Today’s contact centers are interacting with customers that stretch from the Silent Generation all the way to Gen Alpha in a day.

As Garry Gormley, Founder of FAB Solutions, put it, “We’re at a strange impasse.”

There’s the Silents and Boomers who still value voice contact with human agents; Gen X and Millennials who mix digital self-service with human support; Gen Z, who jump between apps and channels; and the emerging Gen Alphas, who are growing up expecting hyper-personalized, predictive experiences.

Put all six generations together, and it’s easy to see why no single communication style or service model can cover everyone.

Managing by Generation Isn’t Just an HR Strategy

There’s an economic case for taking generational differences seriously. Data from the World Economic Forum shows that countries can increase their GDP by 19% over 10 years by managing their workforce based on generational groups, and that extrapolates itself out to customers, noted Katy Forsyth, Managing Director of Red Recruitment.

Every generation wants speed, multichannel and intuitive service, but the defining difference between the generations is that younger consumers want personalization, Forsyth said.

“[Gen Z] want everything addressed to them personally. They want an emotional connection with their service… And then when we get the Alphas coming along, they’re even more hyper-personalized.”

These consumers expect brands to use predictive analysis to make recommendations based on the activity on their phones.

Much of this comes down to economic pressure. Gen Z’s spending habits are different because their financial realities are different. Forsyth highlighted that in the UK, “it costs Gen Z six times their salary to get a house deposit. For an Xer in 1995, it was a third of one year’s salary.”

It’s partly because of that smaller buying power that when Gen Z consumers do choose to spend, they want meaning behind the transaction. “The personalization is super important,” Forsyth said, noting that on Black Friday, Gen Z consumers will spend an average of £255 on purchases, which is almost double the £155 that Gen Xers are expected to spend.

That makes Gen Z customers an important demographic for brands to address and they need to understand how to appeal to them. Younger consumers are the mostly likely to use GenAI and AI assistants in their holiday shopping, with Gen Z accounting for two-thirds of shoppers turning to ChatGPT for gift inspiration, according to research from Bread Financial.

Despite narratives around younger generations’ aversion to picking up the phone, Forsyth warned against oversimplification when it comes to providing voice channels:

“Even though they might want to self-serve, you’ll be surprised… as soon as it gets uncomfortable, they want voice. Do not believe the headlines.”

Data shows that when dealing with emotional issues Gen Z wants to speak to a service agent, indicating that companies need to tread carefully and avoid dealing with customers on the basis of assumptions.

Matching Service to the Customer You Actually Serve

For contact centers, getting to grips with practical ways to stay authentic as they juggle all the different ways generations communicate is not an easy task. Beyond managing multiple channels, it’s about making sure every interaction feels honest and human, whether a customer reaches out on the phone, chat or through social.

That means giving contact center agents the freedom and tools to adjust their tone to the customer, using technology to support real connection.

While older generations may still prefer a softened message, younger generations will not tolerate spin. Forsyth said of Gen Z:

“They do not trust you as businesses, whether you’re employing them or selling to them… They will take bad news… but you need to tell them the truth. Do not flower it up… Forget the good news, just go for the jugular, and they’ll respect you a whole lot more. Tell them it’s expensive, but why?”

Trust was a recurring theme during the discussion, as well as the ways in which it spans across generations.

Marco Ndrecaj, Director of Customer Experience Management, Shared Services Connected, said the biggest threat to customer experience isn’t channel fragmentation, it’s eroding trust:

“We need to make sure that we are demonstrating trust in the right way, through communicating honestly and openly about the engagements that we have, either through a bot, or through an AI agent, or through a live person and being really clear on the distinction between those and servicing that to the right people.”

Ndrecaj highlighted a sentiment from one of his contact center advisors: “Customers are being overwhelmed with information… technology on its own doesn’t build trust. People do… What matters is how we use technology to enhance the customer connection.”

The balance between human empathy and AI capability is the foundation on which to build credibility, increasing trust rather than eroding it.

“Humans bring empathy and judgment, while AI provides skill and insight. And when brands get this balance right, that’s when the magic happens.”

Brands are challenged with producing content to appeal to the TikTok generation, which gravitates toward fast-paced, video-led storytelling, while remaining relevant to older audiences that engage in different ways. “How do we think about how we adapt and create that video first experience for the consumers of tomorrow?” Ndrecaj said.

But Ndrecaj also urged brands not to confuse channels with meaning: “I don’t think it’s the actual medium. It’s more around how you make them feel. Gen Z and Gen Alpha think very differently. It’s not about video content or… collecting points. It’s about them feeling a sense of purpose. It’s about organizations that actually have shared values.”

Ndrecaj pointed to brands like Nike and Lego as examples, noting: “They actually invite their customers to co-create products. And that is a feeling that you can’t buy through TikTok or Instagram.” Forsyth, too, cited Nike as brand that is connecting well with customer service for Gen Alpha.

