Today’s consumers expect every interaction with a business to be convenient, impactful, and tailored to their needs. A customer data platform goes beyond the basics of a standard “Customer Relationship Management” tool to help businesses build comprehensive customer profiles they can use to personalize every interaction.

With these tools, companies can take a unique, data-driven approach to optimize every stage of the customer journey, increasing loyalty, retention, and conversions. Here’s why you should be investing in a CDP to turbocharge your customer experience strategy this year.

1.    More Comprehensive, Unified Customer Profiles

CDPs don’t just “store” data about your customers. These tools collect and combine information from countless different environments, unifying it into in-depth customer profiles (or single customer views). That’s crucial when customer journeys are becoming more complex and multifaceted.

Companies can’t rely on analyzing just one or two customer interactions and touchpoints to get a complete view of their target audience anymore. They must bridge the gaps between hundreds of “data footprints” left across numerous applications. CDP solutions wrangle all the data you need to truly understand your customers, their needs, pain points, and even areas of “friction” in their journey.

This leads to the creation of profiles that give you a more comprehensive view of customer behavior, thoughts, feelings, and actions. With a CDP, you can see everything that impacts your customers’ experience with your brand, from the point when they first encounter your company to the stage when they renew subscriptions or make additional purchases.

2.    Customer Data Platforms Break Down Data Silos

The responsibility to deliver great customer experiences doesn’t lie only with traditional contact center agents anymore. For companies to compete in an experience-driven landscape, they must unify every customer-facing employee with the same data and insights.

Everyone, from traditional agents to “informal contact center employees”, like sales teams and product developers, must be on the same page. Unfortunately, without customer data platforms, it’s easy for data silos to emerge. One team might have information on a customer’s purchasing history, while another knows about their previous issues and support requests.

When all of that data is fragmented, it’s difficult for teams to collaborate on delivering a consistent user experience. Plus, it’s much harder to understand the customer journey fully. CDPs bring teams and data together, enhancing collaboration and customer service decisions.

3.    Unlock Valuable Insights for Growth

The only way to deliver the highly personalized experiences 71% of customers say they expect from brands today, is to gather as much data as you can about your audience. Unfortunately, collecting data today is much more complicated than it seems. Google is terminating third-party cookies that marketers previously relied on to understand customer journeys.

Additionally, buyers are becoming more discerning about the type of information they share. Customer Data Platforms help companies to overcome data shortages. They ensure you can collect larger volumes of the data your customers willingly share through different channels and platforms.

This means you can unify more “first-party” data, to adhere to evolving privacy laws, and you can maintain more control over that data too (which improves the accuracy of your insights). On top of that, you can use the data you collect to develop more in-depth insights. For instance, many CDP solutions allow companies to use their historical data for “predictive analytics” tasks, allowing them to predict changes in behavior, buyer trends, and preferences in advance.

4.    Customer Data Platforms Improve CX

The biggest benefit of investing in customer data platforms is that they actively improve the customer experience. Your customers want to feel like you truly understand them and are ready to put their needs first and deliver a consistent experience across every channel.

CDP technology helps companies to enhance the customer experience in various ways. It ensures your team can:

• Personalize interactions: With access to in-depth customer profiles and insights into previous customer behaviors, it’s much easier for employees to personalize customer interactions. They can triage support requests based on customer concerns and preferences, suggest relevant products to buyers based on previous purchases, and even share relevant content with customers based on their interests.
• Enhance omnichannel interactions: When customer data lives in multiple places, it’s hard for sales, service, and marketing teams to deliver a consistent experience. Alternatively, if everyone on your team has access to the same data when they interact with customers on different channels or create content for different platforms, this leads to a higher level of consistency.
• Accelerate problem solving: When support agents can instantly access everything they need to know about a customer, they can solve problems much faster. CDP platforms can help accelerate resolution rates in the contact center. Some tools even have AI solutions to generate “custom” responses to customer concerns in seconds.

5.    Improve Data Privacy and Compliance

Companies need customer data to deliver personalized experiences. Unfortunately, the more data they collect (particularly across different channels), the more they expose themselves to security and compliance issues. It’s much harder to track sensitive data when distributed across multiple apps and tools.

Customer data platforms ensure you can access a secure, central location for housing data from various sources. This means you only have one environment to monitor for signs of threats and risks (rather than dozens). Plus, it ensures that whenever a customer asks for their information to be “removed” from a system, you can easily find and eliminate that data.

Most CDP platforms have robust data protection tools, such as end-to-end encryption options, multi-factor authentication, and protected data vaults. These can all help to protect you from breaches, damage to your reputation, and regulatory fines.

6.    Customer Data Platforms Can Boost Revenue

Customer Data Platforms allow companies to use the data they gather about their customers more effectively and thoughtfully. When you understand everything there is to know about your audience, it’s much easier to create the personalized experiences that McKinsey says can boost revenues by up to 15%. The more personalized your interactions with customers are, the more likely you will earn their loyalty and trust.

Plus, you can discover new ways to reduce churn and increase conversions by understanding the customer journey and the triggers that influence buying behavior. You’ll be able to identify which factors might cause a customer to abandon your business (like long wait times for service). Plus, you can use AI to detect opportunities to upsell and cross-sell customers at different times.

You can even leverage AI tools to proactively reach customers with offers, deals, and product suggestions relevant to their needs, further increasing conversion rates. This means customer data platforms give you new opportunities to increase profits, and retention.

7.    Increase Efficiency and Productivity

Finally, customer data platforms can significantly improve efficiency and productivity. CDPs can automatically import data from your contact center, CRM, survey tools, and more. This reduces the repetitive “data entry” processes your team needs to commit to.

Plus, when employees only have to use one platform to access all the information they need for marketing, sales, and customer service, they spend less time jumping between tools. This means staff members can complete all kinds of tasks much faster and more efficiently.

Thanks to AI, CDPs will become more advanced, giving employees even more ways to save time and energy. For instance, tools already exist that can instantly transcribe and summarize conversations in the contact center, making it easier to update profiles in real-time.

Discover the Benefits of Customer Data Platforms

Investing in customer data platforms isn’t just a good way of making managing customer data easier for your company. These platforms give you the tools to design stronger customer journeys and build deeper customer relationships.

Through in-depth insights and unified views of your customer’s journey, CDPs can empower you to personalize, optimize, and enhance every interaction with a customer. This leads to greater customer lifetime value, higher revenue, increased retention, and better workplace efficiency.

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

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

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

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

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

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

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

Measurable Customer Data Platform Benefits and ROI

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

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

The pattern repeats across industries.

