When Everyone Has a Different Customer in Mind

Re-design Synthesis Process

Given that the team’s understanding of users is based on labels, and that each team member’s interpretation of these labels varies, I employed a collaborative synthesis process that required all members to participate in the synthesis exercises and activities. The process includes 5 stages from the affinity group, framing, to pattern finding, narrowing down 200+ datapoints to 5 user archetypes.

Balancing Structure and Openness in Data Grouping

To avoid falling back to the broad initial labels we established for the client, I asked that each group contain a limited number of data points (2 to 10 per group). Since the same notes can support different research findings, we are open-minded to forming as many groups as possible throughout the research process. 

Structuring Insights: A Four-Element Framework and Reflexivity Practice

Another common mistake we want to avoid with insights is overusing attributes and descriptors, such as difficult, helpful, confident, etc. These terms are often subjective and do not provide sufficient detail for subsequent product and business decisions, as everyone’s interpretation of them varies. Therefore, we have established a linguistic framework for insights—comprising three elements: Subject, Cognition/Decision, Action, and Conditions—to clearly define user characteristics.

To have the team aware of the power of framing, I designed a brief exercise. Here we discuss how different insight might impact their actual work and decision-making. A series of reflexivity questions is also included to guide the framing. 

One discovery I’ve had from my work is this: the reason some insights prove effective while others leave teams feeling that nothing has changed is not that we lack data, but because our habitual language patterns and priorities have altered the way we think. These linguistic patterns, which fail to drive subsequent decisions, typically feature their punchiness yet lack reasoning and evidence:

• Focusing on finding 'challenges', 'painpoints', but is poor at illustrating what makes it a challenge in people's lives.

• Focusing on surfacing user behaviors without analyzing the underlying behavioral chains or motivations.

• Listing only what a tool “can do” as an opportunity, without considering who and how they would benefit from it.

• Merely listing specific observed details without summarizing the characteristics of those items.

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Customer Pattern Synthesis and Visualization Strategies

To identify a comprehensive customer pattern that can inform future product and business decisions, I focused on highlighting the psychological and behavioral characteristics shared by customers. At this stage, we avoid labeling each pattern in overly simplistic terms, such as “motivation” or “purchase decision”; instead, we aim to preserve rich insights within the patterns so that the team can gain a clear understanding of customer characteristics rather than getting bogged down in the sorting process itself.

Here, we also explore common forms of customer data visualization, including empathy maps, user personas, business blueprints, prototypes, and spectra, to determine the best ways to present customer patterns.