Collecting

Turn raw input into usable signals.Every design decision needs something to stand on. Collecting is where that foundation gets built.User Needs names what users are trying to do. Audience defines who you are learning from. Collecting is the step that turns both into actual evidence — behavior observed, reactions captured, perceptions recorded. Without it, the room fills with opinions. The loudest voice wins. Decisions get made on instinct instead of signal.Collecting is the discipline that prevents that drift. It is not about gathering more data. It is about gathering the right data, from the right people, at the right time — and connecting it to the metrics and decisions that move work forward.What This Block CoversCollecting is organized into seven sections, each with a specific job:SectionWhat It DoesOverviewExplains what Collecting is, where it sits in Define, and how it connects to User Needs, Audience, and Patterns.TechniquesCovers the 12 collection techniques: when to use each, what UX metrics they produce, and how to pair them.PlaybookProvides the five-step collection process with decision guidance, prompts, inputs, outputs, and the Define → Capture → Connect cadence.ReferencesProvides the Research Stacks catalog, the Tools four-axis framework, named instruments, and Design Stacks by context.ExamplesShows realistic collection situations, near-miss cases, and common traps that help teams recognize when a technique or stack is the right fit.DecisionsHelps teams identify their situation, determine where to start, and choose the next step that reduces uncertainty.Agent OperationsDefines how AI Skills behave operationally through routing logic, confidence rules, escalation handling, output contracts, and ambiguity resolution.What Collecting SolvesMost teams collect too much, too late, or for the wrong reasons. They fill dashboards no one reads or run interviews that sound insightful but never shape a decision. The result is the same: more activity, less clarity.Collecting with intent is different. It starts with a clear question, connects to a specific user need and business goal, and uses a method that produces a signal you can act on. The tension between what users need and what the business requires makes the right technique obvious.One signal can stop wasted effort. Ten can create confidence. A hundred can battle-test a strategy until it holds.What Kind of Feedback Are You Collecting?Different feedback types serve different purposes. A strong collection approach mixes several so you can see the whole picture — what users do, think, feel, and say.Feedback TypeWhat It CapturesTechniques and ToolsView user dataBehavior patterns and usage metrics.Analytics, clickstream, heatmaps.See what users doTask flows and completion outcomes.Task success testing, first-click, tree testing, time on task.Sense what users likeVisual attention and emotional response.Desirability studies, emotion tagging, satisfaction surveys, post-task reflection.Hear what users sayOpinions, expectations, and reactions.Surveys, interviews, in-product prompts, video feedback.Pair at least two types on any collection effort. Behavioral evidence tells you what happened. Attitudinal evidence tells you why.The Define → Capture → Connect CadenceEvery collection effort in Glare follows the same rhythm:•Define.Clarify what you need to learn and why. Pair the user need with the business goal. Write the hypothesis.•Capture.Choose the right stack, approach, and technique. Run it lean. Collect observable behavior, perception, or performance.•Connect.Share findings in the right format for the right audience. Show your sources. Link signals to UX metrics and decisions.This cadence appears across all the "-ing" blocks in Glare. It creates a consistent path from curiosity to clarity and makes every collection effort traceable back to a decision.Three Modes of LearningEvery collection effort fits one of three modes. Modes represent the mindset behind the research, not just the method chosen.ModeWhen to UseCore QuestionWhat You GetExploratoryEarly discovery, before clear hypotheses.What should we be solving or improving?Patterns, context, and unmet needs.EvaluativeMid-cycle, once ideas or designs exist.Does this design work for users?Clarity, comprehension, and usability signals.ComparativeLater, when choosing between options.Which version performs or communicates better?Directional proof and confidence in a decision.Modes define the type of learning. Stacks define where you collect it. Techniques define how. The full process is in Playbook.Proof in PracticeA university team was stuck on a navigation decision. Meetings circled for weeks. Everyone had an opinion. Nothing moved.The team defined their intent, paired it with a business goal around reducing support requests, and chose an Evaluative stack. They ran a preference test using Helio. Within hours, they had a signal: the hamburger menu improved usability by 14 percent and positive impressions by 41 percent.One technique, paired with the right metric, ended weeks of debate. That is what Collecting does.Business Impact• Faster validation shortens feedback loops and keeps projects moving.• Clearer signals build design credibility with leadership.• Documented sources give business meaning to design metrics.• Measurable results connect design decisions directly to adoption, retention, and satisfaction.Collecting is the foundation of measurable design confidence. Every signal gathered is a small act of momentum.Where Collecting Sits in DefineCollecting is the third block in the Define area, sitting between Audience and Patterns. User Needs and Audience tell you what to learn and who to learn it from. Collecting is how you actually go get it. Patterns is where those signals get synthesized into direction.BlockWhat It Focuses OnUser NeedsThe motivations, expectations, and goals that drive behavior.AudienceThe people and contexts you learn from.CollectingCapturing behavior, perception, and reaction.PatternsSynthesizing signals into repeatable findings that guide decisions.AI PromptThis prompt helps you choose the right research approach and instruments for your specific user need and business goal.Start with a user need and the business outcome you're trying to move. It guides you to:Pair your user need with a business goal and write the collection hypothesisChoose the right stack and mode for your situationMatch techniques and instruments to the metrics you're trackingPlan how findings will be shared at the project, team, and leadership levelYou'll end with a collection plan that's ready to execute, with technique, instrument, and audience all named.Use this before any fieldwork begins to make sure what you collect connects back to a decision.AI SkillsThe Collecting skill file teaches your AI the full five-step collection process and instrument library so it can recommend the right approach for any research situation.Load it when you need to go deeper on instrument selection, balancing the four feedback types, or connecting findings to a leadership-ready sharing format. It gives your AI:The five-step process from intent through to connecting findingsThe Research Stacks catalog with named instruments including SUS, SEQ, CES, and CASTLEThe full Techniques table with metric mappings for every methodThe four-axis tool framework across attitudinal, behavioral, performance, and specialized toolsDownload the skill file below to use the full Collecting framework with your AI assistant.