll out changes fast. The brands that build this muscle now will be ready when orchestration moves from reacting in seconds to preventing problems altogether.

Building an Engine for the Moments That Matter

People make up their minds about a brand in fast, fragile moments – when a payment fails, a call drops, or a service hiccup ruins the day. Real-time customer journey orchestration flips those points of friction into chances to help, keep revenue on the table, and avoid another round of costly support.

The approach is straightforward: stay tuned to live events, understand who they affect, and step in right then, while the moment still matters.

Ready to upgrade journey orchestration? Explore our guide to the power of generative AI in CJO, or discover how to scale safely, with this article on secure, scalable orchestration.

The problem is simple: systems don’t talk to each other. A customer starts a conversation on live chat, calls later to follow up, and then gets an email with conflicting information. Each hand-off forces them to repeat details, re-authenticate, or explain the issue all over again. Patience runs out quickly.

The cost isn’t hidden for long. U.S. companies lose an estimated $136.8 billion every year to avoidable churn. Customers leave when systems don’t connect, data is trapped in silos, workflows run in isolation, and departments push their own priorities instead of working toward the full journey.

Fixing that takes more than patches. It needs stronger journey orchestration, along with omnichannel workflow design and dependable CDP integration. The aim is for every channel to draw from the same source of truth, so the customer isn’t forced to start over at each step.

Fragmented Journeys: The Hidden Cost and Causes

The cost of fragmented customer journeys isn’t always obvious. Customers don’t usually complain about “systems not talking to each other.” They just get tired of repeating themselves, chasing updates, or being bounced between departments. Some walk away silently. Others switch to a competitor after one poor experience. That lost loyalty is expensive.

All the while, customers that get connected experiences are helping brands grow. Studies show customers who get “excellent” experiences spend about 140% more.

The Causes of Fragmented Customer Journeys

Why are fragmented customer journeys still getting worse? A big part of the answer lies in the systems. Older ERP platforms were built for accounting and operations. They store useful data, but they weren’t designed to share it across customer touchpoints.

On top of that, many firms still run sales, service, and fulfillment on different platforms. Each team shapes processes around its own system, so when customers move between departments, the context often gets lost.

Then there are issues created by:

• Multiple versions of the same customer: Without solid CDP integration, one person might exist in several databases under different IDs. That makes personalization, and even basic service, harder.
• Channels that don’t connect: Phone, email, chat, apps, and stores often sit on different platforms. Customers expect one conversation. Businesses deliver five.
• Processes that drift: Marketing offers a refund or discount, but the policy never makes it to the billing system. Customers get conflicting answers depending on who they ask.
• Automation in silos: Generic automation often backfires. A bot that can’t see the full journey adds more friction, not less.
• Slow-moving data: By the time an update syncs between systems, the customer has already called back.
• Compliance barriers: Privacy and security rules matter, but poor design can block the very context agents need to help.

Taken together, these gaps explain why customers feel let down. The business may see good metrics in one channel, but the overall journey tells another story. Until the foundation is fixed, journey orchestration and omnichannel workflow automation tools can only go so far.

Unifying Journeys: The Journey Orchestration Tech Teams Need

When customers say they feel like they’re dealing with “five different companies at once,” it’s rarely the fault of the service team. The problem sits in the systems. Fixing fragmented customer journeys means building a stack where data flows from the back office to the front line without friction.

Cloud ERP Integration

Most ERPs were built to balance books and manage inventory. They weren’t built to answer a customer who asks, “Where’s my order?” That’s why cloud ERP integration is now so important. When ERP data is connected directly to sales and service platforms, answers come back in seconds instead of days.

Cloud ERP changes that. By connecting ERP directly with CRM and service systems, data is available in real time. Smarter Furnishings made this upgrade with Microsoft Dynamics 365 and reduced quote turnaround times by 80 percent. That kind of improvement comes from eliminating the delays caused by disconnected back-office systems

CDP Integration

Most companies hold records with multiple versions of the same customer. A single person might appear in the marketing database, the CRM, and the billing platform under slightly different records. This duplication makes personalization impossible and creates obvious gaps in service.

A customer data platform (CDP) takes scattered records and pulls them into one profile. It updates as new information comes in, so teams aren’t working from old or conflicting data. That single view makes it possible to keep the journey consistent when a customer moves from one channel to another. With CDP integration, journey orchestration tools have a reliable record to draw on instead of piecing together fragments.

Combining Customer Journey Orchestration and AI Decisioning

The orchestration layer is where data turns into action. Journey orchestration engines like the industry-first solution from NiCE take context from CDPs, CRM systems, and ERPs, and use it to determine the next best step in the customer’s journey. That may mean routing a case to the right team, sending a proactive update, or triggering an RPA process in the background.

Qualtrics research shows that effective orchestration can boost revenue by 10–20 percent while reducing service costs by 15–25 percent At FedPoint, NiCE CXone drove similar results in practice: IVR containment increased from 28.5% to 33.9%, customer satisfaction rose to 98.35%, and average answer speed fell from 35 seconds to 15 seconds.

Omnichannel CCaaS

Customers don’t think in terms of “channels.” They expect one continuous conversation, whether they start with a phone call, follow up via chat, or receive an email confirmation later. Without a unified contact platform, those experiences quickly fracture.

That’s why omnichannel workflow through contact center as a service (CCaaS) is now a priority. BankUnited’s deployment with Talkdesk shows the results: self-service adoption increased by 16%, abandonment fell to 5.3%, and NPS more than doubled.

Automation and CRM Intelligence

Even with orchestration in play, journeys can stall if the back office is still running on manual tasks. That’s where RPA comes in. It takes on work like refunds, policy checks, and updates, jobs that would otherwise create delays and frustration.

