Evolving the Customer Persona: From Slide Decks to Living Conversations
In today’s product environments, especially those navigating omni-channel strategies, it’s no longer enough to rely on a static, siloed view of the customer. The expectation is a seamless flow between digital touchpoints, human support, physical environments, and back again. But our industry tools for understanding them? They often don’t keep up.
Because omni-channel strategies aim to create a unified and seamless customer experience across every touchpoint, from mobile apps and websites to in-person interactions, support channels, and social platforms, they demand a more flexible and full-spectrum understanding of the customer. That understanding has to adjust in real time as context shifts throughout the day, across roles, and between systems.
This tension is what first pushed me to re-evaluate how we approach customer personas in UX design. The traditional one-page design persona slide, while useful for alignment, felt increasingly out of step with the complexity and dynamism of actual human behavior. A bulleted list of pain points can’t reflect a user navigating three devices, four contexts, and shifting expectations across a day. I needed something more dimensional, more alive.
The Day-in-the-Life Narrative
My next step was to go deeper and to bring the persona into a more dimensional, narrative space. I started creating “day-in-the-life” summaries for each internal customer role, grounded in actual interview transcripts and observations. These evidence-based stories are written in the third person, using an anecdotal name to make the experience relatable while preserving anonymity.
What emerged was a temporal understanding: what this person navigates, what they prioritize, where tension builds, and how they move through their world. Because my customers are internal an important aspect of the narrative is capturing how they think about their customers, and how those second-order relationships shape their decisions and daily flow.
Although framed as “a day,” these summaries often compress key moments from across multiple days or weeks. This structure allowed the persona to feel anchored in time, without losing the richness and variability of their real-world experience. It wasn’t about capturing a literal 24 hours, it was about revealing the rhythms, pressures, and values that define the role.
This shift from static descriptors to lived context helps stakeholders connect with the persona on a more intuitive level. Instead of scanning bullets, they can follow a narrative arc, and in doing so, better understand the why behind behaviors, not just the what.
Mapping the Day-in-the-Life as a Graph
As I worked with these narratives, I started to notice patterns, recurring tasks, moments of friction, emotional inflection points, and the tools or systems that appeared repeatedly. The linear structure of the narrative helped establish flow, but I wanted to also understand how things were interconnected. What behaviors clustered? What moments influenced others? What external systems shaped internal decisions?
To explore this, I used generative AI to extract a knowledge structure from each persona which provided a collection of nodes (concepts, tools, experiences, or pain points) and relationships (e.g., leads to, blocks, depends on). These were based on the original narratives, transcripts, and research notes. I then generated pseudocode specifically formatted for Obsidian, so I could visualize this structure in its GraphView.
Obsidian’s graph provided a different lens on the persona, not a story, but a network. It allowed me to see how decisions connected to frustrations, how tools overlapped across workflows, or where expectations and constraints collided. It was, in essence, a structural mirror of the narrative, one that revealed patterns in space rather than time.
This graph didn’t replace the narrative, it extended it. Where the day-in-the-life story built empathy, the graph helped surface systemic insights. It gives my stakeholders a way to trace the logic of the persona’s world, not just feel it.
From Persona as Document to Persona as Dialogue
The next step in this progression is a shift toward an even more dynamic approach to personas as an interactive system that could allow you to explore and question the lived experience of a customer role.
I’ve been exploring a class of AI tools that supports this through the use of agents. These agents are designed to hold structured context from research artifacts such as interview transcripts, narrative summaries, behavioral insights, and they respond to questions in a way that reflects that understanding. Unlike chatbots that rely on general training, these agents are shaped by specific data and can be tuned to represent particular roles or perspectives.
Imagine being able to ask your internal customer:
Can you tell me about yourself?
What are some of your biggest challenges right now?
Now generate your own persona for me.
Instead of pulling up a slide deck or searching for a document, a colleague could just ask, and get a response that reflects the current state of research. The agent could describe its role, its priorities, the kinds of tools it uses, and where it tends to struggle, all in natural language, drawn from grounded sources.
Making Customer Insight Actionable Across the Business
This progression from static documents to interactive, research-driven agents is a potential shift in how organizations can access and apply user understanding at scale, in ways that support both design quality and business momentum.
It supports better, faster decisions
When customer insights live in slide decks or doc folders, they’re harder to find, interpret, and trust. Making them accessible through an interactive agent reduces friction across product, engineering, and business teams. This leads to faster decision-making, better alignment, and fewer assumptions.
It keeps the organization closer to the customer
Many teams talk about being customer-obsessed, but few operationalize what that really means. A persona agent lets colleagues engage directly with user context by asking real questions and getting grounded answers. This helps ensure that customer needs stay visible even as priorities shift.
It extends the reach of research
Research often gets trapped in decks or limited to those who were in the room. A dynamic persona makes insights more visible, repeatable, and reusable across time and teams. This increases the ROI of the original research effort and reduces duplication.
It evolves with the organization
As new research comes in, or as customer behaviors and business goals shift, the persona agent can be refreshed with updated data. While human stewardship is still required, the system is designed to adapt making it easier to stay aligned with reality without rebuilding from scratch.
It creates continuity through change
Instead of restarting the research process every time priorities evolve, the persona agent serves as a single, evolving point of truth. This helps teams maintain a consistent understanding of the customer, even as internal strategies or external conditions change.
This doesn’t replace human research, it’s gives our accumulated understanding a format that’s more useful, accessible, and durable, and one that can evolve over time and be shared more effectively across teams.