The timing matters. Shoppers expect speed and personalization in the same breath. Around 71% say they actually want AI built into the shopping journey. They’re not asking for gimmicks. They want better stock visibility, quicker service, and recommendations that actually fit. Miss those marks and loyalty drops fast.

Amazon has already shown where this is heading: robotics in its fulfilment centres have cut costs by roughly 25%, a sign that retail automation solutions can shift margins as well as customer experience.

Tech giants are moving quickly, too. Salesforce, Google, and Microsoft are building AI agents to automate frontline support and back-end operations alike. It’s the “agentification” of the enterprise – automation that doesn’t just support the business but runs through it.

Challenges Retailers Must Overcome

One of the reasons retail automation is gaining so much attention right now is that the right tools can genuinely solve real-world problems – the kind that hold brands back. Right now, retailers have a lot of issues to overcome. The systems they already have don’t connect. Processes run in silos. Customers fall through the gaps. The result is frustration on both sides of the checkout.

Automation has the potential to tackle issues like:

• Disconnected inventories: A shopper checks a website, sees an item listed as available, makes the trip, and finds nothing on the shelf. The reverse happens too: stock piling up in storerooms with no visibility online. Without automation tying together store systems, warehouses, and ecommerce data, managers are left to guess.
• Cart abandonment: More than seven out of ten online baskets are abandoned before payment, a persistent drain on digital sales. Some of that is down to clunky checkout flows. But much of it comes from poor timing: slow shipping updates, lack of payment options, or no personalized nudge to finish the order.
• Poor customer experience: Customer experience is another sore spot. Fragmented journeys cost U.S. businesses an estimated $136.8 billion a year in lost loyalty. It’s the same pattern every time: a customer starts with live chat, follows up by phone, then gets a completely different answer by email. Each handoff repeats the pain. Without retail automation solutions that unify data, every channel feels like a different company.

As Gartner warns, “limitless automation” is a myth. But the goal isn’t automating everything. It’s automating the right things, with the right guardrails, to fix broken journeys.

Retail Automation Use Cases and Benefits

The impact of retail automation shows up in the basics: how goods flow, how shelves stay full, how support teams respond. When it works, it links the back office to the customer in one thread. When it doesn’t, it becomes just another layer of friction.

The following use cases show where the biggest opportunities lie.

Supply Chain & Logistics

Retail supply chains face constant pressure. Surges in demand, shipping delays, and rising costs. The systems built years ago weren’t built for the pace of modern ecommerce. Automation is starting to bridge that gap. AI now forecasts demand spikes, reroutes deliveries, and even triggers restocks without human input. The payoff: fewer empty aisles, lower transport costs, less waste.

Analysts at NetSuite note that automation in logistics can trim lead times significantly while also cutting excess inventory. Amazon’s own network shows the effect at scale, using AI-driven workflows to manage thousands of sites, speed up decisions, and reduce overheads.

Inventory Management & Forecasting

Inventory has always been retail’s balancing act. Too much stock ties up cash and fills warehouses. Too little drives customers to competitors. The gap between online and in-store data only makes it harder.

Retail automation can close that gap. Machine learning models forecast demand more accurately, pulling signals from sales patterns, seasonality, and even local events. IoT sensors and ERP integration push updates in real time, so a store manager isn’t left guessing what’s on hand. One company, FLO, reduced lost sales by 12% just with AI-powered demand forecasting, allocation, and replenishment tools.

Elsewhere, by connecting systems and automating core workflows, ThredUp reduced manual bottlenecks and kept inventory moving efficiently through its marketplace. That meant quicker processing times, fewer errors, and a smoother experience for both sellers and buyers.

Smarter Customer Service

Customer service is often the first test of a retailer’s brand. It’s also one of the hardest to scale. Long queues, repeated questions, and inconsistent answers push customers away.

This is where retail automation has some of the clearest wins. Many firms now use AI agents to cover FAQs, returns, warranty requests, and basic order updates. That shortens queues and frees staff to focus on tougher cases.

