From Data to Decisions: How Analytics Powers Intelligent Automation

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2026 ANALYST REPORT SERIES

From Data to Decisions: How Analytics Powers Intelligent Automation WRITTEN BY: BROOKE LYNCH

SPONSORED BY:

ANALYST REPORT: FROM DATA TO DECISIONS: HOW ANALYTICS POWERS INTELLIGENT AUTOMATION

Featuring Insights From

Eric Williamson CMO CallMiner

Introduction Delivering an exceptional customer experience is pivotal. In today’s hyper-competitive environment, it requires more than just a friendly interaction. Moving beyond reactive resolutions, customers want streamlined support that addresses and solves their needs from the start – often through connected, intelligent systems that understand their intent and sentiment before they even reach an agent.

According to CCW Digital research, this level of service, however, is far from what customers are actually receiving. As high as 59% of customers agreed that experiences have gotten worse this past year. And when it comes to effectively using tech, only a third of customers stated that they believe organizations are implementing AI with their needs in mind.

This is alarming, but not necessarily surprising. While organizations are always striving to do more for customers, they have not been in the position to leverage technology and data to its fullest potential. Without unified conversation intelligence (the ability to capture and analyze 100% of interactions across channels) customers are left navigating inefficient, friction-filled journeys, seeking reactive support to challenges that could have been resolved proactively.

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Why is this such a sticking point? Unfortunately, too many organizations do not have the intelligence or feedback loops in place to enact real change. Organizations continue to offer more opportunities to engage, with new channels and touchpoints, but they often lack the ability to actively collect and utilize this data to improve outcomes in real time.

CCW Digital research confirms that 99% of organizations are maintaining or increasing their investment in AI. But, without a data-driven strategy, organizations are not implementing the technology with intention.

Eric Williamson, CMO, CallMiner shares

“Insights lead directly to action, whether

it’s agent coaching, process changes, or proactive customer outreach. Without it, even the most well-intentioned analytics programs are dead ends. The “loop” is what turns intelligence into measurable improvement, again and again, in real time.”

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ANALYST REPORT: FROM DATA TO DECISIONS: HOW ANALYTICS POWERS INTELLIGENT AUTOMATION

It is this data and continuous feedback loop that will ultimately help organizations power intelligent automation. From streamlining processes to enhancing conversation flows, data-driven automation supports a more dynamic yet streamlined customer experience.

When leveraged correctly, AI can help uncover critical insights, summarize key information, and take the weight off CX teams as they work to connect with customers.

This report will cover how brands can go from siloed data to AI-informed decisions and highlight what is standing in their way. It will also dive into key solutions for enhancing CX operations and establishing a modern experience that exceeds customer expectations.

The State of Data and Intelligence When it comes to data and intelligence, contact center leaders are aware of its importance. CCW Digital research confirms that data and intelligence is a top investment priority for 60% of executives.

While this is clearly a priority, the investment may not be backed up by a comprehensive strategy,

“When contact center leaders say data and intelligence is at the top of their tech investment list, they’re really talking about survival,” shares Williamson.

The ever-increasing opportunities for customers to connect has left brands with even more data to audit. Williamson continues, “Modern CX has shifted from predictable, one-channel interactions to a constant, omnichannel hum – phone calls, chats, emails, social messages, surveys, all happening simultaneously, at all hours of the day. The flood of interactions is packed with insight, but without the ability to capture, interpret, and take action on it, most organizations are flying blind.”

Without uncovering and acting on these insights, experiences diminish — in a recent CCW Digital customer survey, only 18% shared that their typical experience feels personalized. Customers consistently have to repeat themselves, re-ask questions and forge their own path to resolution.

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ANALYST REPORT: FROM DATA TO DECISIONS: HOW ANALYTICS POWERS INTELLIGENT AUTOMATION

When customers work across channels, context is often lost. If organizations are not making a conscious effort to connect these contact points and capture this data properly, it will lead to diminished outcomes.

A lack of insight also hinders human agents’ ability to form meaningful connections with customers. According to CCW Digital research, 69% of leaders shared that agents have limited or no access to a 360-degree view of the customer journey and past interactions. When agents enter into interactions, including those handed off from virtual agents (e.g. voicebots), with little to no context, it leaves customers with a negative impression.

on in the contact center. With AI, organizations can analyze all interactions in real-time to deliver a proactive experience when it counts. Further, intelligent automation is adaptive and will continually learn from interactions, ensuring that the more data and intelligence it has, the greater the outcomes.