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

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

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

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

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

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

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

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

Customer Data Platform Benefits for Compliance, Security and Trust

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

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

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

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

Improved CX: Personalization and Omnichannel

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

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

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

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

CDP Benefits for Employees and Service Teams

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

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

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

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

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

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

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

The Customer Data Platform Benefits Enterprises Can’t Overlook

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

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

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

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

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

As governments and enterprises deepen their reliance on cloud and AI technologies, control over where data is stored and how it is processed has become central to maintaining operational resilience and regulatory compliance, and most importantly, customer trust.

More than 80 percent of business leaders cite data sovereignty as a strategic business priority, according to research by German analyst firm BARC.

“We have to get a lot better at understanding that data is money, and we need to put the security that we’ve had in place around money for 1,000 years around data,” online privacy expert Ron Zayas, CEO of Ironwall by Incogni, told CX Today in an interview.

Companies are feeding their data to AI engines to train their models, but regulations like the EU Data Act, which creates rules for data sharing and access—not to mention growing cybersecurity threats—require them to tread carefully. As Zayas put it:

“We need to understand that the same way you wouldn’t let your employees interact with networks without a firewall, you can’t let companies interact with AI without having some type of firewall in between and understanding what data you can share.”

Recent moves by European and global technology leaders indicate that they are responding to accelerating demand for a sovereignty-driven approach to innovation.

The Rise of Europe-Built Cloud and CX Solutions

Odigo, a European CCaaS and CXaaS provider, recently acquired Akio, a French software vendor specialising in AI-powered CCaaS solutions for SMEs and mid-market firms. The merger brings together Odigo’s enterprise-scale CX offering with Akio’s capabilities in AI, voice of the customer analytics, and reputation management.

But beyond expanding product portfolios, the acquisition represents a strategic move to consolidate European technological capabilities and reduce dependence on non-European cloud providers. (Aside from data sovereignty that push is becoming more significant given recent cloud service outages.)

As Odigo stated in announcing the deal:

“[T]he merger of two complementary French vendors with a strong presence across Europe reinforces Odigo’s ambition to create a competitive European alternative to the American firms in the sector. This approach comes at a time when European companies are placing greater focus on data sovereignty and control over their technological environments.

Patrick Giudicelli, Founder and President of Akio, added: “Joining Odigo means joining a French company that shares our values of customer proximity and sovereignty.”

The newly combined company offers a customer engagement ecosystem designed and hosted within Europe, where data control and regulatory compliance are built into the architecture.

Global Platforms Are Localizing Data and AI Operations

The big tech players are also evolving their approaches to sovereignty. Last week, enterprise AI platform Workday announced the rollout of its Workday EU Sovereign Cloud in 2026, keeping its European customers’ data local and secure.

All operations, including AI processing, data center access, support, and maintenance, ensure customer data is managed by EU-based personnel and never leaves the region.

“Workday understands how quickly evolving data sovereignty requirements can make it difficult for organizations to keep pace,” Gerrit Kazmaier, President, Product and Technology at Workday, said in the announcement. “Workday EU Sovereign Cloud gives our customers the freedom to innovate and grow confidently—helping them harness the power of AI while knowing their data remains protected and compliant.”

EU Sovereign Cloud is built on AWS infrastructure and spans multiple, geographically separated data centers to provide redundancy for key systems. Hardware protections prevent unauthorized access, and end-to-end encryption safeguards data whether it is in use, in transit, or in storage. An EU advisory board provides oversight to strengthen transparency and adherence to European sovereignty and security standards, Workday said.

The vendor plans to extend the offering to other regions down the line, but there’s no surprise that it’s starting with Europe first, given the region’s strict data rules.

Tech giant Microsoft has added a new set of capabilities to its Sovereign Public Cloud and Sovereign Private Cloud offerings that build on its digital sovereignty controls to deliver AI and cloud services strengthened by its ecosystem of specialized in-country partners.

The update includes end-to-end AI data processing within the European Union’s Data Boundary, the general availability of Microsoft 365 Local, and localized versions of its Copilot AI assistant in four countries by the end of the year, with 11 more to follow in 2026. That ensures Copilot interactions are typically processed in data centers located within a nation’s borders, to give customers greater control over where their data goes.

Microsoft has also extended its Sovereign Landing Zones for Azure and introduced new infrastructure capabilities, such as support for external SAN storage and the latest NVIDIA GPUs, to help enhance the performance of local deployments. The company is expanding its ecosystem of regional experts through a Digital Sovereignty specialization.

Microsoft acknowledged that organizations in Europe and other jurisdictions face a complex slate of regulatory mandates, as well as heightened expectations for resilience. As Douglas Phillips, President and Chief Technology Officer, Microsoft Specialized Clouds, stated in the update:

“Sovereignty has become a core requirement for governments, public institutions, and enterprises seeking to harness the full power of the cloud while retaining control over their data and operations.”

The conversation around data sovereignty has also been amplified by Zoho, which raised the issue in releasing its latest Zoho One upgrade.

The vendor highlighted the value of controlling the full technology stack and emphasized that operating its own infrastructure through to applications allows it to offer deployment models that give customers the control they need to meet regulations and provide transparency to their end users.

“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,” Raju Vegesna, Chief Evangelist at Zoho, said during a media briefing.

This approach allows organizations to maintain national or regional control over critical communication systems, an increasingly common requirement for enterprises that need to guarantee uninterrupted access to essential services.

These initiatives reflect a broader market realignment and a recognition that sovereignty does not need to be a constraint on innovation but can be a selling point for vendors. European enterprises increasingly expect cloud and AI providers to deliver verifiable assurances of data control and jurisdictional compliance.

As regulatory demands tighten and put more pressure on enterprises, from the EU Data Act to AI rules and sector-specific cybersecurity requirements, cloud providers that can offer data sovereignty by design are likely to gain a competitive edge.

In this exclusive interview, we sit down with Martin Taylor, deputy CEO and co-founder of Content Guru, to explore how CX leaders can successfully navigate the challenges of data ownership while embracing the transformational potential of AI and automation. 

Watch the Full Interview on Youtube 

The Data Explosion: From Calls to Connected Everything 

The scale of data generation in modern contact centers is staggering. “We’re creating billions of records a year just as Content Guru, as is everybody else,” Taylor explains in the interview. “So you’ve got increasingly information not just from calls anymore but from all the digital channels.” 

But it’s the emergence of what Taylor calls the “digital customer” that’s truly transforming the landscape. With predictions of 39 billion Internet of Things devices by 2030, each representing a human in the eyes of regulators, the volume and variety of personal data flowing through CX environments is exploding exponentially. 