On the front line, CRM automation does the heavy lifting for agents. AI creates summaries automatically, enriches profiles with data, and shares recommendations with agents in real time. The agent spends less time searching and more time solving. That combination speeds up resolution and helps ensure the journey doesn’t break in the final mile.

How to Start Reducing Journey Fragmentation

There isn’t a quick fix for fragmented customer journeys. The organizations that succeed usually take it step by step. They get the basics right, test in a few focused areas, and only then expand.

• Begin with the data: If core systems don’t share information, the journey will eventually break. That’s why so many CIOs are prioritizing ERP and CRM integration, or even tying in CDP solutions, before layering on orchestration.
• Create a single customer profile: A CDP integration pulls records together from sales, marketing, and service. It means every interaction draws from the same source of truth. Without that, different teams are still working off different stories.
• Pilot orchestration on high-value journeys: Trying to orchestrate everything at once rarely works. Pick a few critical touchpoints, like order tracking or benefit enrollment, and build orchestration around them. A Middle Eastern bank did this with Kore.ai, and eventually achieved 40% automation rates for workflows, as well as higher CSAT scores.
• Add omnichannel contact. Customers don’t think in terms of “phone” or “chat.” They want one continuous conversation. Moving to CCaaS platforms helps deliver that. Particularly when those systems can speak to ERP, CRM, and CDP solutions.
• Automate the back office. Journeys still fail when refunds or approvals sit in manual queues. RPA can process these instantly, while CRM automation gives agents context without the need to dig. Together, they prevent small delays from becoming big frustrations.

Also, measure what matters. Efficiency metrics only go so far. Average handle time may look good on a report but say little about customer loyalty. Outcome-based measures – resolution rates, effort scores, verified completions, tell you whether fragmentation is actually being reduced.

Journey Orchestration: From Fragmentation to Flow

Plenty of firms talk about improving customer experience. The real progress comes from those willing to confront fragmentation directly. They modernize their data foundations, connect ERP and CRM, put CDP integration in place, and then add journey orchestration and omnichannel workflows. Each layer builds on the last, creating a system that actually holds together.

The rewards are measurable. Containment improves without hurting satisfaction. Resolution times drop. Customers stop repeating themselves at every turn. Plus, loyalty grows stronger, the ultimate measure of success in competitive markets where switching costs are low and alternatives are one click away.

Journey orchestration is only going to matter more as AI takes on a bigger role in customer experience. But AI that runs on inconsistent data won’t deliver. Reducing fragmentation is the first step. Once that’s done, journeys become faster, cheaper to support, and more likely to end in loyalty instead of churn.

Sean Taylor, CEO of Content Guru, was a judge and, as part of the evaluation, sat down with one of the finalists’ agents to watch how they worked.  

“They were taking a customer’s payment and had a stack of yellow Post-it notes on their desk,” said Taylor during a recent CX Today interview. “They typed the credit card details into one system, then quickly wrote them on a note.  

“When I asked why, they explained that the information also needed to go into another system, but they couldn’t do both at once.” 

Yet, imagine leaving the building with a pocket full of Post-it notes containing names, credit card numbers, expiry dates, and CVV codes… 

Needless to say, they didn’t win the competition. Nevertheless, the story illustrates just how difficult it is for many agents to switch between systems. 

For all the talk of a “single pane of glass,” a Deloitte study in the UK found that the average contact center agent still works with around 14 separate systems of record. 

Ultimately, that illustrates that there is no silver bullet. A closely considered omni-data strategy is instead the best path forward. 

What Is Omni-Data? 

Just as omnichannel communication brings together voice, email, RCS, WhatsApp, and video into one platform, omni-data brings all an organization’s data systems together. 

Whether it’s Salesforce, Microsoft Dynamics, or proprietary systems like Guidewire in insurance or Epic in healthcare, an omni-data strategy surfaces them in one place. 

Agents can push and pull information without resorting to Post-it notes or duplicate entries. 

Content Guru is leading the omni-data charge by converging its CCaaS solution with a first-party customer data platform (CDP), enabling that single data thread.    

“To me, that’s a no-brainer,” added Taylor. “Yet when we deliver it, customers often say, “Wow, that’s unique.”  

“Other vendors may have strong connectors into Salesforce or Dynamics, but they don’t address the full challenge of integrating data across systems.”  

Omni-Data and the Future of Customer Service  

Omni-data provides a single source of data for agents to push and pull from. Yet, that’s not only human agents; AI agents can also do so.  

Indeed, contact centers may orchestrate experiences where AI agents interact with customers while leveraging data from one a single layer, instead of pulling from a myriad of integrations, which require continuous, rigorous security checks. 

Yet, they won’t just drink from the hosepipe; they feed back into it. 

As such, contact centers can advance their conversation automation strategies, thinking not only about inbound but also outbound.  

After all, the future of customer service isn’t only reactive, it’s proactive, and even pre-emptive.  

With an omni-data strategy, contact centers can detect signals from various systems that indicate the customer is experiencing (or is about to experience) an issue. From there, an AI agent will trigger a corresponding resolution flow and communicate that with the affected customer.  

Here are four cross-industry examples of what that proactive flow may look like in practice. 

1. Proactive Servicing & Repairs (Automotive & Retail)

IoT devices can send signals into the omni-data layer from sensors hidden within products. That includes everything from transport to white goods. 

The devices help monitor product health, so if a car has low tire pressure or a washing machine is about to give up, they can trigger a flow that ends with an AI agent scheduling a repair with the affected customer. 

