Data isn't just for tracking metrics; it's a direct reflection of how users interpret your product's design and guidance. It highlights the gap between the intended use and the actual use, providing crucial feedback for product development beyond simple usage statistics.
Related Insights
Don't treat evals as a mere checklist. Instead, use them as a creative tool to discover opportunities. A well-designed eval can reveal that a product is underperforming for a specific user segment, pointing directly to areas for high-impact improvement that a simple "vibe check" would miss.
Read AI's initial product failed because it presented engagement data without actionable insights. They achieved 81% retention by adding a qualitative 'narration layer' that interpreted tone, emotion, and reactions, turning a data dashboard into a storytelling tool.
Customers describe an idealized version of their world in interviews. To understand their true problems and workflows, you must be physically present. This uncovers the crucial gap between their perception and day-to-day reality.
Data's role is to reveal reality and identify problems or opportunities (the "what" and "where"). It cannot prescribe the solution. The creative, inventive process of design is still required to determine "how" to solve the problem effectively.
Conversational ads offer an unprecedented one-on-one channel for brands to interact with customers at scale. The resulting data—customer questions, complaints, and feedback—is a goldmine for product development and other business functions, potentially exceeding the value of immediate customer acquisition.
Product teams often use placeholder text and duplicate UI components, but users don't provide good feedback on unrealistic designs. A prototype with authentic, varied content—even if the UI is simpler—will elicit far more valuable user feedback because it feels real.
Users often develop multi-product workarounds for issues they don't even recognize as solvable problems. Identifying these subconscious behaviors reveals significant innovation opportunities that users themselves cannot articulate.
Developers often test AI systems with well-formed, correctly spelled questions. However, real users submit vague, typo-ridden, and ambiguous prompts. Directly analyzing these raw logs is the most crucial first step to understanding how your product fails in the real world and where to focus quality improvements.
The true power of UX research is aligning the entire product team with a common understanding of the user. This shared language prevents working at cross-purposes and building a disjointed product that users can feel.
Product performance isn't one metric; it's the sum of all touchpoints, from support tickets to app reviews. These disparate inputs all roll up into the ultimate North Star metric: user engagement.