” The UK Information Commissioner’s Office considers data generated by IoT devices  – be it a movement or somebody’s temperature detected by a smart health device or a smart fridge  reporting it is  empty – as a piece of personal data,” Taylor notes. 

The Jurisdiction Maze: Where Geography Meets Governance 

One of the most complex challenges facing global organizations is navigating the intersection of geography and regulation. As Taylor explains, “Data is being produced at large volume all over the world, every day, every second. So how that is generated and the rules under which it is being generated vary by geography and by market segment.” 

The implications go far beyond GDPR. While the regulation establishes that “the data subject is ultimately the owner of the data,” the practical responsibilities for processors and vendors create a complex web of obligations that vary by jurisdiction and sector. 

“The EU want it to take place within the EU. The UK want it to take place within the UK, the US in the US,” Taylor explains. “And then if you go to the actual sectors themselves like medical or financial, they’ve got a load of rules of their own and those are done per country as well.” 

Breaking Down Silos: The New Collaborative Imperative 

The complexity of modern data governance is forcing unprecedented collaboration between traditionally separate functions. Taylor shares a real-time example from his own organization: “An example from here today is about something that’s come to my desk  about live sentiment analysis and its legality within an EU AI Act context.” 

This seemingly straightforward CX enhancement required input from legal, product, and information security teams – a pattern that’s becoming the norm rather than the exception. “Those sorts of conversations are happening throughout all levels of the value chain from the provider of a service right through to the vendor,” Taylor observes. 

The Death of “Public Cloud” Assumptions 

Perhaps one of the most significant shifts in thinking has been the abandonment of the idea that being “in the cloud” absolves organizations of data responsibility. 

“I think we’ve seen the death of this idea of there being such a thing as a public cloud,” Taylor states emphatically. “Everyone can see that clouds belong to organizations now and that they reside in specific jurisdictions.” 

The AWS outage in Virginia that affected organizations worldwide serves as a stark reminder of this reality. Many affected companies didn’t even know they had connections to that specific location, highlighting the importance of understanding not just whose cloud you’re using, but where it physically resides and under what jurisdictions it operates. 

Balancing Innovation with Responsibility 

As organizations rush to embrace AI and automation, the challenge becomes maintaining innovation velocity while ensuring responsible data handling. Taylor uses an oil refinery analogy to explain this balance: “I think of raw data as like crude oil and then the refining process, fractional distillation. You’re looking now for that kind of high quality racing fuel  that we use to feed the AI.” 

Not every implementation needs to become more complex, but those involving AI require higher-quality data and more sophisticated governance. “In some cases, it’s AI, it needs that richer fuel. You can’t feed it the heating oil, because it won’t work,” Taylor explains. 

Looking Ahead: Preparing for 2026 and Beyond 

As we look toward the year ahead, Taylor predicts continued growth in both opportunity and complexity. “We’ve all heard  a lot about agentic AI  during 2025. I think 2026 is when it starts to get applied,” he notes, while emphasizing that this won’t mean wholesale replacement of human agents. 

Instead, organizations should prepare for “more data, more automation, and that means more data handling challenges.” This will require: 

• Enhanced Security Postures: Moving beyond perimeter defense to comprehensive data protection throughout its lifecycle 

• Geographic Strategy: Making deliberate choices about data processing locations based on customer needs and regulatory requirements 

• Vendor Due Diligence: Evaluating partners not just on technical capabilities but on jurisdictional alignment and compliance frameworks 

The Trust Dividend 

Ultimately, the organizations that succeed in this complex landscape will be those that can demonstrate they’re worthy stewards of customer data. As Taylor concludes, “There’s going to be a lot more scrutiny of how all of this wonderful new processing is going to happen.” 

The complexity brings opportunity for those willing to invest in getting it right. By building transparent, responsible data governance practices, organizations can turn compliance obligations into competitive advantages – earning customer trust while enabling innovation. 

The question isn’t just who owns your customer data – it’s whether you’re prepared to prove you deserve that ownership. 

Continue the Conversation 

For more insights on navigating these challenges, visit contentguru.com 

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.

Speakers pointed to the widening gap between aspiration and execution, especially as AI exerts increasing pressure to demonstrate innovation.

As Natalie Higgins, Solutions Sales Executive at NiCE put it:

“There’s an overload of data and a very short amount of time… frontline team managers, supervisors, executives are spending hours trying to mix all of this information together, but by the time they’ve done that analysis the opportunity has passed.”

The manual approach of the past no longer matches the pace of the environment. “The speed to deliver has changed,” Higgins said, “Using the manual, time consuming process does not make it easy for you to drive continuous optimization.”

Too Much Data, Too Little Clarity

Speakers acknowledged a repeating cycle. Enterprises face the same issues year after year but struggle to move forward. As one speaker put it, “Even though we’ve had the same challenges and outcomes for the last 10 plus years, organizations are stuck,”

“And why is that? Because there’s too much data that we don’t make enough sense of.”

Describing the challenge as “super hard”, Higgins noted that “demands keep increasing and the challenges are rising… the speed to deliver has changed, and that’s what makes it difficult.”

In the rush to respond quickly, teams confront a wall of questions: “Where is my data? What data do I have? And how on earth do I go about it for any particular solution?” Higgins said.

The issue is not the lack of data but the lack of time, capability, and coherence to make it usable.

“There is a massive disconnect between the strategic direction that a business wants a company to go in and actually, how do you get to that insight?” said Andrew Tucker, Solution Engineer at NiCE.

“You know that the data exists for you to be able to make the decisions and roadmap these initiatives.”

Data silos make it difficult to move with agility. “There is a massive time lag between ‘I want to achieve a certain thing,’ and ‘here is a roadmap for how you achieve that,’” Tucker added.

To make matters worse, “we’re layering on an extra level of complexity… caused by every single vendor out there… pushing the AI narrative.”

Data Connection, Not Just Collection

When it comes to data management, teams often lack the ability to translate it into meaningful action. “How do we make a data-driven decision… to be able to influence that?” Tucker asked, describing organizations that spend “weeks and months worth of work… to say what is happening, why it’s happening, and how do I forecast outcomes?”

Building bigger datasets won’t solve the problem. What matters is linking information in a way that reveals what’s really happening.

“This isn’t about data collection. This is about data connection,” Higgins said.

There is much debate in the industry about the level of data organization needed to be able to roll out AI-based applications.

Kim Baker, Head of Operational Support Services at UK Housing Association L&Q warned: “There’s no point launching AI if your data is not right in the first place, because where’s it going to look to answer these questions?”