2. Proactive Pipe Management (Water) 

Don’t think of only first-party data sources as triggers for a proactive flow. Public sources can also feed into the omni-data layer.  

For instance, data from the weather forecast could filter into a water company’s omni-data layer. With that data, an AI agent can predict whether a water supply pipe will freeze and when it may unfreeze, rather than just telling the customer to schedule an engineer.

3. Proactive Network Updates (Telco)

Telcos can feed data from their Network Monitoring System (NMS) into the omni-data layer, with AI agents on alerts for an outage.  

When this occurs, they can proactively notify customers and send updates, keeping them in the loop, so affected customers don’t have to contact customer service. 

4. Proactive Journey Recoveries (Travel)

Plane and train delays often cause passengers to miss their connections. Yet, by plugging data from the Traffic Flow Management and CRM systems, companies can charge AI agents with rebooking customers on the next-best journey. 

As such, when the customer arrives or lands, they don’t have to queue for customer support. Instead, they receive an alert with their new booking or alternative options to consider.  

Get Ahead with Content Guru  

Content Guru entered the cloud contact center market in 2005, before “cloud software” was a term that many people had ever used.  

Its parent company, Redwood Technologies, subsidized the business for the first eight years because adoption was slow. But, Taylor and his team believed the cloud would matter. 

The same happened with AI. Content Guru invested years before the current boom, before COVID delayed adoption, but models like ChatGPT accelerated it again. 

“Our philosophy is to blend customer-driven innovation with long-term bets based on intuition and experience,” said Taylor. “Sometimes we’re early, which can be frustrating, but when the market catches up, we’re ready.” 

Its next bet is omni-data. Given its track record and status as a global CCaaS provider, who’d bet against the company this time around? 

For more on Content Guru’s contact center tech, visit:  www.contentguru.com  

AWS, Five9, and Talkdesk join them in the Leader square, with the latter bouncing back after placing as a Visionary last year.

Content Guru also rises up the pile. It has shifted from the Niche Player quadrant and is now a Challenger. Meanwhile, Cisco moves in the opposite direction.

8×8 has dropped out of the evaluation, yet Zoom enters and takes its place as a Niche Player.

Alongside 8×8, Google, Microsoft, and Sprinklr are prominent CCaaS providers that don’t feature in the Magic Quadrant matrix.

The Definition of Contact Center as a Service (CCaaS)

All cloud applications that enable customer support teams to manage multichannel conversations fall under the term “Contact Center as a Service (CCaaS)”.

The providers included in the Magic Quadrant assemble those apps, both native and third-party, on CCaaS platforms, enabling service experiences led by both humans and AI.

Yet, it’s not all about facilitating conversations. CCaaS platforms will also offer solutions for analytics and reporting, agent assistance, and workforce engagement management (WEM).

While Gartner’s definition is more comprehensive, that’s ultimately what each vendor in the report offers.

The analyst evaluates them on such capabilities, alongside pricing models, support services, integrations, verified customer feedback (stripped from Gartner Peer Insights), and more.

In doing so, the research firm splits nine of the most prominent industry players into four groups: Leaders, Challengers, Visionaries, and Niche Players. Here’s how they performed.

Gartner Magic Quadrant Leaders

Leaders sit in the top right-hand square of the Magic Quadrant, scoring above average in their “ability to execute” and “completeness of vision”. This year’s Leaders are:

• NiCE
• Genesys
• Amazon Web Services (AWS)
• Five9
• Talkdesk

NiCE

NiCE has secured several major enterprise CCaaS deals this calendar year, including two nine-figure mega-contracts.

Key to these deals are its advanced global support services, which Gartner lauds, alongside the vendor’s “technical account manager support”.

Additionally, the analyst pinpointed “advanced AI and analytical capabilities” as a strength. However, it didn’t note how NiCE’s burgeoning enterprise partnerships, with the likes of AWS, ServiceNow, and Snowflake, aid that AI strategy and set the stage for end-to-end, automated resolution flows.

Also, Gartner fails to mention NiCE’s workforce engagement management (WEM) heritage, which continues to be a significant differentiator, especially with the top two third-party alternatives – Verint and Calabrio – set to merge. However, in fairness, confirmation of this merger seemingly came through after the research firm completed its evaluation.

Genesys

Genesys excels in big enterprise deployments, especially from its own on-premise install base, offering tried-and-tested playbooks, process maps, and solutions to make migrations easier.

Gartner recognizes these strengths, alongside its “adaptability and innovation”, highlighting Genesys’s rapid delivery of new, differentiated features.

Somewhat remarkably, however, Gartner doesn’t mention Genesys’s leading role in converging CCaaS and CRM solutions, despite noting this as a key market trend.

Its recent $1.5BN investment from Salesforce and ServiceNow seemingly rubberstamps Genesys’s strategy here, with the two CRM vendors taking learnings from their collaboration with the CCaaS revenue leader and applying those industry-wide.

As that trend kicks into gear, Genesys will continue to play a leading role in converging the customer support stack.

Amazon Web Services (AWS)

Gartner notes that Amazon Connect clients often report their satisfaction with building “functionally rich AI capabilities”, leveraging the broader AWS portfolio.

As this suggests, AWS uses its size well and enables differentiated innovation.

AWS also wins praise for its “customizable solutions”, which seems to reinforce perceptions that Amazon Connect is a platform for the builders.

Yet, the perceptions are outdated. For instance, its major platform re-architecture, announced in March 2025, embedded first-party AI capabilities across its platform, enabling customers to deploy native AI in “just a few clicks”.

As such, Amazon Connect is now more of a solution for businesses that want an “oven-ready” platform, as well as those looking to build. Unfortunately, whether intended or not, this report somewhat reinforces those antiquated notions.