“Leaders have realized that intelligence isn’t a niceto-have – it’s the foundation and a key differentiator.

Without it, investments in automation, agent coaching, or even marketing campaigns will miss the mark because they’re operating on assumptions rather than truth,” shares Williamson.

With all of these conversations occurring simultaneously, it is clear that brands are struggling to transform this data into meaningful insights. Without a strategy in place to capture, collect and organize this intelligence (ideally leveraging tools that can unify and enrich it), leaders and frontline teams are left to make decisions based on assumptions — which is never productive.

Beyond operational support, data and insights power everything leaders do. Every day they’re looking at this critical information, to make effective decisions about the future of support, technology investments and customer needs. In fact, 58% of leaders stated that a growing emphasis on predictive and proactive CX is impacting their technology investment strategy.

Analytics for Intelligent Automation

Building a strategy to support a more cohesive intelligence operation that drives informed decision making is increasingly necessary as we look ahead.

Additionally, introducing the tools and technology that can support them in capturing 100% of interactions, across every channel, will help establish a more comprehensive single source of truth. With this in place, leaders can begin to power intelligent interactions.

To leverage analytics and intelligence effectively, leaders must home in on both tech and strategy.

CCW Digital research confirms key goals for analytics investments in 2026: to improve predictive and proactive engagement, monitor and measure quality across multiple channels and conversation types and identify root cases of CX and EX challenges.

By digging deeper and getting an understanding of why things are going wrong, how interactions can improve and what it will take to get there, organizations are setting their CX teams up for success. AI can support this process, empowering teams to uncover insights across the customer spectrum. By making customer conversations searchable and identifiable, this information becomes more accessible.

Once they are able to identify root causes, leaders can work to eliminate them. Pain points like long wait times and repetitive interactions can be solved with a more intentional AI implementation. AI assist tools can help streamline workflows and reduce manual tasks, allowing human agents to act more quickly and focus on the customer.

In today’s ever-changing, CX environment, it is not enough to reactively track pain points and mistakes, leaders must have a real-time pulse on what is going

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Closing the Loop It is clear that AI has the potential to streamline workflows and positively impact experiences. When asked about their current AI deployments, 67% shared that they have been impressed by the value and actionability of insights they have secured.

To establish intelligent automation, leaders should home in on a few key areas. First, securing visibility across channels. This visibility must extend from the boardroom to the frontline. Making insights accessible and digestible is critical to begin using them to inform decision making. Leaders can also embrace tools like automated multichannel journey mapping to track and analyze interactions as they flow across platforms.

By visualizing the customer journey, organizations can better understand behavior and quickly identify bottlenecks in the experience.

Leaders should also leverage AI analysis tools to dig

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ANALYST REPORT: FROM DATA TO DECISIONS: HOW ANALYTICS POWERS INTELLIGENT AUTOMATION

deeper into every interaction. For 78% of leaders, real-time customer intelligence like quality monitoring, sentiment analysis and predictive insights are key use cases for agent-facing AI, according to CCW Digital research. With these tools (especially when built on a unified conversation intelligence foundation), organizations will begin to uncover critical trends and deeply understand customer needs.

Most importantly, leaders must prioritize closed-loop automation to ensure that no customer signal is wasted. With so many new channels of communication, organizations must look at the customer journey holistically. When organizations are able to track pain points across channels and monitor progress, they can continually make improvements.

Williamson shares that without this closed-loop approach, even the best analytics can become dead ends. This “loop” turns intelligence into improvement.

“It’s not just about ‘more data.’ It’s about knowing exactly what your customers are saying, feeling, and needing in real time, and being able to use that understanding to adapt processes, guide frontline teams, and deliver personalized experiences, at scale,” states Williamson.

Customers are consistently telling brands what they want — through interactions, social media and real-time feedback.

These signals must go beyond the channel to be integrated into future strategy. When organizations are able to keep a consistent pulse on what customers expect out of interactions, they can remain dedicated to continuous improvement and a closed-loop approach.