Proactive outreach also helps cut down on cart abandonment and cancellations. At a deeper level, automation is reshaping the shopping experience itself. L’Oréal, for example, used Salesforce’s Agentforce to unify data and automate service interactions. Customers received consistent, personalised responses across every channel, turning routine contacts into relationship-building

Revenue Growth & Marketing

Automation goes beyond efficiency; it drives sales. Ecommerce automation tools are now used for predictive pricing, upselling, cross-selling, and tailored offers at scale. Customer Data Platforms bring scattered records into a single profile, enabling true personalisation. That data fuels real-time campaigns designed to anticipate customer needs and lift conversion rates.

By automating parts of its customer experience, marketing, and sales strategies, Simba Sleep generated more than £600,000 in additional monthly revenue. The company’s AI agent now does the work of 8 full-time employees, freeing human staff up for other work. The automation didn’t just cut costs. It created a direct and measurable growth impact.

Enhancing Employee Experience

Retail isn’t just about customers. Employee experience matters too. High turnover and burnout are expensive. Automating repetitive work helps keep staff engaged, while workforce scheduling tools ease pressure during peak demand.

For example, by automating key workforce processes, Lowe’s saved over $1 million in just eight months. The benefits went beyond the bottom line – supervisors reported higher satisfaction, and frontline staff were able to focus on more meaningful work.

Great Southern Bank also achieved similar results, watching attrition rates fall by 44% after building intelligent automation into workflows. This is clear evidence that automated retail tools don’t replace staff. They make jobs more rewarding by removing the least engaging parts of the day. That has a direct impact on retention.

Unlocking Business Insights

Retail runs on data. But in most organizations, that data is split. Marketing has one view. Ecommerce has another. Service teams work with something different again. By the time reports land on a desk, the moment to act has already passed.

Retail automation changes that. Automated systems connect the dots between platforms and feed AI models that can see patterns in real time. Which product lines are about to sell out? Which promotions will flop? Who looks ready to walk?

A single view of the customer makes the difference. That’s why retail automation solutions now often include Customer Data Platforms. When Vodafone brought its records together in one place, engagement rates jumped by nearly 30%, and teams were able to build more effective journeys without risking burnout.

The gains aren’t limited to revenue. Automation can also catch compliance issues, broken workflows, or supply chain weak spots before they turn into costly problems.

Best Practices for Retail Automation

The potential of retail automation is huge. But so are the risks. Without a clear plan, projects can misfire – frustrating customers, raising compliance concerns, and wasting money. The retailers that succeed tend to follow a few clear rules.

• Get the data foundation right: Automation is only as good as the information it runs on. If customer records are scattered, bots will give inconsistent answers and supply chains will make the wrong calls. That’s why many retailers are investing in Customer Data Platforms. A CDP pulls together records from marketing, sales, service, and ecommerce. One view. One source of truth. Without that, everything else is shaky.
• Set guardrails: Gartner has already warned about the danger of chasing “limitless automation”. Not every process should be automated. Not every customer interaction should be handed off to AI. The best deployments use escalation rules, monitoring, and clear ownership so nothing gets lost.
• Avoid generic automation: Customers spot it instantly. A one-size-fits-all chatbot that can’t see their order history does more harm than good. Graia has called out this problem in CX, showing that automation has to be tuned to the business and the customer journey, not just bolted on.
• Train the workforce: Automation changes jobs. It takes away repetitive tasks, but it also requires staff to know how to work with AI systems. The best companies invest in training and create “automation champions” on the front line. That reduces fear and speeds up adoption.
• Measure what matters: Metrics like call volume or handle time don’t show the true impact of automation. Smarter measures include containment quality, safe deflection, and revenue lift. Tools like Scorebuddy now track the performance of AI agents directly, adding oversight where it’s needed most.

Don’t jump in trying to automate everything. Automate carefully, with the right data, the right checks, and the right training.