Elsewhere, Gartner praises AWS’s “ability to scale”. Yet, surprisingly, omits its pricing model, which advances on consumption-based pricing. Indeed, it includes a single price for all AI features, lowers costs for AI testing, and ensures customers don’t need to pay for unused seats. That’s often a big deal-winner for AWS.

Five9

Five9 has endured some negative press in 2025 with multiple rounds of layoffs. However, its CCaaS revenue growth held firm, rising at a double-digit rate.

Gartner credits strengths in its “support services” and “broad market fit”, with Five9 growing far beyond its North American roots and delivering successful enterprise implementations worldwide.

Many of those implementations have a “high attach rate for AI Agent functionality”, per Gartner, with Five9 quick out of the gates in releasing AI agent functionality.

That speed reflects deeper strengths in contact automation, with it being the only CCaaS vendor to make it onto CX Today’s top conversational AI providers to watch list in 2025.

Talkdesk

After a two-year absence, Talkdesk is back in the Leader’s quadrant. Its “industry-specific solutions” are a big reason why, as it not only customizes its products to the sector, but pre-packages specialized integrations and workflows to accelerate migrations and innovation.

The solutions have expanded Talkdesk’s market, as Gartner emphasizes. Yet, another key solution that the CCaaS provider released helped here: Talkdesk Embedded.

Interestingly, this solution helps “embed” elements of Talkdesk’s cloud contact center into third-party CRM and helpdesk systems. Not only is that innovative from a platform convergence perspective, but it makes Talkdesk an attractive option for system integrators (SIs).

Lastly, Gartner lauds Talkdesk’s account managers, who have seemingly helped its customer satisfaction levels rise sharply over the past 18 months.

Yet, CTO Munil Shah, who arrived in April 2024, also deserves plaudits. Indeed, since his arrival, Talkdesk hasn’t just executed on its industry-specific strategy but delivered several unique innovations to boost the customer and employee experience. Its AI Rewriter is an excellent example.

Gartner Magic Quadrant Challengers

Challengers in the Magic Quadrant place in the top left-hand square of the Magic Quadrant, excelling in their “ability to execute” but trailing Leaders in their “completeness of vision”. This year’s Challengers are:

• Content Guru

Content Guru

Like Genesys, Content Guru has established a reputation for doing “big” well. Gartner underscores this, alongside the vendor’s suitability for brands with significant scale and customization requirements.

Additionally, the research firm recognizes “high service availability” and “AI service orchestration” as key differentiators for the brand.

However, Gartner doesn’t reference how Content Guru is converging CCaaS and customer data platform (CDPs). That is a big differentiator, as the provider helps its customers to establish an omni-data layer from which all its AI innovation can spring, setting customers up for long-term success.

Given this, it’s perhaps surprising that Content Guru didn’t score better in its “completeness of vision”. Nevertheless, Gartner does raise “negotiated SLAs” and “complex pricing” as two of its cautions.

Gartner Magic Quadrant Visionaries

Visionaries in the Magic Quadrant sit in the bottom right-hand square of the Magic Quadrant, scoring well in their “completeness of vision” but lagging Leaders in their “ability to execute”. This year’s Visionaries are:

• There are no Visionaries in the 2025 Gartner Magic Quadrant for CCaaS.

Gartner Magic Quadrant Niche Players

Niche Players in the Magic Quadrant sit in the bottom left-hand square of the Magic Quadrant. While they have accrued a strong industry presence, their “ability to execute” and “completeness of vision” fall behind the market Leaders, according to Gartner. This year’s Niche Players are:

• Cisco
• Zoom
• Vonage

Cisco

Cisco is one of only two “Customers’ Choice” vendors, which Gartner tagged in its latest Peer Insights “Voice of the Customer” for CCaaS report. That reflects the high satisfaction rates of its install base.

As such, it’s surprising that the analyst didn’t note positive word of mouth as a core strength. Instead, it applauded how Cisco has converged CCaaS with UCaaS and CPaaS. Indeed, this combination boosts the Webex Contact Center in various ways, such as enabling swarming and next-level proactive customer service. As AI agents soon start leading outbound conversations, that latter strength will come increasingly into its own.

Meanwhile, the report also commends Cisco for its “global support network” and “advanced security measures”. The latter demonstrates how Cisco, like AWS, is doing an excellent job of leveraging its broader portfolio to deliver unique innovation.

Nevertheless, it has dropped into the Niche Player Quadrant. Amongst Cisco’s listed cautions are its “multiple administrative interfaces” and “limited third-party integrations”, which are possible justifications here.

Zoom

Zoom only entered the CCaaS space in 2022, but ever since, its innovation streak has gone from strength to strength, while its install base has surged.

Much of that is due to its reputation for delivering consumer-grade tech to the enterprise. Yet, Gartner also pinpoints its “tight UCaaS integration” as a principal reason, alongside its “native AI functionality” and “simplified setup and administration.”

However, Zoom doesn’t just think of CCaaS and UCaaS. On one platform, it delivers both solutions alongside conversational AI, sales intelligence, Workvivo, and many more applications. That single ecosystem sets the stage for original innovation and data sharing that can set Zoom apart.

As such, expect Zoom to rise in the coming years, as it also addresses the “breadth of features” and “third-party integrations” concerns Gartner pinpoints in its report.

Vonage

Like Cisco, Vonage wins plaudits for converging CCaaS, UCaaS, and CPaaS. Its CPaaS offering is particularly strong, though, enabling access to APIs – like 5G network APIs – that strengthen the spine of Vonage’s contact center platform.