When enterprises can get a handle on their data, they can draw out actionable insights, and AI can be a tool to help manage and extract data, making it AI-ready.

“Data is becoming more readily available. It’s more insightful. We can make better data driven decisions as organizations,” said Chris Rainsforth, Director of Learning and Innovation at The Forum.

“Some people haven’t caught up with that data yet and are still sitting back in that old way of thinking. That change will continue, and it’ll continue to drive us.

Marco Ndrecaj, Director of Customer Experience Management at Shared Services Connected, described large-scale operations facing overwhelming customer segments and datasets: “You’re like, oh my god, what am I looking at first? And I think that’s where the strength of AI comes to play.”

“Let AI take care of the data, take unstructured data, the structured data, and then turn it into insight. Once that’s done… let the human with empathy and with care to take it from there.”

As the conversations made clear, it’s imperative that enterprises turn data “overload into clarity,” and strike the right balance between automation and human judgement.

Sales and marketing departments have entered a new era. One defined by rising customer expectations, fierce digital competition, and intense pressure on revenue performance.  

As growth slows and investor scrutiny increases, commercial leaders must deliver more profitable and customer-centric outcomes. Technology now sits at the heart of that mission. 

Long gone are the days of the salesperson with only charm in their utility belt. Modern sales teams are harnessing digital tools to personalize their message, deeply understand their target buyers, and streamline their own workflows. 

When it comes to marketing, the modern buyer wants more than catchy slogans and tech demos. More independent than ever, buyers respond to marketers who can provide real data and relevant content. 

This guide explores the capabilities, considerations, and opportunities within the evolving sales & marketing technology landscape. Its goal is to equip leaders with clarity, structure, and direction. To help them find the right tools to keep up – or dominate – in a competitive enterprise landscape. 

This comprehensive guide will help you understand: 

• What is Sales & Marketing Technology?
• The Key Trends Defining This Sector 
• The Different Categories Within Sales & Marketing Tech 
• What is in the Sales & Marketing Tech Stack?
• Why Enterprises are Struggling with New Tech Adoption
• Vendor Selection: How Do I Do It? 
• 2030 and Beyond: The Future Trends Defining Sales & Marketing 
• Where Do I Go to Find Out More? 

Sales & Marketing Technology, Explained: The Engine Behind Modern Growth

Sales and Marketing Technology refers to a connected ecosystem of tools and platforms. Their aim is to help organizations attract, engage, convert, and retain customers across the full buyer journey. 

Its purpose is to unite data, digital channels, and revenue teams so businesses can strengthen customer lifetime value.  

In today’s competitive climate, technology has become the backbone of modern commercial strategy.  

The New Rules of Revenue: Trends Reshaping Sales & Marketing

Analysts have identified three key areas where sales & marketing leaders are looking to improve – driving interest in new technology:

“CSOs must balance revenue generation with operational efficiency as investor demands rise.” – Gartner

 

“Leaders must prioritize improving revenue processes and customer-centric strategies.” – Forrester  

 

“The 2025 trend to watch for is the Personalization Renaissance.” – Mintel  

In other words, three capabilities have now become competitive differentiators. Better revenue generation, better personalization, and better processes among sales and marketing teams.  

Forward-thinking enterprises have responded to these challenges in a similar way – harnessing artificial intelligence. Here are three recent case studies where these areas were addressed with new AI products. 

• Better revenue generation:
  • PWC identified one key differentiator enabling some marketing teams to deliver nearly 80% more shareholder value than competitors. Their trick? Harnessing and investing in AI.
  • “Used narrowly, AI can make marketing less expensive – faster content, smaller budgets, leaner teams. Used strategically, it can make marketing indispensable – unlocking new growth, higher profitability, greater enterprise value”, it concluded.
  • Top performing marketing teams were found to regularly invest in new AI-powered capabilities. This in turn generates revenue, and funds marketing teams to invest in more tools – creating a cycle of enterprise success. 

• Better personalization:
  • A European telecom company found that customers receiving personalized messages took action 10 percent more than those who received generic advertising materials.
  • According to a 2025 McKinsey report, the company used GenAI to personalize messaging based on age, gender, and data usage.
  • McKinsey reported that it has “seen some marketers deploy gen AI to personalize content development 50 times faster than a more manual approach”. 

• Better processes:
  • Enterprise IT platform Workday saw 3,500% ROI after adopting an automation solution for client contracts. 
  • By connecting data across platforms, the Workday team saved hundreds of thousands of hours in its global projects. 

The Four Categories of the Sales & Marketing Technology Landscape

Whether you’re an inbound marketing expert, a sales team leader, or a CIO, you have an important role to play in harnessing and optimizing these technologies.  

The team at CX Today have distilled this wide-range of products into 4 core categories. 

1. Building Awareness (Acquisition)
   Tools that help organizations attract attention, generate demand, and capture leads through content, campaigns, and data-driven targeting.
2. Sales Enablement (Closing Deals)
   Platforms that empower sales teams with insights, automation, messaging, and training to shorten sales cycles and increase conversion.
3. Retaining Customers (Client Success)
   Technology that strengthens onboarding, engagement, renewal, and advocacy – protecting recurring revenue and reducing opportunities for churn. 
4. Omnichannel Connection (Linking Everything Together)
   Integration and automation technologies that unify data to deliver consistent experiences end-to-end. 

Your Tech Arsenal: Understanding the Tools That Fuel Revenue

Vendors are looking to support a broad spectrum of job titles within sales & marketing, with an aim to automate, optimize, and manage workloads. With the four categories as a dividing structure, here are some of the typical solutions that are found in the modern sales & marketing tech stack: 

Building Awareness 

This is the front door of the enterprise growth engine. Awareness tools help brands capture attention, generate qualified leads, and convert insights into pipeline opportunities.  

• Social media and content sharing: These platforms look to generate leads through inbound marketing where interested readers are prompted to engage further with the brand. This is particularly valuable for industries that rely on thought-leadership to grow brand awareness, such as professional & business services (consulting, legal, accounting). 

• Lead capture: This can include strategic forms where brands can gather intent data and contact details to set priority accounts for further marketing. It may also include web deanonymization, where brands can reach out to visitors to its site for sourcing potential leads. 

• Smart webpages & content journeys: Modern customers want more independence and feel more confident doing their own research. These platforms can help personalize and enhance how customers reach the decision stage, providing relevant content without being overbearing. 

• Related vendors: HubSpot, Hootsuite, 6sense, Uberflip 

Sales Enablement 

Once awareness is established, sales enablement technology equips revenue teams to engage prospects intelligently and close business deals efficiently. This leads to shorter sales cycles and higher conversation rates. 