The Future of Retail Automation: Growth, Loyalty, and Smarter Operations

The role of retail automation has shifted. It’s now about reshaping the sector end-to-end – supply chains, inventory, customer service, and marketing. When used well, automation and AI cut costs, trim waste, and improve both staff and customer experiences.

But there are risks too. Fragmented data, overuse of bots, and weak oversight can undermine trust faster than they deliver returns. Success depends on planning: build solid data foundations, set limits, train teams, and track outcomes that go beyond call times or ticket counts.

Automated retail is already here. The retailers that move carefully but with intent will be the ones winning the next decade, with leaner operations, more loyal customers, and stronger margins.

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.

At the Call and Contact Centre Expo 2025, the primary focus of many sessions was centered around AI, trends, and how to join the never-ending CX competition.

Fola Olafare, Senior Contact Center Delivery Manager at Transport for London, highlighted TFL’s approach to differentiate from the mainstream AI-focused contact space toward a more customer-centric one.

The event, ‘Mind The Gap: How TFL’s CX Strategy is Transforming Customer Experience’, emphasized how organizations can still function in the modern day meaningfully without turning straight to AI for results.

Olafare highlighted what he sees as the current CX trend issue:

“You’ll just see AI laced everywhere – it’s getting to the point of bringing AI for the sake of bringing AI.”

Less AI, More Human

However, with customer loyalty being a valuable currency in the CX space, the customer-centric trend has allowed TFL to thrive, having simplified their customer service approach drastically in the last decade.

By focusing less on AI integration, customer service can continue the traditional approach to drive meaningful human experiences to each individual customer.

He highlighted TFL’s current “Core ethos about listening to our customers and demonstrating that we care.”

Previously, TFL saw frequent barriers between company and customer.

“From a customer point of view it wasn’t great, we had 15 different phone numbers and 35 different emails.

“Maybe 1o, 12 years ago we didn’t have that influence.”

Today, customer’s transportation experiences are leaps and bounds ahead.

He said, “From a contact center point of view, we’ve come a long way representationally,”

“We have a really nuanced support for our visitors – allowing us to provide a dedicated care service for all our customers,

“Telephone is a great starting ground for us – now we have one phone number for customers.”

Customer’s can go to customer support to receive advice on travel planning, how to handle complaints, and discuss transportation issues within their area.

This has also included showing support for customers after negative or traumatizing transportation experiences.

“The aftercare support to the victims of life changing incidents that happen on our networks – providing them that support for a good duration.”

This approach has shown in its results, with 2024 seeing 30 million daily journeys, 9,000 buses, and over 1,400 e bikes around the city, whilst also managing 25% of London’s roads, improving overall transportation for residents and visitors.

In fact, this has prompted the London mayor to set a goal to see more people using public transport, hoping that “by 2041, 80% of customer journeys are being taken by customer transport.”

Automation is Still Key

Despite the focus on human experiences, automation continues to play a role in TFL’s customer experience, utilizing that tool through analyzing real customer experiences to provide its customer’s with a system they actually need.

He said, “We do some much from an automation point of view – we have a lot of strong algorithms working in the background to work out different anomalies.

“We’ve now ensured that intention is available for customers from a journey point of view by enhancing them with our alternative journey messages.” 

And whilst TFL does implement automation in the organization, it recognizes that setbacks will occur with this tool.

“For every automated journey we have, we acknowledge it may not work as well.”

However, in return, “You can have really great conversations for resolving that issue in a really caring way.”

Despite this approach, TFL are conscious about keeping up with customer demands and circumstances.

“We also want to make sure we’re adapting to customer circumstances, to have a really good strong set of customer values – we want to be open and transparent about what we’re doing.

“From a TFL point of view, what excited me is there is so much opportunity to make a lot of people’s lives better in an integrated way.”

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. 

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.

In its quarterly report on Wednesday, the technology company revealed several high-value investments in its AI products. 