Brands also need to strike a balance between acknowledging the differences between generations and making assumptions about what customers want.

Beyond Stereotypes: Reading the Real Customer Need

Sandrea Morgan, Head of Customer Support at Adanola, warned against treating generational traits as blanket truths. “It depends on where you are as a business and what type of customer you’re interacting with…. because what a customer expects depends on the experience they want to have. What am I trying to purchase. Is it something for the home? Is it something for you personally? That does change what you expect no matter what age you are.”

Morgan contrasted the customer expectations of two different types of businesses.

“In my current role [with a] younger Gen Z customer, the majority of what they want is [for interactions] to be simple, quick, on brand, but pretty efficient and professional. I was in a role a year ago, [with] a slightly older customer. The product was a bit more expensive. There was more of a luxury feel to it. What they wanted from us was very, very different, and the tone of voice that the advisor had was very, very different.”

Understanding the customer makes it easier for brands to move beyond generic customer service design and give their contact center employees the tools and training they need to connect with customers in the most appropriate way for the service they expect.

“Sometimes that’s a piece of technology that you can give them, and sometimes it’s about the training that you give them to be the best in their job every day,” Morgan added, stressing the importance of aligning agents’ skills to the customers they serve.

And to complicate things even further, figuring out what customers want isn’t straightforward, because while they might say they make purchases based on their values, their actual choices can tell a different story.

For Gen Z, for example, their values matter, but they are also under strain from the limits to spending power. As Forsyth pointed out:

“Their values are really critical, but we are in a cost-of-living crisis that is affecting the Zs, and they’re having their values pushed as a result of that.”

Businesses need to be prepared for that to change over the next three to five years and make sustainability more cost-effective to deliver. “Then we keep every generation happy, but particularly the Alphas, who will just be hitting with the spending power,” Forsyth said, as they transition to becoming a larger share of retail spend.

Ultimately, serving customers spanning six generations is about listening closely and building the kind of service that can flex as customers’ needs shift.

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

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

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

What is Customer Loyalty?

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

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

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

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

The ROI of Customer Loyalty

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

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

The return is measurable:

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

What is Customer Loyalty Management?

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

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

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

Loyalty Management Tools and Platforms

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

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

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

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

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

How to Measure Customer Loyalty

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

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

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

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

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

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

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

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

How to Choose Loyalty Management Software

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

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

Here’s what separates the useful from the disruptive:

True Integration

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

That means:

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

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

Dashboards That Get Used

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

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

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

Scalability

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

Look for:

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

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

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

Best Practices for Improving Customer Loyalty

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

Build Feedback Loops That Actually Close

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

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

Use Tiering: But Don’t Let It Turn Transactional

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

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

Let AI Do More Than Segment

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

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

Tie Service Quality to Loyalty Outcomes

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

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

Reward the Behavior You Want More Of

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

Instead, reward the moments that drive growth:

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

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

Localize Where It Matters

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

Consider:

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

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

Customer Loyalty Management + Service: The Critical Link

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

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

When Service Is Seamless, Loyalty Feels Earned

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

This is where integration matters:

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

Proactive Service = Preventative Loyalty Loss

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

For example:

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

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

Empower Agents Like They’re Brand Ambassadors

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

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

Customer Loyalty Management Trends to Watch

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

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

Here’s what’s changing right now.

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

Customer Loyalty Management Beyond the Transaction

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

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

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

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

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

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

Will Salesforce’s Informatica Acquisition Make Agentforce Unstoppable?

Salesforce has announced the acquisition of Informatica.

First reported back in May, the purchase has now officially been confirmed for approximately $8BN.

The deal will see Salesforce leverage Informatica’s AI-powered cloud data management capabilities to improve its agentic AI offerings – most notably, the Agentforce platform.

Alongside the data catalog, Salesforce will also gain access to Informatica’s integration, governance, quality and privacy, metadata management, and Master Data Management (MDM) services.

The end goal is to use these capabilities to build a unified data foundation for agentic AI, enabling safe, responsible, and scalable AI agents across the enterprise.

Indeed, in discussing the news, Salesforce Chair and CEO Marc Benioff described data and context as the “true fuel of Agentforce.”

“When companies get their data right, they get their AI right, and Agentforce becomes unstoppable.”

In terms of the specifics, Salesforce also detailed how Informatica’s capabilities will sharpen its Data 360 feature… (Read more).

Cloudflare Outage Disrupts Major Platforms, Payments, and Black Friday Plans

It’s becoming a familiar story: A technical glitch at Cloudflare, one of the biggest internet infrastructure providers, knocked a number of websites and services offline for a few hours on November 18, disrupting customer access and merchant payments.

X (formerly Twitter), ChatGPT, Claude, Perplexity, Spotify and payment giant Square were among those caught up in the fallout.