• CRM systems: A strategic approach to converting sales relies on a centralized database which highlights opportunities, past interactions – in sync with the awareness-building marketing teams. 

• Smarter sales pitches: Salespeople are in a stronger position to increase conversions when they have personalised decks, playbooks, and pitches. These solutions help manage and track these sales content pieces. 

• Training and Coaching: These solutions put salespeople in a meeting with AI avatars, letting them practice their pitch in a risk-free environment. And after a genuine sales meeting, they can analyse transcripts to find areas for improvement. 

• Related vendors: Highspot, Seismic, Showell, Microsoft Dynamics 365 

Retaining Customers 

Retention and expansion are now as critical as acquisition. Customer success technology ensures that value delivery continues beyond the sale, and helps Chief Revenue Officers to better predict financial forecasts. 

• Customer Success Platforms: With data analytics and dashboards, these solutions can help client teams to understand the health of the accounts they manage. From there, they can upsell promising accounts or prevent churn. 

• Product Usage Analytics: One of the core ways to retaining customers is to ensure their onboarding and usage is going smoothly. These tools track this information and enhance the work of support teams who address problems. 

• Post-purchase communication tools: Once customers are onboarded, client teams can use a lifecycle communication tool to keep customers engaged and prime them for upsell pitches. 

• Related vendors: Qualtrics, Amplitude, Totango, Braze. 

Omnichannel Connection 

The final layer – and the most transformative – focuses on unifying data and experience across the organization. These platforms make marketing, sales, and service work as a single, insight-driven system. 

• Customer data & identity management: With these intuitive systems, client teams have a top-down 360° view of all customer touchpoints. This enables personalized content and predictive insights across the client journey. 

• Smarter digital engagement: When clients communicate with a company’s AI bots or human agents, omnichannel systems enable seamless conversations across sessions and channels. 

• Integration & automation layers: Acting as the connective tissue itself, these tools enable information to automatically flow to the right places and at the right times, feeding the 360° vision. 

• Related vendors: Salesforce, Zeta Global, Sprinklr, Zapier. 

Mind the Gaps: Adoption Pitfalls That Can Stall Your Tech ROI

While these solutions can open new doors for marketing & sales teams, adoption is not always a straightforward path. And the stakes are high.  

Putting aside financial consequences for the business, members of a buying committee may lose credibility if they support a purchasing decision that later fails to bear fruit. 

Going one step further, an unsuitable adoption journey can spark a negative reaction from customers, regulators, and investors.  

Vendors often pitch that their tools are simply ‘plug and play’. The reality is that enterprises must consider these adoption challenges: 

Privacy and first-party data:

Concerns around user privacy have been growing steadily, and this has resulted in a clamp down on legacy forms of data collection, such as third-party cookies. 

• Marketing teams today are expected to comply with all new privacy regulations. They should aim to responsibly collect consented data while fostering valuable personalization.
• Enterprise buyers must consider GDPR, CCPA, and other AI regulations – or risk the resulting backlash. 

Preventing underutilization:

A 2022 study from Gartner found that marketers were only utilizing 42% of their martech stack, a 16% drop from two years prior. The most common reason for this was an overlap of tech solutions, rendering part of the stack obsolete.

• With this in mind, sales and marketing teams can first consider how legacy solutions can be upgraded. Implementing a whole new solution may result in waste and underutilization. 

Employee satisfaction and skills:

One of the most common adoption challenges across every aspect of tech is ensuring the satisfaction of the humans that will be interacting with it day in and day out. 

• Adoption can be stalled when teams don’t have the skills or motivation to complete the onboarding. In relationship-driven industries such as sales, hesitancy about handing over the reins to AI is understandable.
• Secondly, if vendors can’t provide comprehensive support post-purchase, this will also extend the adoption process unnecessarily.  

Proving value:

“It’s not what you know, it’s what you can prove”. This isn’t just a stereotypical line from a legal drama, it’s also a key consideration when purchasing a new sales & marketing tool. 

• Due to the nature of outbound marketing, for example, it can be difficult for CMOs to prove that their department is truly delivering ROI. 
• More page views? More likes on a LinkedIn post? An increased email open rate? Consider which metrics are strong enough to justify a purchasing decision and whether a new solution will complement them. 
• For sales leaders, one common target is maximizing time with potential clients. This means they must prove that any new tech solution adopted is truly optimizing their time and workflow to open up their calendars for more calls. 

Rather than looking at the new features of an AI tool, tech buyers can start by looking at their own KPIs. Considering how a new solution will integrate and enhance existing processes of success measurement is key.

Cutting Through the Noise: A Buyer’s Guide to Selection Criteria

15,384.  

In kilometres, it’s roughly the distance between Guatemala City and Hyderabad. To count to from one, it would take you around four hours. But it’s also the number of Martech solutions that exist in 2025, according to a recent report. 

There isn’t even a recognised number of Salestech solutions out there, depending how wide one wants to cast their net, but it’s estimated to be over 1000. 

Rather than cause a serious bout of decision paralysis, these statistics are meant to illustrate how critical it is for enterprise buyers to have effective selection criteria. 

Here are some starting points to help you get from thousands to just one. The right one. 

Identifying your pain point:

Enterprise buyers will likely know what their primary growth constraint is, whether it’s more leads, more conversions, or a more comprehensive view of the entire customer experience. 

• Using the four categories system, buyers should ensure that there is a strategic fit with the relevant buying stage.  
• Keep in mind however, how processes upstream and downstream will impact your KPIs and growth. If you’re a sales leader struggling to convert meetings into successful deals, it could be that the marketing team is not generating targeted enough leads, for example. 

Data unification costs:

While it’s been established that AI can be a major differentiator in sales & marketing, but it is very much the ‘cherry on top’, as opposed to the solid foundation to build upon.  

• Without unifying new tools with existing data systems, creating a single, reliable source of truth becomes difficult.
• Without that, AI can expose more problems than it solves according to Tim Banting of Techtelligence. 
• Therefore, enterprise buyers should not expect a flashy new AI solution to be a ‘do-it-all’ tool. Instead, selection criteria should evaluate the integration costs that will create a fertile soil for AI to grow from. 

Success-centric vendors:

Vendors will already be thinking about how to prove their solution is right for you. Consider whether a vendor can provide a measurable realistic forecast of productivity gains that you can take to the buying committee.

• This mindset signals a shift away from promises, and more towards tying programs to results. 