In the earnings call, Cisco emphasized that this rapid growth in AI product adoption indicates a rising demand for secure networking. 

Customer-Centric Strategy 

Over the past year, Cisco’s quarterly results have demonstrated high levels of growth after several previous declines, and it is now reaping the benefits of its increased customer spending and investment. 

This has included various AI products and suites, as well as investments in data centers to support the demands for AI-driven workloads and cloud networking. 

However, the attention has turned towards its customers and their willingness to adopt these products into their workflows. 

Despite this growth in demand, a Cisco study revealed that only a third of companies are certain that their IT infrastructure can safely integrate their AI projects, which Cisco views as favorable for them. 

With its extensive networking portfolio, the company believes it is on track to deliver the critical infrastructure to its customer enterprises, enabling them to adapt to the AI era. 

Modernizing Customer Experience 

In response to the study, Cisco has acknowledged that many companies are still far off from where they’ve been expected to be with AI. 

Charles Robbins, CEO and Chairman at Cisco, recognized the readiness gap between planning and execution when it came to adopting AI. 

He said:

“We know many customers still have a lot of work to do to ensure they have the modern, scalable, secure networking infrastructure to support their AI goals.” 

Cisco has already begun its move toward a modernized customer experience through various upgrades and expansions, allowing for simpler large-scale AI deployments. 

This has included its global network and infrastructure upgrades, allowing Cisco to enhance its enterprise switching, routing, and Wi-Fi to conduct large-scale AI and data-intensive workloads with fast, scalable, and secure performance. 

From this, Cisco expects its enterprise customers to switch from legacy networking equipment to its newer systems, collectively spending billions as part of its multiyear, multibillion-dollar refresh opportunity. 

With global data expansion, Cisco has established numerous regional data centers worldwide, as well as a European customer-based sovereign critical infrastructure portfolio, focusing on a global scale-up with region-focused deployments. 

By supplying software and cloud-native transformation, customer enterprises can also receive automated network surveillance and deliver secure, scalable customer experiences. 

In addition, Cisco offers end-to-end security integrated into the network, supporting modernized infrastructure for reliable and capable traffic pattern management. 

Workloads with Agentic AI 

Cisco’s earnings call reported a surge in agentic AI activity, with the number of queries through agentic AI measuring at 25x higher in network traffic than chatbots. 

And demand for AI has increased with it, with Cisco expecting AI infrastructure to generate $3BN in revenue for fiscal year 2026. 

A contributing factor is the AI workloads needing the necessary models and infrastructure to process locally. To support this, Cisco announced the release of its Unified Edge last week, as part of its strategy to process AI at a speedier and secure level. 

This platform offers integration for compute, networking, and storage into one system, enabling enterprises to receive real-time predictions and decisions for secure AI management. 

Another recent release is the Cisco Data Fabric architecture, which allows for the unification and management of various machine data sources, enabling companies to create more innovative AI models, adding to Cisco’s value when it comes to technology investments. 

Cisco Webex Winter 2025

Cisco has also published its Webex Winter 2025 press release, detailing its recent updates in CX technologies. 

Some key results from the season include: AI translation capabilities now expanding to 120 languages for meeting summaries; its regional cloud infrastructure locations such as the UK, Saudi Arabia, South Africa, and the UAE; a 3D workspace designer for visual blueprints; and AI Assistant for Calling for live and post-meeting summaries. 

These help to enable higher productivity levels, improve global coverage, and drive flexible working systems, with Webex allowing customers to use meeting rooms, calls, and contact center through one platform. 

However, not all these features are available for deployment as of yet. 

In conversation with CX Today, Tim Banting, Head of Research at Techtelligence, discussed Cisco’s decision to strengthen its overall CX stack across AI, global scale, and device flexibility. 

He said, “The move aligns with current Techtelligence buying-intent data showing a 19% rise in enterprise research around UC productivity and automation, involving more than 29,000 companies actively investigating process and workflow automation in communications suites. 