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ANALYST REPORT: FROM DATA TO DECISIONS: HOW ANALYTICS POWERS INTELLIGENT AUTOMATION

Next-Steps for Success Organizations that work to unify their data, analyze it in real-time and act on it quickly will consistently be on the cutting edge.

Although it can, at times, feel like a never-ending journey, making a few intentional, strategic moves can help set an organization up for long-term success.

The CallMiner team offers a framework for next steps: 1.

Unify your data: Integrate every interaction channel into one source of truth.

So many organizations struggle with siloed data;, unifying this data is not just about storing it properly but building contextual continuity across the experience. This will help eliminate blind spots, reduce customer effort and establish a seamless journey. With so few organizations in the position to deliver a 360-degree view of the customer, this step is critical. Leading conversation intelligence solutions can help unify channels automatically, providing an integrated insight layer for decision-making.

2. Build intelligence first: Automation without understanding is risky. Get your conversation intelligence foundation right before scaling automation.

Rushing to deploy automation technology will not solve deep-seated issues. Without taking the time to understand pain points, organizations can end up actually making the problems worse. Ultimately, brands cannot automate what they do not first understand.

It’s important to dedicate time and resources to build a conversation intelligence foundation. By capturing, analyzing and acting on data, organizations can then begin to integrate automation into their operations. But as it stands today, and according to CCW Digital research, less than one third of customers believe AI is helping to improve their experience.

Knowing this, it is necessary to start with a firm understanding of existing pain -points. It is essential to lead with a strong foundation in intelligence, rather than deploying automation based on assumptions. This approach ensures AI deployments are based on verified truths from actual customer conversations, rather than theoretical models.

3. Align cross-departmental collaboration: Make sure CX, marketing, sales, and product teams agree on how insights will be used.

As organizations open up a world of insights, they must work to ensure data flows across departments. Without a crossdepartmental agreement and proper frameworks, insights can become lost, or even worse, a source of conflict.

Feedback loops aren’t just for external customers’ processes. Leaders should build actionable internal feedback loops with formal processes, tracking how data flows throughout the organization. By prioritizing a collaborative approach, insights will start to make a positive impact across the board.

Conversation intelligence platforms can play a key role here, enabling shared dashboards and reports for crossfunctional alignment.

4. Start small, expand fast: Launch with one journey or workflow, prove impact, then broaden scope to more processes.

When organizations try to tackle everything at once, – it can actually lead to more stalled projects than progress. With more than half of leaders stating that their AI journey has been slower than expected, starting with a smaller scope can help scale at a more productive, but intentional pace.

By starting small, organizations can also fail safely. Leaders can iterate and improve before rolling out changes more broadly to customers. This prompts a more efficient but tailored approach, giving customers and agents access to the most enhanced technology.

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ANALYST REPORT: FROM DATA TO DECISIONS: HOW ANALYTICS POWERS INTELLIGENT AUTOMATION

Piloting with unified conversation intelligence ensures early projects produce measurable insight-driven results, accelerating trust in broader AI programs.

From Data to Decisions: Why Analytics are Key in 2026 In 2026, leaders know that the only way to improve is to deeply understand what customers want. Once that intelligence is revealed, brands can work to create an experience that feels both tailored and efficient.

When organizations are in the position to unpack the most urgent pain points, they can finally work to eliminate them. As we look ahead, the bridge between current challenges and future opportunities hinges on intelligentse of automation and analytics. Technology will continue to evolve, but the fundamental need for unified data and intelligent foundations remains constant.

Ensuring these foundations come from accurate, multi-channel conversation data will be critical to sustaining competitive differentiation and customer loyalty.

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ANALYST REPORT: FROM DATA TO DECISIONS: HOW ANALYTICS POWERS INTELLIGENT AUTOMATION

About the Author Brooke Lynch is the Divisional Director of Digital. With a background in television news and production, she’s worked across industries covering B2B marketing, procurement and finance events.

Her current work highlights challenges and opportunities for customer experience and contact center leaders, with a recent focus on e-commerce, retail, and technology.

Brooke Lynch Division DIrector, Principal Analyst CCW Digital

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Managing Director & Principal Analyst CCW Digital

Audrey Steeves Content Analyst CCW Digital

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