Gartner also applauds how Vonage has optimized its solution for the midmarket and its “Salesforce Service Cloud integration”, although the latter doesn’t appear much different from the integrations offered by Genesys and AWS.

Where Vonage does stand apart is in its Intelligent Workspace, which leverages AI to rearrange the screen based on the call, enabling agents to better navigate their desktops.

However, Gartner cautions toward the provider’s “system reporting” and “tendency toward use of CRM partner technology.”

The CCaaS Magic Quadrant: A Third-Party Take

For an extra perspective, CX Today invited Zeus Kerravala, Principal Analyst at ZK Research, to share an alternative take.

Kerravala anticipated NiCE and Genesys would lead the pack again, yet agreed with AWS creeping closer to Gartner’s frontrunners.

“As a late entrant, for Amazon to have made its way into such a strong position in such a short period of time is a testament to how much they have invested in this business, said Kerravala. “They came to market around the same time as Twilio but have certainly set themselves apart.”

Five9 also maintains its place at the top. However, the analyst cautions about its long-term sticking power. While acknowledging its CTO as an industry thought-leader, Kerravala referenced the executive turnover, since Gartner completed its research, as a concern. After all, it likely indicates flux in its strategy.

“[This] shows the flaw in the Magic Quadrant,” he noted. “It’s a document that is supposed to live on for a year but can’t adapt to market changes.”

Nevertheless, Kerravala’s most significant gripe is with Cisco’s drop from a Challenger to a Niche Player. “Gartner’s position does not align with reality at all,” he said.

Cisco CCaaS has shown very strong growth and was a Gartner Peer Insight Customer Choice [provider] for 2025. This shows the disjointedness in Gartner research.

“While I don’t think they’re a leader yet, they have a very high level of execution capability and should be a Challenger or Visionary.”

Lastly, Kerravala stated his belief that Zoom should shift right, citing its vision for enterprise communications beyond CCaaS and UCaaS, alongside “very strong” channel feedback and its “tremendous growth up and down market.”

Delve into additional coverage of Magic Quadrant reports exploring adjacent technologies below:

• Gartner Magic Quadrant for CRM Customer Engagement Center (CEC) 2024
• Gartner Magic Quadrant for Conversational AI Platforms 2025
• Gartner Magic Quadrant for Communications Platform as a Service (CPaaS) 2025

As of today, the following out-of-the-box agents are now available:

• Audience Agent: Builds and recommends high-value customer segments.
• Journey Agent: Designs and optimizes digital experience and campaigns across channels to meet specific outcomes.
• Experimentation Agent: Tests ideas (such as those to improve the website experience), analyzes impact, and generates AI-driven optimization insights.
• Data Insights Agent: Gathers and visualizes customer signals to “visualize, forecast, and remediate” the impact of various customer experience initiatives.
• Site Optimization Agent: Monitors websites and flags issues (such as broken backlinks) to boost performance and engagement.
• Product Support Agent: Streamlines support resolution by creating and tracking cases.

All these agents will be supported by the Adobe Experience Platform (AEP), the vendor’s digital experience platform, ensuring that the AI agents are “rooted in a deep understanding of enterprise data and workflows.”

The agents will be accessible across various Adobe enterprise applications, including Adobe Real-Time Customer Data Platform, Adobe Experience Manager, Adobe Journey Optimizer, and Adobe Customer Journey Analytics.

They are designed to help businesses tackle core customer experience challenges, such as audience segmentation, journey building, experimentation, and analytics, without the manual effort traditionally required.

To help users wrangle their new army of AI agents, Adobe has also released its AEP Agent Orchestrator.

The tool is powered by a reasoning engine that blends decision science with advanced language models.

This enables agents to understand context, plan multi-step actions, and refine responses, with new partnerships from Cognizant, Google Cloud, Havas, Medallia, and Omnicom expanding its reach across the CX ecosystem.

The result is goal-driven, contextually relevant automation, which also provides an option to keep a human in the loop for added oversight and refinement.

In discussing the news, Anjul Bhambhri, Senior VP of Engineering for Adobe Experience Cloud, stated:

Adobe’s agentic AI innovations are redefining customer experience orchestration in the era of AI, enabling businesses to unlock productivity with agent orchestration, reimagine longstanding processes, and deliver personalized experiences at scale to drive business growth.

Indeed, brands such as Hershey, Lenovo, PGA TOUR, Wegmans, and Wilson are already putting Adobe’s AI agents to work.

Adobe has reported that these organizations have used the AI-powered tools to boost internal expertise and deliver more seamless, impactful customer experiences.

Adobe’s Agentic AI Vision

While the new AI agents and Agent Orchestrator may have only just gone live, they were first teased at the Adobe Summit 2025 back in March.

Interestingly, at the time, the vendor mentioned ten purpose-built agents, with Account Qualification, Content Production, Data Engineering, and Workflow Optimization solutions seemingly delayed.

However, whether or not the additional four agents are eventually released, it is clear that Adobe is firmly planting its flag atop the agentic AI summit (excuse the pun.)

For Liz Miller, VP and Principal Analyst at Constellation Research, the release is a way for Adobe to “bring agents that work for marketing together with data that works for business.”

The Adobe Experience Platform is critical to helping facilitate this cross-pollination of data.

By unifying business and customer data into a single, harmonized space, it provides the foundation on which all of Adobe’s applications can build, enabling faster, smarter, and more connected customer experiences.

Miller also outlined the “specificity of the reasoning engine that underpins the genetic processes” as a key aspect of the release.

These are not simple AI workflows. These are workflows that reason and can take autonomous action on behalf of the brand and on behalf of the marketer.

