People, learning, and the next chapter of 1:1 customer engagement.
A journey through Amsterdam
On a recent Amsterdam trip, a colleague invited me to join the product engineering team for an after-work boat outing around the canals on his boat. Away from our usual working day, it was a lovely opportunity to spend time and reflect on the decades past and the excitement around all that’s happening today.
Across the team, engineering, data science, product, and customer-facing backgrounds bring varied experiences to a shared purpose. All our engineers are moving the platform forward together. Their experience is critical and additive: each perspective helps us understand customer challenges, learn from one another, and build better solutions.
My own 25-year journey spans Chordiant and Pega. Being with new and similarly tenured colleagues in Amsterdam made me proud of that shared effort—and reminded me why the story matters beyond those who lived it.
If you are new here, 1:1 customer engagement means engaging with people as individuals, responding to their needs rather than treating everyone in a segment alike. Pega Customer Decision Hub (CDH) helps organizations decide how to do that across customer interactions.
This Expert Circle is a place to explore the practical lessons, customer challenges, and possibilities behind that ambition. Whether you have been building with us for years or are encountering these ideas for the first time, I hope it helps connect where we have been with what we can do next.
The individual was always the point
The product journey brings together important strands: KiQ’s predictive analytics and adaptive learning, and Prime Response’s campaign management. Together, they helped shape an enduring question: what makes sense for this customer, in this interaction?
That is the idea behind next-best-action: choosing the most appropriate thing to do for an individual, using what we know about their needs, likely responses, and current situation. Someone trying to resolve a service problem may need help, not an upsell. Another customer may genuinely benefit from a relevant offer. Sometimes the right choice is not to make an offer at all.
I think of this as a segment of one. Segments can help us understand patterns; the ambition is to make a decision for the person, not simply repeat the same treatment for everyone who shares a label.
Predictive AI estimates likely responses. Adaptive AI learns from outcomes. Business controls guide which actions should be considered. That combination has been central to this product journey for decades, with adaptive learning originating in KiQ—not appearing as a recent addition to the story.
Making that philosophy work takes continuous learning: listening to customers, testing ideas, and using what happens in real interactions to improve the next decision.
The software keeps moving
The principle has endured; the software around it has changed considerably.
Early decisioning brought predictions, learning, and business rules together around individual recommendations. After Chordiant joined Pega in 2010, that work developed within a broader platform, helping organizations coordinate engagement across inbound and outbound channels.
That matters because customers experience one relationship, not our organizational chart. A useful recommendation on a website can be undermined by an unrelated message from another team. Connecting those interactions helps the organization respond with greater consistency and context.
In 2020, Pega Marketing and CDH came together in Customer Decision Hub [8.5]. Business-led strategy design and control became increasingly connected around the decision: not just what a model predicts, but what the business intends, which customers qualify, and how changes are managed.
These are not separate histories to memorize. They are steps toward making individualized engagement more useful, coordinated, and manageable.
A more natural way to work
Today, Customer Engagement Studio opens another possibility: using conversation to create and refine engagement strategies and analyze their performance. Large language models can simplify that user experience. Expressing an intention or asking a question more naturally can leave teams with more attention for the customer problem and less for finding their way through software.
CDH remains the predictive and adaptive decision engine underneath, with business policies and governance supporting how strategies are applied and changed.
The platform is continually evolving through that collective effort. Decades of continuous learning and innovation help us explore new possibilities while staying focused on a question that still deserves our best thinking: how can an organization be more relevant and helpful to each person it serves?
The next chapter belongs to all of us
That is what we want this Expert Circle to be a home base for: practical lessons, real customer challenges, next-best-action, and the opportunities and governance questions that come with AI. Whether new or experienced with CDH please join the conversation, your experience can help us ask better questions.
Thank you to our internal Pega 1:1 community and our customer community for the collaboration, experience, and challenges that keep this work grounded. Longstanding members and newcomers alike: share your experience, challenge our ideas, and build with Pega.
The tools will keep changing. My conviction is that the individual customer must remain our constant.
Thinking back to Amsterdam, what makes me hopeful is the shared experience and collaboration behind this work. All our engineers are pushing the platform forward, and the wider community helps give that progress purpose. I look forward to what we can build together.
HELP SHAPE THE NEXT CHAPTER
What would you add to the story?
Whether you have been part of this journey for years or are discovering next-best-action today, I would love to hear your perspective.
- Share a memory: What milestone or product capability has been the most useful for you?
- Add your perspective: What have I missed, what dates did I get wrong, or what would you add or describe differently?
- A new perspective: New to Customer Decision Hub, what will better shape your adventure, where/when did you first read/hear about “Next-Best-Action”.
- Look ahead: What customer challenge or idea should we explore next?
Leave your thoughts in the comments.