“However, Cisco faces an execution challenge. Several key AI and automation capabilities remain in the “coming soon” category, creating a perception gap in a market that rewards immediacy and credibility. 

“Techtelligence data shows that buyers are rewarding vendors delivering deployable automation and measurable risk controls now – not future roadmap promises. 

He added: “For CX buyers, the practical value lies in features that are globally available and compliance-ready today. The platform consolidation trend is undeniable.  

“Cisco’s success will hinge on whether it can deliver AI responsibly, at scale, and ahead of rivals who are already reshaping perception around “secure AI collaboration.” 

Cisco Key Earnings Results

After enterprise customers’ strong demand for its AI products, Cisco has risen above estimates for the quarter. 

• Cisco’s revenue is up to $14.9BN, increasing 8% year-over-year  
• Its product orders are up 13% year-over-year, with growth across all markets and geographies 
• AI infrastructures currently stand at $1.3BN 
• Service revenue increased by approximately 2% 
• Product revenue increased by approximately 10%

Amazon Sues Perplexity for Allegedly Misusing Its AI Shopping Tool

Amazon has threatened Perplexity with legal action after its shopping tool was accused of computer fraud.

On Tuesday, the startup’s Comet AI was accused of violating Amazon’s ban on robot and data gathering.

Amazon has previously warned Perplexity about the use of the tool on its shopping site.

In the claim, Amazon accused Perplexity of misconduct against its company’s terms of service, claiming that its agentic browser, Comet AI, was being used to access customer accounts and make automated purchases on behalf of a customer, without Amazon’s knowledge.

The accusation also claims that perplexity has damaged Amazon’s customer experience by pretending to be a human consumer and accessing restricted sections of its website, threatening the trust and privacy of customers.

In a statement on Tuesday, a spokesperson for Amazon addressed the claims made against Perplexity.

They said:

“We’ve repeatedly requested that Perplexity remove Amazon from the Comet experience, particularly in light of the significantly degraded shopping and customer service experience it provides.”

Read on to find out more.

Zoom Eyes the Small Business CX Market with Bonsai Buy

Zoom has signed an agreement for the acquisition of Bonsai, an all-in-one client engagement and business management platform designed for solopreneurs and small businesses.

The deal underscores Zoom’s commitment to providing customer service features to businesses of all shapes and sizes, from enterprises to small-scale organizations.

In a nutshell, Bonsai’s solutions are built to support service professionals like designers, consultants, and architects by equipping them with an easy-to-use, unified workspace.

In doing so, it provides an accessible and affordable way for small businesses and soloprenuers to deliver a superior level of customer experience and improve customer loyalty.

In a blog discussing the acquisition, Vi Chau, General Manager of Online Business at Zoom, wrote that Bonsai “stands out in a market underserved by complex, enterprise-focused tools.

“At Zoom, we see an opportunity to simplify this effort by empowering solopreneurs to focus on growth, not administrative work.”

In practice, this means integrating Bonsai’s tools with Zoom Workplace, including products such as Meetings, Webinars, Team Chat, Zoom AI Companion, and Docs (Read more…).

Gartner Magic Quadrant for CRM Customer Engagement Center (CEC) 2025: The Rundown

Like almost every facet of the customer experience and service tech stack in recent times, the CRM Customer Engagement Center (CEC) landscape is in the midst of an AI-powered rethink.

Gartner’s Magic Quadrant for CRM Customer Engagement Center (CEC) 2025 underscores how swiftly the market has shifted from digital engagement to intelligent orchestration, with AI agents, automation frameworks, and composable platforms defining the new service stack.

While last year’s report reflected stability, 2025 marks a decisive pivot.

A fresh evaluation model, new scoring criteria, and a heavier focus on agentic AI have redrawn the map.

However, despite the changes, Salesforce was still comfortably the top of the pack, with Microsoft, ServiceNow, and Zendesk some of the major names trying to chase it down.

Read on to find out which other vendors made the latest report and what most impressed Gartner.