The trouble began just before 11:48 GMT, when Cloudflare posted that it was dealing with an “internal service degradation” causing intermittent outages across its service network. Users saw error pages, stalled logins, broken APIs, and sites claiming connections were blocked. There were a few conflicting signals about the restoration progress, as at one stage the company reported that services were beginning to recover, but then around 15 minutes later reverted to “continuing to investigate this issue.”

By 13:04 GMT, Cloudflare admitted that one of its fixes involved disabling WARP access in London entirely, temporarily cutting off users from its WARP performance-boosting and VPN service that helps secure and accelerate internet connections:

“During our attempts to remediate, we have disabled WARP access in London. Users in London trying to access the Internet via WARP will see a failure to connect.”

Cloudflare announced a fix five minutes later, but continued to receive “reports of intermittent errors” until close to 17:00 GMT… (Read more).

Five9 Targets CX Inefficiencies with New Genius AI Upgrades

Five9 has introduced a fresh wave of Genius AI updates designed to push the company’s “Agentic CX” vision further into the contact center core.

Announced at the company’s CX Summit in Nashville, the new capabilities span routing, quality management, analytics, and digital engagement, tying them more closely together to help organizations extract greater value from AI at scale.

As many enterprises attempt to take AI from pilot projects into day-to-day operations, fragmentation continues to slow progress.

Disconnected data, inconsistent reporting, and standalone AI experiments often make it difficult to achieve the continuous improvement leaders expect.

Five9’s latest releases aim to combat these challenges by treating AI not as an add-on but as the connective layer running across the environment.

Five9 Chief Product Officer Ajay Awatramani framed the shift as a more fundamental rethinking of how AI should function inside the contact center:

“Our Agentic CX vision is about creating systems that don’t just respond but also help teams better understand and anticipate customer needs.”

So, let’s take a closer look at Five9’s newest features… (Read more).

UJET Acquires Spiral to Address Customer Data Analysis Roadblocks

UJET has announced its acquisition of Spiral to bolster its AI capabilities.

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… (Read more).

At London’s annual Call and Contact Centre Expo, the telecommunications company revealed how its customer-centric approach to limit consumer frustration has improved its overall loyalty.  

This solution is aligned with Vodafone’s strategy to transform customer experience. 

Customer experience results have been improved since the strategy launch in July 2025, with 9 out of 15 of its markets leading with this new strategy, resulting in a six percent reduction in company detraction after the first few months. 

When first researching customer experience strategies, Vodafone discovered that seamless interactions were a high priority for customers, with frequent causes of company detraction relating to negative customer experiences. 

These incidences included: holding for additional agents, transferring calls, repeated conversations, and a company’s failure to keep promises. 

In fact, they had discovered that customers who had experienced at least one bad experience from customer service were 4 times more likely to abandon the company. 

Melda Sofuoglu, Global Senior CX and Service Excellence Senior Manager at Vodafone, explained how the customer expectations have grown since the rise of AI in the CX space:

“We are operating in a rapidly changing industry – expectations have grown to 24/7 service.” 

However, research revealed that as long as customer interactions remained seamless, then customers would be more likely to remain with a company that avoided friction. 

And when companies failed to deliver on results, 46% of customers would research Google to find answers to their issues, driving enterprise intensity to produce better results as customers discover what sets the bar in the CX space. 

Just Ask Once

Vodafone has since researched some of the leading customer services spaces online, including Google and Octopus, to take elements and utilize the most productive strategy for resolving customer complaints. 

The strategy, known as ‘Just Ask Once’, began in 2024 to target pain points in the company’s Albania market, with the aim of resolving a customer issue after just one interaction. 

This strategy utilized generative AI omnichannel service to avoid customers re-explaining issues and call waiting times to resolve queries, whilst also keeping customers in the loop if issues cannot be solved immediately to avoid confusion or miscommunication via text. 

This is also done by deploying Vodafone’s suite of capabilities, such as Super-TOBi, a generative AI assistant that handles complex conversations and queries in comparison to the standatd TOBi chat bot. 

This strategy, however, is not designed to elminate human agents from the mix, but rather to place them at the center of this strategy with chat bots as a second option during traffic spikes, with many of these queries being completed through human agents rather than bots to avoid frustration. 

These bots simply allow agents to complete Vodafone’s vision for setting the new standard for customer experience centered around meaningful interactions and added loyalty, even when mistakes occur. 

This has involved significant investments in human agent training to keep them adapted and involved in the consistently changing state of customer experience, rather than eliminating their positions for AI-only service. 

However, Vodafone has experienced setbacks in this strategy amongst social media responses. 

Aimie Jago, Global Senior CX and Service Excellence Senior Manager at Vodafone, explained how the company are managing the influx from social media:

“In some markets we see some backlash on social media – its more about previous customer experience through chat bots.” 

Resolving past customer interactions remains challenging for Vodafone, arguing that to tackle this previous frustration into returned loyalty they need to experience this new transformation. 