While it is still very early days, the new agents and orchestration tools signal Adobe’s intent to maximize the potential of agentic AI in the enterprise space.

By embedding its agents directly into CX workflows, Adobe is aiming to enable teams to automate complex processes, act on real-time insights, and deliver more personalized, data-driven experiences at scale.

Another Adobe Agentic AI Announcement

Although the new agents and orchestration tools dominated the headlines, Adobe also confirmed plans to roll out an Experience Platform Agent Composer.

The interface is designed to let businesses customize AI agents in line with brand guidelines and policy controls.

The tool will also help teams fine-tune agent behavior, accelerate time-to-value, and extend capabilities into new industries and use cases.

To support developers, Adobe will introduce an Agent SDK and Agent Registry, enabling the creation and orchestration of bespoke agentic apps.

Crucially, the platform also supports multi-agent collaboration through its Agent2Agent protocol, paving the way for seamless interoperability across ecosystems and more tailored, context-driven workflows.

Now, as part of the Kao Corporation, it continues to scale its global footprint.

Naresh Krishnamurthy plays a big role in that effort, leading digital customer experience transformation at Molton Brown.

In doing so, he aims to connect the company’s legacy with the future of digital CX. Here are five ways in which his team is doing so.

1. Follow a More Experiential Loyalty Model

Traditionally, brands in the luxury space looked at customer loyalty through transactions, i.e., points and purchases. Molton Brown has evolved this into an experiential model using SAP CX.

Sharing more, Krishnamurthy said:

We now offer exclusive previews, personalized fragrance layering advice, tailored content, and even gamification features like our Fragrance Finder on the website.

Behind the scenes, Molton Brown also uses SAP Commerce Cloud and Master Data to create a single customer view that crosses customer-facing departments.

2. Embrace “Phygital”

“Phygital” is the practice of blending physical and digital experiences. Molton Brown is embracing a phygital strategy.

For instance, it’s ensuring the product assortment a customer sees on its website mirrors what’s available in their closest store, eliminating confusion and strengthening consistency.

Now, it’s looking to go further by uplevelling its personalization strategy, so in-store, online, and AI assistants can anticipate customer needs and provide tailored recommendations.

That strategy hinges on real-time data orchestration. So, for example, if a customer browses woody fragrances online, that preference is captured in SAP. When they later book a boutique consultation and scan their loyalty profile on arrival, the associate sees a single customer view. That includes fragrance preferences, online interactions, and campaign responses, enabling the associate to make more relevant suggestions.

3. Leverage “Non-Gimmicky” Gamification

As noted, Molton Brown launched a Fragrance Finder on its e-commerce website. This offers a gamified experience where customers answer personality- and preference-based questions. It then recommends products tailored to their responses.

“It’s not just a gimmick; it’s a way to immerse customers in our brand story,” explained Krishnamurthy. “The focus is on engagement, not just conversion.” He continued:

All the data flows back into our single customer view. This means when a customer later visits a boutique, associates already understand which fragrances have resonated with them.

Additionally, Molton Brown has layered in exclusivity. For example, loyalty members can unlock rewards, previews, or special access through these gamified interactions.

Meanwhile, seasonal experiences, such as Molton Brown’s annual Christmas games, add to this engagement while staying aligned with the brand’s luxury positioning.

“It’s a modern, digital-first way to make luxury interactive,” concluded Krishnamurthy.

4. Get Strategic on Specific Social Channels

At first, many brands jump on a new social channel to open a new door to the business. Yet, Molton Brown is always cautious to create a unique experience through its channels.

For instance, it sees Instagram as key for unveiling campaigns, sharing artistry, fragrance creation, craft, and heritage through rich imagery.

Meanwhile, TikTok is more playful and focuses on short-form engagement, such as fragrance layering tips or seasonal rituals.

“Different generations gravitate to different channels, so we tailor content accordingly,” said Krishnamurthy. “What’s critical is that all of this isn’t siloed.”

“Whether a customer discovers us via Instagram, plays with the Fragrance Finder online, or later visits Covent Garden, the journey is continuous.”

While doing so, Molton Brown recognizes preferences across channels through its SAP CX stack, customer data platform (CDP), and loyalty systems.

Ultimately, its goal isn’t to chase every platform, but ensure one consistency: wherever customers interact, they experience the brand promise.

5. Prepare for a Future of Conversational Commerce

In April 2025, OpenAI rolled out shopping in ChatGPT following rumors of a big Spotify partnership.

The announcement beckoned a future of conversational commerce, and Molton Brown is closely monitoring these developments.

Krishnamurthy explained: “The opportunity for us isn’t just about visibility, it’s about how we show up as a luxury house.

Our focus is on using AI to guide discovery in a way that feels authentic, personal, and true to our heritage.

For example, if a customer asks for the best fragrance on a summer evening, Molton Brown hopes AI will guide them with the expertise and storytelling they expect from an associate.

This focus is particularly important in fragrance and body care, a category that is naturally harder to sell online. By using AI and personalization, Molton Brown bridges the gap between digital and in-person discovery.

Yet, Krishnamurthy also urged his team’s caution. “Luxury is about balancing innovation with exclusivity,” he summarized. “Our priority is a connected experience across all channels.”

What Else Is Molton Brown’s CX Team Focusing On?

Alongside all the above, Molton Brown continues to innovate around the post-purchase experience.

Recently, it has introduced tailored replenishment reminders, fragrance layering rituals, and seasonal discovery boxes. These aim to extend the luxury experience beyond the point of sale.

Krishnamurthy also named sustainability a top priority after noting a trend in the number of customers asking how sustainable its products are.