Phishing Campaign Targets Cloudflare Pages and Zendesk to Mimic Support Portals

A new phishing campaign is targeting customer support channels by abusing Cloudflare Pages and Zendesk, showing that even well-protected platforms can be manipulated.

Arda Büyükkaya, Cyber Threat Intelligence Analyst at EclecticIQ, has warned that threat actors have registered more than 600 *.pages[.]dev domains, using typosquatting to mimic legitimate customer support portals for popular brands.

Typosquatting is a technique in which attackers deliberately register domain names that are slight misspellings or variations of legitimate company web addresses, to trick users into thinking they are visiting the correct site. For example, a domain like zendeskcupport.pages[.]dev could be used to impersonate Zendesk’s official support portal while relying on users to overlook the subtle typo.

The phishing pages are “very likely AI generated and include an embedded live chat interface, staffed by an human operator who asks victims [their] phone number and email address under the pretext of providing technical assistance,” Büyükkaya explained in the post on X (formerly Twitter).

“The attacker then instructs victims to install a legitimate remote monitoring tool (Rescue), which grants them full remote access to the device.”

The goal appears to be stealing sensitive information and taking over accounts for financial gain (Read more…).

The move highlights how unified communications and contact center capabilities are fast becoming inseparable.

The new package combines the calling and collaboration tools of RingEX with customer engagement features such as advanced queue management and a shared SMS inbox, creating what RingCentral calls a “lightweight contact center” experience.

“Over a million users rely on RingCentral RingEX as a lightweight contact center, enabling employees to respond to customers alongside everyday work,” said Kira Makagon, President and COO of RingCentral.

“The future is customer-centric — uniting AI, unified communications, and contact center capabilities.

“With the Customer Engagement Bundle, we’re empowering every organization to deliver experiences that build loyalty, boost efficiency, and drive growth.”

The move positions RingCentral squarely in the emerging space where UCaaS, CCaaS, and even CPaaS intersect.

As Denise Lund, Research Director at IDC, noted, “RingCentral’s CE Bundle exemplifies the integrated UC-CE convergence that IDC identifies as one of the fastest-growing segments in business communications.”

That convergence, Lund added, “addresses a critical gap for organizations that need robust customer engagement capabilities without full contact center complexity.”

UCaaS and CCaaS: From Integration to Convergence

For years, vendors have promoted integrations between UC and contact center systems. But now, as RingCentral’s announcement underscores, the focus is shifting toward true convergence: a single platform for both employee and customer communications.

Microsoft made a similar move earlier this year when it confirmed the general availability of Teams Phone extensibility for the Microsoft Dynamics 365 Contact Center.

The feature allows both platforms to share the same voice infrastructure, simplifying deployments and streamlining billing.

By consolidating systems, companies like Sweden’s Sveriges Lärare – anearly adopter of Teams Phone extensibility for the Microsoft Dynamics 365 Contact Center – have reduced operational complexity and empowered agents to collaborate directly with subject matter experts.

Christopher Ehlo, Sveriges Lärare’s Tech Lead, claimed that “by consolidating our telephony on one platform with Teams Phone and Dynamics 365 Contact Center, we’re reducing complexity and improving operational efficiency.”

Microsoft itself has described such moves as “essential for modern service delivery”, arguing that the lines between CCaaS and UCaaS are “vanishing fast”.

These developments mark a shift in how businesses think about communications infrastructure.

What was once a clear division between “front office” customer service and “back office” collaboration is rapidly dissolving.

The Enterprise Perspective

William Rubio, Chief Revenue Officer at CallTower, believes this convergence of UCaaS and CCaaS is being driven as much by employee expectations as by customer demand.

Indeed, speaking in an exclusive interview with CX Today from earlier this year, he said:

“There was always a big real focus on the customer side of the house. And I think ever since the pandemic, it’s changed, and now it’s really about what can we do to solve the business outcomes of our customers.

“What are the tools that we’re able to go ahead and give to our employees… to make it a win-win solution for both?”