This has affected the company’s ROI after significant investments; however, they are expecting to receive this once business case justification takes place. 

Furthermore, Vodafone’s continues to remain vulnerable, as this strategy depends primarily on technology, investment, and strong sponsorship, due to its small space within the CX space.  

Today, this strategy is being implemented by Vodafone’s global markets, aiming to champion the voice of the customer by creating a strong customer community, available to customers through the Vodafone app. 

First reported back in May, the purchase has now officially been confirmed for approximately $8BN.

The deal will see Salesforce leverage Informatica’s AI-powered cloud data management capabilities to improve its agentic AI offerings – most notably, the Agentforce platform.

Alongside the data catalog, Salesforce will also gain access to Informatica’s integration, governance, quality and privacy, metadata management, and Master Data Management (MDM) services.

The end goal is to use these capabilities to build a unified data foundation for agentic AI, enabling safe, responsible, and scalable AI agents across the enterprise.

Indeed, in discussing the news, Salesforce Chair and CEO Marc Benioff described data and context as the “true fuel of Agentforce.”

“And without clean, connected, trusted data there is no intelligence – only hallucination. Informatica is the trusted platform that turns fragmented enterprise data into context, so every agent can reason, act, and deliver outcomes with precision.

“When companies get their data right, they get their AI right, and Agentforce becomes unstoppable.”

In terms of the specifics, Salesforce also detailed how Informatica’s capabilities will sharpen its Data 360 feature by delivering cleaner, more reliable data across the business, while its integration strengths pair with MuleSoft to create a more complete, enterprise-wide connectivity layer.

That stronger foundation directly benefits Agentforce, giving autonomous agents the trusted data they need to act with confidence.

Tableau also gains from the deal, with clearer, richer context feeding into analytics and lifting the quality of insights across the board.

Making Agentforce “Unstoppable”

Benioff’s remarks around the Informatica deal helping to make Agentforce “unstoppable,” might sound like the usual vendor bravado, but they do speak to a genuine Agentforce concern: so far, the platform has been fairly stoppable.

While Agentforce has turned plenty of heads, its early momentum hasn’t quite matched the noise surrounding it.

Salesforce’s own fanfare helped create expectations that were always going to be difficult to meet, and many customers arrived at pilot projects only to realize they weren’t fully prepared for what the technology demands.

Some of that stems from implementation readiness. Consultancies and end users alike have found themselves wrestling with half-built agents, legacy processes, and a level of technical debt that makes it hard to get consistent outcomes.

The common thread is data. Agentforce can only be as sharp as the information it draws on, and too many organizations are discovering that their underlying data simply isn’t mature enough to support reliable agentic behavior.

Salesforce has offered guidance on best practices, but many customers underestimated just how much groundwork is required before Agentforce can deliver at scale.

When the data feeding the system is inconsistent or siloed, results can feel underwhelming.

Add to that a pricing model that initially confused buyers – particularly around how “conversations” were counted – and it’s clear why enthusiasm occasionally softened once projects moved from demos to delivery.

Salesforce has already taken steps to address some of those sticking points, including replacing the old per-conversation model with the more transparent Flex Credits approach.

Yet the larger barrier remains the data plumbing underneath the platform. And this is where the Informatica acquisition becomes far more than a simple expansion of Salesforce’s portfolio.

Informatica gives Salesforce a proven set of tools for tackling the data preparation issues that have slowed Agentforce deployments.

Its integration fabric, data governance controls, and MDM capabilities reach well beyond the front office, allowing organizations to clean, connect, and align information across the entire enterprise – not just whatever happens to sit inside Salesforce already.

That wider foundation is exactly what agentic systems need if they’re going to reason properly and take reliable action.

By bringing Informatica into the fold, Salesforce can help customers close the readiness gap that has held Agentforce back.

Cleaner inputs mean stronger outputs. Stronger outputs mean more trust in AI-driven automation. And with that trust, the platform finally has the conditions it needs to gain the momentum the early hype promised.

The tech giant is using one of its largest annual events to highlight how AI agents are becoming an operational reality.

Across sales, service, content creation, and employee enablement, Microsoft’s updates signal a shift from “copilots that assist” to agents that act.

Here are the five biggest CX takeaways from this year’s announcements:

1. The Sales Development Agent Brings Autonomous Selling into the Mainstream

Microsoft’s new Sales Development Agent is easily the headline act for CX, sales, and revenue teams.

Now in the Frontier preview, it’s designed to “research, qualify and engage leads during and after business hours,” according to Microsoft, with the aim of ensuring “no lead is left behind.”

For CX and sales leaders, this changes the rhythm of pipeline generation. Rather than relying solely on human outreach or rule-based automation, organizations can now experiment with an autonomous agent that can drive early-stage conversations and escalate only when human intervention adds value.

