Despite years of investment in martech and customer data platforms, many organizations still find themselves stuck—unable to translate mountains of data into meaningful, measurable outcomes. Why? Because the real challenge isn’t just technical. It’s organizational.
In our recent webinar, Joe Stanhope, VP and Principal Analyst at Forrester, joined Jeanne Jones, VP of Digital Marketing and Analytics at BECU, and Ranajay Nandy, VP of Analytics at Citizen Watch, to unpack what it really takes to make customer data work—and where so many organizations go wrong.
The Real Roadblock to ROI? Silos.
Joe Stanhope put it plainly: “You can’t have a technology conversation without also discussing the data.” The scale and complexity of customer data today is both a massive opportunity and a mounting problem. Most organizations are stuck in a loop—more engagement leads to more data, which should lead to more insights, but too often leads to more fragmentation.
“Users report to Forrester that it takes too long to deliver value with data. There are foundational data management challenges. Users experience poor data quality, and data still tends to exist fragmented and in silos,” Joe explained.
From Fragmented to Unified: Building the Foundation
BECU faced this exact challenge. Their initial focus? Simply getting access to the right data.
“We overcame that by working with Amperity, onboarding it into one system, stitching it together,” said Jeanne Jones. “Now we’re working to democratize that data across the organization. It’s a journey, not a project—it’s something you’re always going to be working on.”
Citizen Watch’s journey was similar. “We started with cleansing our internal data and building our CDP with Amperity,” Ranajay Nandy shared. “But the second challenge was governance—getting people to use the centralized data and not rely on local spreadsheets. It’s about process, training, and trust.”
From Data to Impact: The Power of Use Cases
One key insight across the conversation? Avoid the trap of building data infrastructure without knowing what it’s for.
“We don’t develop anything until we have a use case,” said Ranajay. “We run combined agile sprints with business and technical teams, anchored on an ‘object to outcome’ model.”
Jeanne echoed that sentiment: “Start with the business problem. What’s the question we’re trying to answer, the experience we want to deliver, or the segment we need to build? From there, the data needs become clear.”
Both emphasized tying use cases to measurable outcomes—whether it’s improved CPA, higher conversion, increased NPS, or better operational forecasting.
Personalization, AI, and the Human Element
When it comes to the future, AI is front and center—but it’s not a magic wand. Joe reminded us that AI success is still a people challenge: “AI is similar to any technical capability. The success is determined by the people.”
For Jeanne, it comes down to focus: “Don’t just do something because it’s cool. Do it because it will drive a business outcome.”
Ranajay added, “AI will collapse current workflows. Change management—not just technology—will be the key to success.”
A Culture Shift, Not Just a Tech Shift
Perhaps the most important insight of the hour came not from a technology strategy—but a mindset one.
“I wish I’d realized sooner that this was going to be an empathy exercise,” said Jeanne. “It’s not just about data or tools. It’s about understanding what motivates the people you’re working with—what they’re accountable for, what they’re afraid of. That’s how you build trust and make real progress.”
Want to hear the full conversation?
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