The Future Trends Defining Sales & Marketing Technology

As we look toward 2030 and beyond, the sales & marketing technology landscape will undergo deeper transformation driven by greater automation, personalization, and data management.  

These teams can expect to see transformation in the content they produce, but also the workflows that define their workplace experience.  

Here are some future capabilities and trends to consider: 

The human and the machine:

While automation and AI will be embedded deeply, the differentiator will shift to how humans play a strategic role. Can they use technology to amplify creativity, judgement and empathy – not replace it?

• More than 50% of the internet is estimated to be AI-generated content. That trend has no signs of slowing. Companies that utilize AI, while amplifying their humanness, could capitalize on AI-fatigue among customers. 

Outcome-driven models:

As pressure mounts to prove ROI among sales & marketing teams, vendors may change how they frame their products.  

• The time of features, capabilities and upgrades, could be no more. 
• The future could vendors and buyers more oriented around business outcomes (e.g., increased net revenue retention, shorter sales cycles), rather than flashy products. 

Convergence of martech-adtech-servicetech:

The segmentation between “marketing tools”, “sales tools” and “customer service tools” will blur. This comes as omnichannel data connects everything and intelligence is found everywhere. 

• The future could see enterprises normalize an integrated revenue ecosystem with real-time feedback loops across the customer journey.

Final Takeaway: Building a Smarter, More Human Sales & Marketing Engine

Over the coming years, AI-driven orchestration, unified customer data, and outcome-based measurement will redefine what effective go-to-market execution looks like.  

Leaders who invest in scalable, ethical, and modular platforms today will find themselves better equipped to navigate tomorrow’s volatility. A future where buyer journeys are self-directed, expectations are personal, and attention is fleeting. 

Stay up to date on the latest sales & technology news by following CX Today on LinkedIn and keeping an eye on our new website category: Sales & Marketing Technology.

To hear from fellow buyers and tech decision makers, join the CX Today community group on LinkedIn where over 40,000 industry professionals are inspiring change. 

Indeed, workflows are expanding beyond departments, and solutions are knitting together

As such, parts of the business that may never have worked with a platform like Workday, like CX functions, may consider becoming more familiar with such leading technologies.

Here’s an example. Consider a customer service rep raising a query regarding their job benefits. In the future, they’ll likely interact with an AI agent that runs across into Workday to resolve their query.

As customer experience leaders collaborate with IT on these cross-department workflows, it’s fascinating to consider how leading tech brands, like Workday, are expanding their portfolios.

On that note, here are five of the biggest announcements from Workday Rising 2025, including product updates, a massive acquisition, and milestone partnerships.

1. Meet Workday’s New Illuminate Agents

Peter Bayless, Chief Technology Officer at Workday, gave key context to Workday’s product direction:

We’re shifting from the system of record for people and money to a system of action for people and money that understands their businesses, understands what they need, and helps them reimagine what work gets done.

As Workday becomes a “system of action for people and money,” its “Illuminate” AI agents will drive the action.

At Rising 2025, Workday announced three more AI agents to its Illuminate portfolio.

The first is a Case Agent that streamlines HR case management by reviewing cases, applying compliance context, and drafting responses.

Next is a Performance Review Agent. This gives managers a first draft of performance reviews, pulling in data from other systems.

Finally, a Financial Close Agent coordinates tasks, flags issues in real time, and reduces risk in the month-end close process.

The new agents bolster those already available on the Workday platform, as below.

Yet, as businesses deploy these agents and scale AI, managing the associated costs can be tricky. Recognizing this, Workday is introducing a new way for businesses to consume its AI: Flex Credits.

These credits come as part of Workday subscriptions, with the vendor promising no hidden fees or premium licenses.

Additionally, all the Credits are usable across any Workday AI agent or API. Meanwhile, customers can track their ROI “in a single dashboard.”

2. Workday Unveils a New Developer Platform

Workday Extend is a low-/no-code app development solution on which over 1,400 customers – including Target, Netflix, and NASDAQ – have built over 3,000 apps.

Now, Workday is introducing Build, the next evolution of Extend.

“This isn’t just another low-code platform,” said Mark Woollen, GVP of Partner Innovation at Workday. “It’s a complete offering, and designed specifically with the intelligent enterprise in mind.”

That complete offering includes several new tools and features. These include:

• A FlowWise Agent Builder – A low-code tool to design, deploy, and manage AI agents.
• AI Developer Tools – These include generative AI copilot and an Agent Gateway to connect AI agents built on Workday with third-party agents.
• An Expanded Ecosystem – Here, Workday provides vetted partner solutions that address industry- and region-specific needs.
• A Global Community – A space for developers to learn, certify, and collaborate.

Interestingly, in a demo, Workday also showed how its AI agents could connect to third-party apps like Microsoft Teams or Slack to automate cross-department tasks and publish directly into the Workday system of record.

3. Get Ready for Yet Another Data Cloud…

Workday Build sits on top of another new platform: Workday Data Cloud.

The platform aims to solve a common problem: enterprise data is often scattered, inconsistent, and siloed.

Workday Data Cloud does so by offering organizations secure, zero-copy access to their Workday data, leveraging the following key components:

• Apache Iceberg-based data lake (open standards).
• A Direct SQL access API for real-time insights.
• Workday Prism for governance and trust.

Through partnerships with Snowflake, Databricks, and Salesforce, businesses may combine Workday’s people and money data with broader enterprise datasets.

As a result, they can combine EX and CX data, unlock richer analytics, and accelerate AI innovation.

4. Workday to Acquire Sana for $1.1BN

Workday has agreed to snap up Sana Labs in the hope of turning Workday “into the new front door for work.”

The Sana Agent is critical here and will help to create a new user experience within Workday.

Indeed, it will help find information by scouring company data and knowledge sources, reason with that information, and act on it.

From there, it may create new documents, presentations, dashboards, and even “full learning courses” based on the information it takes.

Additionally, it can automate tasks by tracking changes in the data, which may span the enterprise.

So, a Workday user could soon use the Sana Agent to automate an action with an adjacent platform, like an employee service CRM module, without leaving the platform.

As such, this idea of a new front door for work is exciting. Yet, Sana Learn is another fascinating addition the acquisition brings to the company, as it could transform the Workday Learning platform. Below is a closer look.

5. Workday to Deliver a “Unified AI Agent Experience” with Microsoft

Finally, Workday has entered into a new relationship with Microsoft to help deliver a “unified AI agent experience.”

What does this mean? Essentially, brands can build AI agents on Copilot Studio and register and manage them within the Workday Agent System of Record (ASOR).

As such, if a brand wants to automate a workflow within their Workday instance, they can turn to Copilot Studio and deploy an AI agent within the Workday platform.