Security and governance controls are built in through Agent 365, which Microsoft says comes “ready to use with the security, governance and productivity tools in Agent 365 right out of the box.”

This will be one of the most closely watched previews of 2025, especially for teams seeking to modernize their lead engagement strategy without rebuilding their tech stack.

2. Sora 2 Arrives in Microsoft 365 Copilot – A New Era for Customer-Facing Content

In the age of AI, customers are expecting more and more from their service interactions.

With Sora 2 integrated into Microsoft 365 Copilot, marketing and CX teams can meet these enhanced expectations by generating short videos directly within the Create experience.

Microsoft confirms that users will be able to “generate short AI-generated video clips from natural language prompts” and even replace stock footage with AI-generated alternatives.

For CX leaders, this opens a fresh lane of possibility:

• Personalized explainer videos
• Onboarding clips
• Campaign assets
• Product walk-throughs

All without waiting weeks for production resources.

Brand kits, voiceovers, and music tools are included, helping teams create content that feels consistent and polished.

While still part of the Frontier program, it’s a sign of where Microsoft believes customer-facing content creation is heading.

3. Power Apps Gains Agent-Powered Automation – A Boost for CX Operations

Low-code builders have become essential to CX operations, especially when bridging gaps between CRM, support platforms, and custom business processes.

At Ignite, Microsoft announced a new agent-powered maker workspace in Power Apps.

The company says the new workspace “combine[s] what a maker needs — planning, data modeling and app building — into one intelligent, AI-powered canvas,” with the ability to generate apps simply by chatting with Copilot.

For CX leaders, the implications are practical:

• Quicker development of service workflows
• Easier creation of custom tools for agents
• More agility without waiting on development teams

Power Apps also introduces its own Model Context Protocol (MCP) Server, allowing AI agents to call an app’s capabilities. Microsoft notes that “agents will be able to call capabilities built into apps,” including retrieving records or submitting approvals.

This is a significant step toward agent-driven customer operations.

4. Agents in Microsoft Teams Become Cross-App Orchestrators

Another update includes the ability for Agents inside Microsoft Teams channels to now integrate with third-party systems such as Jira, Asana, and GitHub.

Microsoft explains that agents can pull risk information directly from these tools, surface blockers and even “schedule a meeting with the team to discuss a mitigation plan.”

While this may sound like more of a UC function on the surface, for CX organizations, particularly those running cross-functional operations (product, engineering, marketing, service), this has real value:

• Fewer context switches
• Less manual follow-up
• More coordinated communication around customer issues

Rather than agents acting as isolated helpers, they become part of team-wide workflows.

5. Microsoft 365 Copilot Expands Its Content and Collaboration Capabilities

Ignite 2025 delivered a wave of enhancements across the Microsoft 365 ecosystem that CX teams will appreciate.

Most notably, Microsoft 365 Copilot Chat can now create Pages, allowing teams to turn ideas into interactive documents.

Microsoft says the tool can “write code directly onto a page,” helping users create “interactive reports” or even turn them into PowerPoint presentations.

It’s a practical way to speed up:

• Knowledge base creation
• Internal playbooks
• Campaign plans
• Customer-facing documentation

SharePoint creation via Copilot Chat also arrives in preview, enabling users to generate structured pages and lists with prompts like “@SharePoint page agent create a page for our Q4 marketing campaign.”

For organizations where content fuels the customer experience, these additions could provide real productivity gains.

Final Thoughts

Microsoft Ignite 2025 showed a company doubling down on agentic AI; not as an abstract vision, but as a practical operating model.

While some features remain in preview, each one points toward a future where AI agents handle more of the repetitive, early-stage and cross-system work that slows down CX, sales, and service teams.

For CX leaders, this year’s Ignite offers a toolkit that stretches from autonomous sales engagement to rapid content creation and operational automation.

It’s a significant step in the evolution of Microsoft’s AI ecosystem, and one that customer-focused organizations should watch closely in the months ahead.

You can find out more about all of the major UC announcements from Ignite 2025 by checking out our sister site UC Today.

Across the customer service and experience space, the technology is being used to answer questions, guide purchases, and increasingly handle conversations once reserved for human agents.

Yet a familiar problem keeps surfacing: these systems still behave unpredictably.

They can be fluent and insightful one moment, then miss something basic the next. And when that happens, the customer experience suffers.

Salesforce’s latest releases take direct aim at this reliability gap.

Across service, commerce, and AI research, the company is seemingly placing accuracy, consistency, and predictable behavior at the center of its AI system design.

And the CRM powerhouse isn’t tiptoeing around the issue.

This is evident with the launch of eVerse – the vendor’s new simulation environment built by its AI Research department to uncover failures before they ever reach a live customer.

In discussing the motivation behind eVerse, Salesforce pointed to what it refers to as “Jagged Intelligence”, instances where AI excels at complex tasks but struggles with simple ones.