Rubio added that the integration between UCaaS and CCaaS is “very critical” because contact center agents are increasingly pulling in colleagues from outside the contact center.

This concept, often referred to as swarming, has been a key selling point for Microsoft’s Dynamics-Teams integration and now finds a counterpart in RingCentral’s bundled approach.

Both vendors are responding to the same enterprise need: a seamless way for employees to collaborate across roles and deliver consistent customer outcomes, regardless of channel.

A Convergence Milestone

The RingCentral CE Bundle may not represent a full contact center overhaul, and in many ways, that’s precisely the point.

Many businesses don’t need the complexity of enterprise-grade CCaaS, but they do need to ensure customer conversations aren’t missed.

In that sense, RingCentral’s latest release serves a growing middle ground: organizations looking for customer engagement capabilities embedded directly within their everyday communications environment.

When taken alongside Microsoft’s moves and the broader market sentiment echoed by CallTower’s Rubio, it appears that the long-discussed convergence of UCaaS and CCaaS is no longer just a theory; it’s happening, and it’s reshaping how enterprises design their customer and employee experience strategies.

The deal underscores Zoom’s commitment to providing customer service features to businesses of all shapes and sizes, from enterprises to small-scale organizations.

In a nutshell, Bonsai’s solutions are built to support service professionals like designers, consultants, and architects by equipping them with an easy-to-use, unified workspace.

In doing so, it provides an accessible and affordable way for small businesses and soloprenuers to deliver a superior level of customer experience and improve customer loyalty.

In a blog discussing the acquisition, Vi Chau, General Manager of Online Business at Zoom, wrote that Bonsai “stands out in a market underserved by complex, enterprise-focused tools.

“Running a small business today means juggling client work, communication, and finances across multiple tools.

“At Zoom, we see an opportunity to simplify this effort by empowering solopreneurs to focus on growth, not administrative work.”

In practice, this means integrating Bonsai’s tools with Zoom Workplace, including products such as Meetings, Webinars, Team Chat, Zoom AI Companion, and Docs.

For example, integrating Bonsai with Zoom AI Companion could automate repetitive administrative work – from scheduling follow-ups to generating proposals – while maintaining a consistent tone of voice with clients.

Bonsai CEO Redon Gjika highlighted this potential in a post on LinkedIn, noting that Bonsai’s future will be “augmented by Zoom’s AI-first Workplace products.”

The move mirrors how other major vendors, including Microsoft and Salesforce, are weaving AI into both collaboration and customer engagement layers.

For small firms, this could mean delivering the kind of friction-free, personalized experiences once reserved for enterprise-grade platforms, without the complexity or cost that often comes with them.

Zoom’s CX Ambition

The acquisition reflects a growing industry trend: the convergence of collaboration, productivity, and customer experience tools.

By incorporating Bonsai’s client-management features, Zoom moves closer to offering a unified environment that helps small businesses handle both internal communication and external client interactions.

Indeed, Chau wrote that “Zoom and Bonsai will support small business owners and solopreneurs from the first client contact to final payment.”

That first-to-final phrasing speaks to an expanded customer experience scope.

Zoom is aiming to support relationship management, service delivery, and payment – effectively covering the full client lifecycle.

A Milestone for Bonsai

Founded in 2015, Bonsai has carved out a loyal following among independent professionals and service-based microbusinesses.

In discussing the agreement, Gjika described the deal as the culmination of a decade-long mission:

“This moment marks a major milestone in a journey that began 10 years ago with a clear mission: empowering solopreneurs and small businesses to run and grow their businesses with confidence.”

He added: “Joining Zoom allows us to expand what’s possible for our users, combining Bonsai’s deep focus on client and business management with Zoom’s resources, technology and AI leadership.”

Gjika confirmed that Bonsai will “continue to operate as a standalone platform under its own brand,” with its capabilities gradually integrated into Zoom’s AI-first ecosystem.