As such, the company has pledged to go further with its sourcing and refillable packaging. “It’s integral to our customer experience and brand promise,” Krishnamurthy confirmed.

Yet, Krishnamurthy and his team are constantly considering new ways to innovate around digital customer experiences. To stay up to date, follow him on LinkedIn.

Yet, on their own, use cases will only drive so much value.  

Instead, some contact center leaders are realizing a much bigger opportunity, and it starts with data and context. 

These leaders are asking: Who are our customers? Why do they reach out? Who are our agents? What intents do they handle well? Where do they need training?  

Then, finally, how do we connect the dots? 

Ultimately, that’s a challenge that deploying a call summary tool or AI agent won’t solve. However, an integrated contact center data layer will. 

Building a Contact Center Data Layer

To build a data layer, don’t jump to solutions. Consider: What data do we already have? What do we know we need to know? And what else should we be looking for? 

Then, build those insights into a data layer, which can inform the contact center’s routing strategies, quality assurance, journey orchestration, and beyond.  

That intelligence should be real-time and actionable, not just post-facto analysis, which requires extra human capital to make sense of.  

Unfortunately, most CCaaS platforms aren’t set up for this. Instead, they rely on customers to integrate diverse information into their data lake. 

However, Content Guru is flipping the script.  

The Content Guru Approach

Content Guru offers a full-stack CCaaS platform with an AI orchestration layer, alongside integrated workforce management, quality assurance, conversational intelligence, and various other tools. 

All these generate data that flows into the vendor’s adjacent customer data platform (CDP): storm CKS. 

As contact centers migrate to Content Guru, they can start with the data they already have and get it structured and integrated before creating a data loop.  

The data loop takes new data, like analytics, and feeds it in automatically. 

In doing so, Content Guru doesn’t just present a deep contact center platform but a system that becomes smarter over time.  

A Contact Center That Gets Smarter

In most customer environments, there are multiple systems of record. By converging its storm CCaaS and CDP tech, Content Guru creates a single, unified, persistent data layer.  

Over time, contact centers can expose that layer to more data from various solutions, like Internet of Things (IoT) devices that feed in real-time information. 

In doing so, businesses can create an “omni-data strategy” that sets the stage for new AI use cases. 

As Martin Taylor, Deputy CEO of Content Guru, explained during a recent interview: “Customers often come to us already thinking about deployment. We usually have to walk them back a few steps and ask: Is your data in a stable state? Are you recording the same types of events consistently? Do you have overlapping data or similar information presented in different ways? 

Part of the role of omni-data and the customer data platform is to smooth all of that out – like running a lawn roller over it – so the data becomes tidy, consistent, and accurate. Once that’s in place, it can then be used effectively to build AI models that become smarter over time.

Consider the IoT example and how it may bolster a contact center AI strategy. An IoT device could send signals from gadgets like smart meters, which indicate an issue, into the data layer, where it’s normalized.   

Feeding from this, a CDP can trigger sending a proactive notification to the customer, as it is a system of action, not just a system of record, before they even know something has gone wrong, removing the need for that customer to make contact.  

Yet, that’s just one possibility of many, as this approach supports data-backed routing, customer journey mapping, hyper-personalized interactions, and more. 

Indeed, Content Guru’s strategy brings new capabilities to the market, not just new features. 

Contact Center Buyers Should Ask…  

Without a clear-cut data strategy, the effectiveness of contact center AI has a ceiling. Yet, most CCaaS platforms aren’t set up to deliver that, without leaning on third parties.  

As such, contact center buyers should ask: What’s the trajectory?  

Those providers that answer this question best will have a vision for building an infrastructure that adapts and evolves with tech, regardless of next year’s buzzword. 

Content Guru’s storm platform and brain AI orchestration layer can offer a compelling answer. For more about its tech, visit: www.contentguru.com   

Microsoft to Scrap Business Discounts Across All Its Online Services, Including 365, Azure, and Dynamics 365

Microsoft is removing discounting on Online Services products purchased through its volume licensing programs, starting November 1, 2025.

Its Online Services portfolio includes Microsoft 365, Azure, Dynamics 365, Power, and other specialized solutions, such as Microsoft Defender and GitHub.

Currently, businesses can secure volume licenses for many of these online services at various price points, across Price Levels A–D. These levels vary by region and customer category.

However, the move means that every Online Service – sold under an Enterprise Agreement (EA) or a Products and Services Agreement (MPSA) – has one consistent price across each tier. That price will be available on Microsoft’s website.

As such, Microsoft limits some customers, renewing after October 31, 2025, from securing the same discounts as in their previous contracts.

That said, the standardized price could be lower than what some customers currently pay.

Moreover, while Microsoft customers may not be able to secure license cost discounts, they could still seek concessions on multi-year terms and value-added services (Read more…).

Salesforce to Snap Up Waii, Boost Data Cloud & Tableau Next

Salesforce has agreed to acquire Waii, a natural language-to-SQL platform provider.

Waii offers technology that translates everyday language into powerful SQL queries, removing the need for data scientists and engineers.

Its software benefits businesses as most store data in complex databases requiring SQL access. Waii allows non-technical users to extract data.

For instance, a service or sales rep may ask: “Which customers in region A are up for renewal?” From there, Waii generates an SQL code allowing the rep to retrieve the answer.

Alongside that capability, Waii has built a self-learning metadata knowledge graph. Think of it as a smart map of data that adapts to the business’s unique structure.

With Waii, Salesforce hopes to make the data stored on its platform more accessible and relevant to everyone in the business, regardless of their technical know-how.