The vendor believes that this phenomenon “creates unacceptable business risk” and that eVerse “directly addresses” the issue.

A Reliability Problem Hiding in Plain Sight

Through its Agentforce platform, vendors like Salesforce have been at the forefront of expanding the capabilities and usage of AI agents in the customer service and experience space.

These tools are moving beyond basic interactions to acting autonomously in key moments of the customer journey – highlighting just how prevalent AI now is within the sector.

As Kishan Chetan, EVP and GM of Salesforce Service Cloud, puts it:

“AI agents go beyond predictions and automation; they can understand context, take action, make decisions, and adapt in real time.”

Indeed, Salesforce’s 2025 State of Service report claims that 30% of service cases are currently handled by AI, with this percentage expected to rise to 50% by 2027.

Given the sometimes volatile nature of AI, this shift has the potential to drastically increase instances of unpredictability.

In an environment where one incorrect decision or confused response can alienate a customer and damage a brand’s reputation, there is plenty of risk accompanying the reward of further automation.

Salesforce appears to be attempting to combat the unreliability of AI so that the technology can become safer while its popularity continues to soar.

Breaking AI Before Customers Do

In a nutshell, eVerse is designed to break AI before customers do.

The training environment is unforgiving. It throws noise, accents, unpredictable behavior, and messy real-world scenarios at AI models to see how they cope.

Salesforce AI COO Madhav Thattai explained how Agentforce Voice was one of the eVerse guineapigs:

“With eVerse, we were able to explore many nuances of human conversation before Agentforce Voice reached production.”

“This type of rigor is what turns breakthrough research into scalable products and dependable customer experiences.

“It’s how we’re expanding that same level of responsiveness and consistency across the full observability stack to solve our customers’ most complex needs.”

UCSF Health is one of the companies currently involved in the pilot phase of eVerse.

Collaborating with clinical experts, the Salesforce team is training AI agents to handle healthcare billing, where precision is essential.

Early tests showed agents reaching up to 88% coverage across routine and complex tasks, with reinforcement learning and clinical oversight shaping the results.

Sara Murray, MD, MAS, VP & Chief Health AI Officer at UCSF Health, summarized the goal:

“When used responsibly, we believe AI can help our teams simplify one of the most complex parts of healthcare.”

Salesforce believes that the continuous trial-and-error training loop “transforms agents from generic language models into enterprise-specialized systems ready for production deployment.”

Retail Has the Same Problem – With a Commercial Twist

Salesforce’s reliability push stretches into commerce too, where a new set of challenges is emerging.

Traffic from consumer AI channels, including upcoming integrations with ChatGPT, is rising sharply. Salesforce forecasts that during Cyber Week, intelligent agents will influence 22% of global orders.

This represents another potential risk if the AI representing your brand gives inconsistent answers.

To combat this, Salesforce has announced fresh capabilities for Agentforce Commerce.

The new features allow retailers to syndicate product data into AI channels with tight control over accuracy, pricing, and brand voice.

Self-described as the “first platform designed to give retailers full control over the entire agentic shopping journey,” Agentforce Commerce lets brands push product catalogues into AI platforms like ChatGPT while delivering personalised, agent-led journeys on their own sites to drive loyalty and higher lifetime value.

One organization currently using the tool is Pandora. The company’s Chief Digital & Technology Officer, David Walmsley, discussed the importance of being able to deliver dependable AI, stating:

“This is more than just commerce; it’s about using trusted AI and unified data to guide every customer, making them feel understood, supported, and valued.”

It is clear from Walmsley’s comments that when AI is steering purchasing decisions, that trust has the potential to become a direct revenue lever.

Fixing the Problem Long Before It Shows Up

Viewed together, Salesforce’s recent updates follow a clear logic: push reliability upstream.

The vendor is building it into the training data, the simulation environment, the risk checks, the decision-making logic, and the human oversight loops.

The logic appears to be: if reliability becomes an afterthought, AI remains a gamble; if it becomes structural, the technology scales far faster.

Salesforce’s State of Service report hints at the same dynamic. AI is already reshaping frontline roles. But adoption still hinges on trust. Service teams want tools they can rely on, not systems that feel experimental.

Security leaders echo this. While 51% report delayed rollouts due to risk concerns, Salesforce’s State of IT: Security report finds unanimous agreement that AI agents can strengthen security posture – once reliability and safety controls are in place.

In other words, the enthusiasm is there, but the confidence is catching up.

Maybe reliability will prove to be the missing piece.

A Line in the Sand for AI in CX

As AI agents step further into direct customer interactions, the industry is hitting a turning point.

These systems are no longer side tools; they’re the first point of contact in many journeys. That places reliability above convenience, above cost savings, and above speed.

Silvio Savarese, Chief AI Scientist at Salesforce, linked the research to real-world outcomes:

“Our partnership with UCSF Health demonstrates how applied science translates directly to customer value, proving that when you train agents in environments that mirror real-world complexity, they perform reliably when it matters most.”