Key to this is a new integration between Workday Agent System of Record (ASOR) and Microsoft Entra Agent ID.

Per Workday, this will ensure that each AI agent entering its ecosystem can be verified and has enough business context to operate securely across the organization.

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In doing so, it has honed in on the requirements of its sweet spot: the midmarket.

Companies in the midmarket don’t typically have the skillset or time to configure innovations, like AI agents, from scratch.

Instead, they typically want pre-built innovations to drop into their platforms, customizing them to their business, teams, and needs.

HubSpot is following that path, not jumping from the latest hot trend to the next.

While some may frame HubSpot as lagging the likes of Salesforce, its customers can match its speed, steadily advance, and prove results.

The announcements at HubSpot INBOUND 2025 aim to help its customers take their next steps.

From new data and configure, price, quote (CPQ) solutions to pre-built AI agents and playbooks, here are the top ten announcements from the event.

1. HubSpot Debuts an All-New Data Hub

CRM platform providers have battled with unstructured data management for decades due to various challenges, often relating to data volumes, scope, and quality.

At INBOUND 2025, HubSpot released a new Data Hub in beta to tackle the issue head-on.

Data Hub aims to combine “all” data from across the front office (and beyond), centralizing structured, unstructured, and external sources into a single data foundation.

In doing so, it takes “every” data signal from across service, sales, and marketing, scouring warehouses, databases, documents, and apps.

From there, it automatically detects trends in the data and suggests connections. That allows businesses to piece together more complete customer profiles, while boosting automation efforts, segmentation strategies, and reporting across the HubSpot platform.

Indeed, HubSpot promises that Data Hub will tell a more “complete story” of the customer journey.

Meanwhile, Data Hub should lessen the load on customer-facing teams by equipping them with tools to fix common data quality issues. These include duplication, irregular formats, and inconsistencies.

2. Smart CRM Gets “Reimagined” for Hybrid Human-AI Teams

Data Hub will sit inside Smart CRM, HubSpot’s ecosystem of Engagement Hubs. These span service, sales, marketing, commerce, content, and operations.

As part of the Smart CRM platform, it will bolster that single pane of glass customer view.

Yet, it’s not just Data Hub that will do so. Instead, HubSpot has embedded a new capability to automatically catch and save data from the customer conversations happening across its Hubs.

Leveraging this “Conversational and Intent Enrichment” capability, companies can automatically update customer records with new intelligence, so every call, email, and meeting adds new context to the single customer view.

Additionally, HubSpot is introducing a “Smart Insights” tool to surface particularly useful new insights from across the CRM platform, so CX leaders don’t need to go digging through reports.

Finally, new “Flexible CRM Views” will allow users to visualize customer records in new ways, whether via a table, chart, or custom design.

Each of these three innovations is now in beta and, per HubSpot, highlights how it’s reimagining Smart CRM for hybrid human-AI teams.

3. HubSpot Unveils 18 New Breeze Agents

Announced at INBOUND 2024, HubSpot Breeze is a suite of AI solutions available across the Smart CRM platform.

Breeze includes a collection of AI agents, aptly named: Breeze Agents.

HubSpot announced 18 new Breeze Agents in beta at this year’s event. These include seven for marketing, six for sales teams, and five for customer service, as the chart below shows.

These join the 15 “ready-to-work” Breeze Agents already generally available.

At INBOUND 2025, HubSpot spotlighted three specific examples customers are finding particularly beneficial: its Data Agent, Customer Agent, and Prospecting Agent.

The Data Agent scours CRM data, transcripts, files, and external web sources to research and answer custom questions about customers. Answers taken from the web can be added to the Smart CRM.

Meanwhile, the Customer Agent serves go-to-market teams, answering their questions, quantifying leads, and communicating with customers across channels. In doing the latter, it leverages CRM data for personalization and can automatically resolve over half of customer interactions, according to HubSpot.

Lastly, there’s the Prospecting Agent. This works like a sales rep, automating tasks like monitoring buying signals from prospects, researching target accounts, and sending personalized outreach.

4. New Assistants Enter the HubSpot Breeze Party

While HubSpot first offered Breeze Copilot across its individual Hubs, it now provides a ubiquitous Breeze Assistant that works alongside users as they navigate HubSpot.

In doing so, the Breeze Assistant remembers the user’s preferences as it performs “dozens” of tasks, like conducting research that spans CRM solutions and prepping for meetings.

Additionally, HubSpot is offering Custom Assistants. Companies can train these assistants on their business processes, documents, and best practices to automate specific tasks for their employees.

For instance, a marketing team may build a Custom Assistant that works alongside associates to update specific landing pages. Yet, possible use cases span the Smart CRM ecosystem.

5. The Breeze Studio & Marketplace Also Go Live

HubSpot customers will soon be able to discover, scout, and deploy all of HubSpot’s Breeze Agents and Assistants via the new Breeze Marketplace, which is now in public beta.

While each Breeze Agent is pre-configured for particular use cases, businesses can customize each AI agent and assistant to meet their specific requirements.

How? By visiting the new Breeze Studio, which has also entered public beta.

Within the Studio, brands can upload knowledge sources, define guidelines, and outline processes, enabling Agents and Assistants to function as team members who truly understand the company.

6. HubSpot Introduces a CPQ Solution to Commerce Hub

ServiceNow added a CPQ solution to its CRM platform after its April 2025 Logik.ai acquisition. Now, HubSpot has quickly followed suit.

Indeed, it added an “AI-powered CPQ” to Commerce Hub, which is again available in beta.

The CPQ takes deal context and conversational data to draft branded price quotes, which sales reps can tailor, via a drag-and-drop interface, and send off to customers.

From there, the customer can review the quote, accept, and pay from one page.

Meanwhile, the sales rep will receive an alert when the customer views, shares, and responds to their quote.

Those are the core capabilities. Yet, the CPQ also comprises a Closing Agent that can help to answer any questions the buyer might have about the quote, competing products, and possible discounts.

Finally, there’s also a “Product Builder and Flexible Approvals” capability. That allows the seller to tailor the CPQ to their business, includes marking fixed-price items, creating complex tiered product structures, developing customer approval workflows, and more.

7. HubSpot Tackles Sales Busy Work

The new CPQ will assist sales reps who still calculate prices manually, navigate spreadsheets, and rely on email chains. Yet, HubSpot has made several other moves to improve the sales rep experience.

These come in the form of new updates to Sales Hub, which are (once again) available in beta.

Two of the new updates stand out.