The CX View

For CX professionals, the significance of this deal lies less in the transaction itself and more in what it represents: the steady blurring of boundaries between collaboration and customer experience technology.

Zoom’s acquisition of Bonsai highlights how the next generation of CX enablement will be native to the tools businesses already use every day.

As the transaction is expected to close by the end of 2025, it will be interesting to see how Zoom can translate Bonsai’s small-business focus into measurable CX value.

If successful, the move could allow Zoom to dominate the small business and solopreneur market.

More News From Zoom

Last month, Zoom confirmed that Oracle will adopt its contact center solution to support global customer service operations.

The 15,000-seat CCaaS agreement marks Zoom’s largest contact center deployment to date, bringing Zoom CX to Oracle’s worldwide service teams.

First hinted at in February as a record-breaking deal with an unnamed Fortune 100 company, the partnership has now been officially identified as Oracle.

The announcement also extends the collaboration between the two firms, with Zoom CX now available on Oracle Cloud Infrastructure (OCI).

Elsewhere, back in August, Zoom revealed the enhancement of Zoom Phone by integrating its Virtual Agent, enabling businesses to route callers directly to the right department without manual transfers.

This new “24/7 AI receptionist” can interact with customers, understand their intent, process inputs, and intelligently direct them to the appropriate team, reducing the need for agent intervention and streamlining the customer journey.

Last week, the enterprise software company released its Q3 earnings report, revealing that its stock price had declined by 1.51% in aftermarket trading. 

However, despite the poor overall performance, the vendor did report some impressive CX initiatives and outcomes.

Most notably, the company demonstrated its strategy for AI in customer experience by making it a core enabler of its CX strategy, with AI now at the forefront of its customer portfolio vision. 

In fact, Christian Klein, CEO of SAP, explained how this new focus could impact the company’s bottom line, stating that “AI will be the key enabler for accelerating double-digit total revenue growth through 2027. 

No apps, no data, no AI. Only the combination of LLMs with business processes and contextual data results in high-value AI use cases. 

This significant increase in AI adoption has driven strong outcomes for SAP, including reduced friction in customer engagement and decision-making, increased responsiveness, and improved interactions, as well as smooth and individualized customer experiences. 

And by applying their AI-integrated self-service options, over 82% of customer issues have been supported via self-service. 

This increase in AI adoption can be traced to its end users applying SAP Business AI to their systems at higher rates, whilst also seeing positive results. 

For example, engineering and technology company, Bosch, has reportedly saved 2,500 hours in customer service each year when using SAP’s services agent. 

This and other striking results have led SAP to expect to sign RISE deals early in Q4 rather than 2026 as originally planned. 

SAP has also announced its decision to implement and divide AI agents into specific areas and functions through their Joule AI Copilot for Q4, to increase team productivity across all company areas, whilst targeting each individually. 

Regarding its integration strategy, SAP has continued to strengthen its products and services, implementing its Business Data Cloud (BCD).

Integrated features have included: a Shopping Agent that provides personalized product recommendations, Contact and Individual Customer Duplicate Checks to monitor data accuracy, Business Information Extraction that extracts product information from case descriptions, Microsoft Ads Integration to personalize ad experiences for Microsoft search engines, and an AI-assisted promotion creation that recommends effective actions to launch promotions. 

Furthermore, the company has made clear intentions to push for more accessible and adaptable cloud and AI technologies, which could result in expanding its customer base to smaller enterprises. 

During the call, SAP highlighted how its strategy is to position the company as a key enabler of enterprise transformation, to ensure its tools are straightforward to use and apply for highly regulated customer environments. 

This includes an entire cloud portfolio encompassing SAP cloud solutions, Business Technology Platform (BTP), BDC, and AI, to be deployed collectively in a customer data center. 

This portfolio offers high-quality levels of data, operational, technical, and legal sovereignty, keeping in line with SAP’s customer interest. 

SAP also remains committed to provide software and cloud solutions with its strong cloud infrastructure partners.