That’s the crux of Salesforce’s message. In the agentic era, reliability must be foundational; not an afterthought.

Teams that recognize this early – and harden their AI accordingly – will be the ones who are best placed to fully maximize the potential of the technology.

The division brings together the company’s Partners, CX Customer Success & Services, Marketing, Global Business Operations, IT, and Corporate Security departments under a single organizational umbrella.

According to NiCE, the new structure is designed to enhance its operations while accelerating its AI-first approach to customer experience. By integrating technology, process, and customer-facing teams, NiCE aims to create a more seamless and responsive experience for its clients.

“NiCE continues to advance its mission to redefine customer experience through AI-orchestrated business outcomes, uniting human empathy and intelligent automation at scale,” the company said in announcing the new structure.

Arun Chandra is joining NiCE in the newly created role of Chief Operating Officer to lead the Global Customer Operations division, reporting to CEO Scott Russell. Chandra brings leadership experience from Disney, Meta, and Hewlett Packard Enterprise, where he built a track record of driving operational innovation and customer-centric growth, NiCE said. At Disney, Chandra modernized the $24 billion streaming business’s customer experience for over 195 million subscribers, using AI and automation to enhance engagement and reduce friction.

“I have a deep understanding of the significant impact NiCE delivers for leading organizations, and I’m excited to build on that foundation, scaling global operations, deepening partnerships, and ensuring every customer interaction reflects the innovation and integrity that define NiCE.”

NiCE’s new customer-focused division fits within a broader trend in which IT, security, and business operations are increasingly intertwined with customer service functions. Companies are investing in technology-driven customer experience strategies that rely on data, automation, and AI, while still emphasizing the human element in service interactions.

Supporting Integrated Customer Operations

IT and security teams are increasingly tasked with supporting customer service operations, making sure that AI tools and a patchwork of third-party apps and integrations run securely and reliably.

That requires a more integrated organizational approach, where teams that were previously siloed have to work together more closely. In turn, those teams need unified platforms and processes that allow data and insights to move across departments more freely, enabling proactive issue resolution and faster decision-making.

While few CX software vendors have explicitly launched a global customer operations division in the same way NiCE has, several are taking similar steps to integrate their customer success, service, IT, and operational functions.

For example, ServiceNow has been aligning its customer service management and front-office operations with its IT workflows, creating a more unified, AI-driven platform for service delivery and operational efficiency. Cisco recently merged its CCaaS and CPaaS teams into a single Webex Customer Experience organization, bringing together engineering, operations, and customer-facing teams with a view to accelerating innovation and streamlining AI-powered service. Meanwhile, SAP’s CX suite consolidates marketing, commerce, sales, service, and customer data with back-end systems, allowing cross-functional teams to collaborate more seamlessly.

By bringing together CX, IT, operations, and security under a single division, NiCE is positioning itself to make use of automation and AI more effectively across all touchpoints, while still preserving the human empathy central to customer interactions. The new structure should make it easier for the company to turn data and intelligence into actionable insights that drive operational efficiency and more personalized, responsive customer experiences.

Such integrated approaches could become a standard model for enterprise customer operations, as organizations increasingly blend technology, data, and human expertise to meet the demands of modern customers.

The update puts unification at the forefront. Addressing the fact that many enterprise teams have to toggle between standalone tools, Zoho aims to deliver something closer to a true operating system.

A Connected Workspace Designed for Frontline Service Teams

The most immediate impact comes from the redesigned interface. Zoho One’s new “Spaces” structure organizes tools by context, whether for personal productivity, company-wide collaboration, or functional areas like marketing, sales, or finance. The value proposition here is to reduce friction.

The Action Panel and unified Approvals take that concept further, pulling tasks, sign-offs, and action items from across the stack into a single view. Customer-facing roles, especially those that handle service escalations and sales cycles, often have to pull data from multiple apps. This approach aims to reverse that dynamic by pushing relevant information to the user instead of the other way around.

Dashboards and the new Boards framework also help consolidate operational and customer-related data. Because Boards can be assembled from Zoho’s own analytics or third-party dashboards brought in through single sign-on, customer support and sales teams can combine metrics, from ticket backlog to deal progression to customer sentiment, within one context.

Unified Integrations for Consistent CX Across Systems

Customer-facing operations typically rely on diverse systems covering ticketing, CRM, commerce platforms, payment portals, and engagement tools. Zoho has addressed this with a stronger emphasis on native integrations and an expanded model for third-party connectivity.

The unified integration panel gives administrators full visibility into Zoho-to-Zoho and Zoho-to-third-party connections, including recommendations for additional integrations.

Raju Vegesna, Chief Evangelist at Zoho, said during a media briefing that limits on integrations are typically dictated by outside vendors:

“There are limits in terms of capability and the exposure of their API… technically, as long as they support some of the standard protocols, it’s fairly straightforward.”