The first is new meeting assistance functionality, with AI automating various tasks that sales reps perform before, during, and after customer conversations.

Before, it will handle prep by analyzing the customer’s previous conversations, taking context from their deal history, and conducting ad-hoc research. During the meetings, it will capture key insights and action items. Finally, it will send personalized summaries to participants and isolate next steps after the interaction.

The other standout capability is a new tool that analyzes meeting transcripts to spotlight deal risks that could impact the rep’s pipeline. That enables proactive, preventative action.

8. HubSpot Launches a Growth Playbook for Marketers

As Yamini Rangan, CEO of HubSpot, stated during the company’s latest earnings call, marketing us experiencing “its biggest shift in decades.”

To help marketing leaders navigate that shift and keep their funnel full, HubSpot introduced Loop, a playbook for growth in the AI era.

Loop is the playbook that HubSpot uses itself, comprising four interconnected stages.

The first stage is “express“. Here, marketing leaders should “express” the brand’s taste, tone, and point of view. The Breeze Assistant may help, analyzing VIP customers and creating a style guide.

Next is “tailor“. In this stage, brands focus on how they can customize content so that it’s relevant and aligns with customer preferences. That could involve using AI-powered segmentation to develop audiences based on intent and fit signals.

Third is “amplify“, with HubSpot encouraging brands to diversify content across human- and AI-led channels. The vendor’s AEO (answer engine optimization) Strategy Tool can help here to pinpoint content in need of a refresh.

The final stage is “evolve” by running back through this strategy and iterating effectively. Again, HubSpot recommends one of its AI tools here: Email Engagement Optimization. The Marketing Hub feature helps predict which recipients are most likely to engage.

9. A New Marketing Studio Comes to Marketing Hub

Alongside the new Loop Playbook, INBOUND 2025 has brought many more innovations to marketers. Many of these, available in beta for Marketing Hub, will aid customers in bringing Loop to life.

First is a new visual canvas that enables marketing teams to collaboratively plan, create, and execute campaigns. It also provides AI suggestions to optimize results based on past performance.

Next is a “Segments + Personalization” feature that analyzes data from the CRM that pertains to a web visitor. It then segments and personalizes the site for that individual, with web pages and call to actions (CTAs) more likely to speak to them.

Finally, there’s “AI-Powered Email”. With this, marketers can personalize every email within a campaign, so individuals receive unique content and messages relevant to them. The feature will also predict who will engage and when.

10. HubSpot Confirms a New CRM Connect for Google Gemini

In press materials shared before INBOUND, HubSpot referenced three CRM connectors for large language models: ChatGPT, Claude, and Gemini.

While HubSpot previously announced the former two integrations, the Gemini connector appears to be a new addition.

These connectors pull data from HubSpot into the familiar AI tools for analysis. They can then draw any new insights they discover into the CRM for data enrichment.

So far, HubSpot is the only CRM vendor to offer such connectors. Yet, others will likely follow. When they do, they’ll likely pose some tough questions for today’s conversational intelligence market.

CX Today will be posting overviews like this through event season. To keep a pulse on what’s happening in the space, subscribe to our newsletter.

While major data breaches are becoming more common, many raised an eyebrow as one of the world’s most powerful tech companies succumbed to the hack.

The attack occurred in June of this year and targeted a Google corporate database run by Salesforce.

A statement released by the Google Threat Intelligence Group (GTIG) confirmed that the database in question was “used to store contact information and related notes for small and medium businesses.”

“Analysis revealed that data was retrieved by the threat actor during a small window of time before the access was cut off.

The data retrieved by the threat actor was confined to basic and largely publicly available business information, such as business names and contact details.

The attack is believed to have been orchestrated by the ShinyHunters ransomware group, also known as UNC6040: a well-established hacking collective.

Indeed, Cyber Security News is reporting that ShinyHunters has unofficially taken responsibility for the attack, claiming to have stolen approximately 2.55 million customer data records.

While no specific examples of these data records have been made public yet, the group’s typical strategy is to create a data leak site, which is used to target and extort victims with demands for bitcoin ransom payments.

In an update posted on the official GTIG blog on August 8th, the organization announced that it had “completed its email notifications to those affected by this incident.”

How the Attack Happened

When envisaging how the attackers went about infiltrating Google’s databases, you’d be forgiven for picturing some sort of technological wizardry.

However, it was actually voice phishing (vishing), one of the more traditional tools in the hacker arsenal, that was Google’s undoing.

Vishing is tried and tested for a reason. Rather than trying to navigate robust software defenses, the phone scam targets human vulnerabilities.

In this instance, the attackers posed as IT support staff to trick administrators into installing a malicious version of Salesforce Data Loader, disguised under names such as “My Ticket Portal.”

The genuine Data Loader is a trusted desktop tool capable of extracting, updating, or deleting Salesforce data, making it a powerful target.

The fake application mimicked the legitimate tool, reusing OAuth credentials to bypass consent screens and gain access to the organization’s backend.

From there, the attackers could quietly obtain sensitive data.

In discussing how the breach came about in a LinkedIn post, Anshul Verma, President of Cynoteck Technology Solutions, stressed:

This isn’t a Salesforce vulnerability – it’s a human-centric breach, exploiting trust and familiarity.

How to Stop Such Attacks from Happening to Your Business

Knowing how the attack happened is all well and good, but what really matters is figuring out how to prevent it from happening again.

Verma explains how, although companies like Salesforce have powerful security measures in place, these are of no use unless they are configured correctly.

In an extensive list of how to limit the likelihood of cyberattacks, he outlined the importance of only downloading software, tools, and apps from known sources.

Of course, this was the downfall of the Google hack. Had the customers checked directly with Salesforce, they would have discovered that Data Loader is available within the CRM itself, so there would have been no need to access it via a different source.

Verma is just one of many IT and security professionals who have spoken out following the confirmation of the breach.

Speaking in a Forbes article, Dray Agha, Senior Manager of Security Operations at Huntress, explained how any use of third-party vendors comes with risks, commenting:

Businesses must rigorously vet and continuously monitor all vendors with access to their data.

Agha also advocated for enhanced security awareness training and tighter access controls, particularly for cloud platforms managing sensitive customer data.

Although the Google incident wasn’t an especially sophisticated attack, in an AI era, hackers have more advanced weapons than ever before.

There is no doubt that the above advice will certainly limit the likelihood of an attack, but it is almost impossible to make your company completely bulletproof.

For most, it is no longer a case of will it happen, but when will it happen.

This is why businesses must also allocate time and resources to a best-in-class, fully tested Incident Response Plan.

After all, if it can happen to Google, it can happen to anyone.