Raveendrnathan Loganathan, EVP of Salesforce Data Cloud, doubled down on this. He said: “The future of business isn’t about having the most data; it’s about making that data speak a common language.

Our vision is to empower every employee, from the boardroom to the frontline, to have a trusted conversation with their data.

As Loganathan suggests, increasing data accessibility by taking away the need for specialized SQL skills is the principal driver for this acquisition (Read more…).

Cisco Confirms Two $1BN+ Megadeals, Including Webex

Cisco has confirmed that two enterprises placed mega-orders worth over $1BN during fiscal year (FY) 2025.

Notably, from a customer experience perspective, both deals included Cisco’s collaboration suite, which comprises CCaaS, CPaaS, and UCaaS solutions.

Chuck Robbins, CEO of Cisco, celebrated the wins during the company’s latest earnings call. He said:

Two webscale customers each placed total orders of over $1,000,000,000 for networking, security, collaboration (Webex), and observability in FY 2025.

The megadeals underscore the growing payoff of Cisco’s strategy to pull Webex through as part of larger enterprise deals.

In 2024, Cisco accelerated that strategy by centralizing Webex with networking and security in one business unit, unifying the go-to-market for sales teams and partners.

Additionally, Cisco kick-started a drive to build capabilities from some solutions into others, enabling differentiated innovation (Read more…).

NiCE Tightens Its Salesforce Integration, Opens Up to Agentforce

NiCE has expanded its Salesforce partnership, announcing a deeper CCaaS-CRM integration.

The integration builds on the 2022 release of Bring Your Own Telephony with Salesforce Service Cloud Voice.

Back then, NiCE, like many CCaaS competitors, embedded its voice channel within Service Cloud.

Now, the contact center stalwart is adding workforce engagement management capabilities (WEM) into the CRM desktop and providing an integrated channel set.

In doing so, NiCE doesn’t present competing capabilities, as with similar Service Cloud integrations, but offers a unified channel mix and inserts unique features into the CRM.

Indeed, while NiCE has yet to specify which WEM tools it will augment the CRM with, it leads the CCaaS space in resource planning and may provide many value-adding capabilities.

Additionally, the vendor has pledged to join the Salesforce Zero Copy Partner Network, claiming to be the first CCaaS provider to do so.

By establishing a bidirectional Zero Copy integration with Salesforce Data Cloud, NiCE can pull data from its CXone Mpower solution into the customer data platform (CDP), and vice versa (Read more…).

The integration builds on the 2022 release of Bring Your Own Telephony with Salesforce Service Cloud Voice.

Back then, NiCE, like many CCaaS competitors, embedded its voice channel within Service Cloud.

Now, the contact center stalwart is adding workforce engagement management capabilities (WEM) into the CRM desktop and providing an integrated channel set.

In doing so, NiCE doesn’t present competing capabilities, as with similar Service Cloud integrations, but offers a unified channel mix and inserts unique features into the CRM.

Indeed, while NiCE has yet to specify which WEM tools it will augment the CRM with, it leads the CCaaS space in resource planning and may provide many value-adding capabilities.

Additionally, the vendor has pledged to join the Salesforce Zero Copy Partner Network, claiming to be the first CCaaS provider to do so.

By establishing a bidirectional Zero Copy integration with Salesforce Data Cloud, NiCE can pull data from its CXone Mpower solution into the customer data platform (CDP), and vice versa.

As a result, NiCE creates a shared data foundation not only with Service Cloud, but all the other applications businesses have plugged into Data Cloud.

Ultimately, that sets the stage for mutual customers to leverage AI agents, connect workflows, and potentially automate end-to-end customer fulfilment.

These AI agents may be NiCE Mpower or Salesforce Agentforce agents, running on the CXone Mpower Orchestrator and leveraging the combined intelligence on the CDP.

“This renewed partnership with Salesforce marks more than just deeper integration; it signals a vision for the future of customer service,” said Barry Cooper, President of CX Division at NiCE.

Together, we will collaborate to help businesses move from disconnected touchpoints to intelligently orchestrated experiences that span the entire customer journey.

“As our partnership grows, so does our commitment to helping our mutual customers lead the way in AI-powered service.”

Alongside AI agents and the potential for automation, the shared intelligence on Data Cloud can filter into Service Cloud, ensuring a unified customer view.

However, that data also becomes available to other customer-facing functions, like marketing, sales, and commerce, who can leverage it for smarter engagements and campaigns.

As such, the new integration breaks down system and functional silos. Kishan Chetan, Executive VP and GM Service Cloud at Salesforce, stressed this, stating:

Together, we’re helping organizations move beyond channel silos and orchestrate intelligent, outcomes-driven interactions at scale, ultimately delivering greater value to our mutual customer through continued innovation.

Interestingly, the announcement comes just a week after Salesforce invested $750MN in NiCE’s chief CCaaS rival, Genesys.

Yet, despite that investment, the CRM leader stressed its desire to avoid playing favorites.

Sure, some may be able to bring products to market first, yet Salesforce wishes to service its fellow contact center providers with opportunities to build similar innovations.

As such, expect others to follow NiCE and join the Salesforce Zero Copy Partner Network.

However, NiCE’s orchestration capabilities may help it stay ahead of the competition. As Zeus Kerravala summed up:

With CX, there are too many silos. Salesforce addresses the front end of the customer journey, and NiCE the back end. This allows businesses to automate workflows across the entire journey, creating significantly better experiences.

Alongside this announcement, NiCE has also established partnerships with AWS, ServiceNow, and Snowflake, aiming to support more customers in tying together end-to-end fulfilment flows.

Ultimately, this is another step on that journey. Yet, given Salesforce’s CRM dominance, it’s a significant leap forward.