The introduction of a unified portal may have the most impact on customer experience operations. Instead of customers juggling multiple logins for CRM updates, support tickets, commerce orders, payments, and more, organizations can merge all their portals, including those from non-Zoho systems. For large enterprises especially, where siloed customer portals are a known pain point, this consolidation could help improve customer effort scores.

Domain verification, authentication records, and other behind-the-scenes tasks can also now be handled centrally. This includes new support for GoDaddy users, who can authorize automatic updates to DNS records, which is a useful capability for customer service and marketing teams that previously relied on IT intervention.

AI Steps Into a More Contextual Role

AI is deeply embedded in the release through Zia, Zoho’s AI assistant, which has an expanded footprint, and new intelligence hubs. Because Zoho One unifies data from more than 50 apps, Zia can take on tasks that span categories, for example, pulling HR, CRM and support information into a single query.

For example, it can help leaders understand how much time each employee spent with a particular account, Vegesna said, which requires cross-system reasoning not typically possible in isolated applications.

Zia Hubs, now promoted to a standalone application, automatically collects content such as signed contracts or recorded meetings into dedicated hubs. Users can then query that information directly. Vegesna explained:

“All the documents that you put in that hub… you can say, ‘hey, here are the same documents. Show me only the documents that auto renew within the next three months.’”

This could streamline contract renewals, customer onboarding, or issue-resolution workflows by exposing the right information without manual digging.

AI also assists in product navigation. Zia is trained on all 55+ Zoho applications, which means a user can ask how to run an Instagram campaign and be guided directly to the relevant tool, in this case, Zoho Social, and receive recommendations on how to use it, Vegesna noted.

Zia is coming into the status bar of Zoho One. Zia will be able to create and plug in widgets because the data is connected to the back end and powered by analytics. Users will be able to select from preset reports and dashboards and they are organized, whether they are CRM, HR or support related, such as a helpdesk overview, and pinned to the dashboard, Vegesna said.

“Because we have a broad suite of applications that are deeply integrated on our stack, and have the context that enables the intelligence… we are basically embedding [AI] contextually so that the user does not even know that they’re using AI here.”

Ensuring Data Sovereignty and Enterprise Control

Security and data sovereignty are becoming an increasing concern for enterprises as they pay more attention to where AI systems source and store data. Zoho made clear that its ability to operate its own full stack from infrastructure to applications enables deployment models that many competitors can’t match. As Vegesna noted:

“In sovereignty… we are doing these on-premise deployments in some countries where your data center has to be set up in that country, because we own … the entire stack … we are able to do it particularly when dealing with governments.”

The demand for national or regional control is growing, especially in markets where critical communication systems must remain within the country’s borders to comply with data privacy regulations. “They want to own some key aspects. For example, communication … I don’t want someone else to … pull the plug on my communication systems, so I want it on my data center within my country … those have come up a lot, and we are doing those deployments as well.”

Encryption and data governance were also focal points. Zoho confirmed that customers can now bring their own encryption keys and assign them at the application level. “On the security side … customers ask, ‘Can I bring in my own encryption keys and encrypt my data within Zoho?’ And now we are enabling that,” Vegesna said. “They can now select which applications can use what encryption key, and they can define encryption keys based on their specific set of applications, like their documents [and] emails.”

Zoho argues that AI governance, especially around permission systems, has been overlooked in broader industry discussions. Vegesna said:

“B2B LLMs are different from B2C LLMs, because the permission layer plays a very critical role. I think nobody can do a solid AI strategy and implementation if you do not have a directory system in there. And we have been saying it for years, and we are one of the very few vendors who do directly in Zoho, because that has the entire permissions structure in place.”

Cloud directory integrations that enable permissions are a granular level should be at the core of enterprise AI.

“If we do not have a directory system, we cannot say we can do good AI that is well protected, and you should not have access to some data that AI just memorized, because that all has to be under a firewall and the permission system.”

“We own the triple A: authentication, authorization and access control,” Vegesna added.

Together, these capabilities reinforce Zoho’s pitch to enterprises, that unified architecture and control over its infrastructure allow for tighter data governance and deployment models that meet stringent regulatory or geopolitical requirements.

The through-line across the release is the shift away from app-centric work toward context-centric work. This is a change that resonates strongly in customer-facing environments where speed, accuracy, and personalization depend on smooth access to data.

By pulling together dashboards, workflows, approvals, and AI-generated insights from across the business, Zoho One offers a way to reduce employee and customer effort. Functions that are traditionally fragmented, including billing, support, onboarding, and renewals, can be unified at the workflow and data level rather than treated as separate systems stitched together by manual processes.

For enterprises looking to consolidate their customer-facing tech stack without compromising on data control or the breadth of tools, Zoho is positioning the new release as a platform that can serve both operational needs and experience-driven outcomes.

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.