Playbook

From User Signals to Named Situations

The Situations Playbook helps teams move from collected signals to stable, shared context that can guide product and design decisions. Where Techniques covers how to read signals through four lenses, the Playbook covers what to do with that reading — how to organize evidence, move through the Observe → Interpret → Name cadence, and decide when a situation is ready to carry into Measure.

The playbook supports product teams, researchers, designers, AI-assisted workflows, stakeholder reviews, and concept evaluation.

Situation Inputs

Situations emerge from signals gathered across the Define blocks that come before them. User Needs names what people are trying to accomplish. Audience identifies whose signals carry weight. Collecting gathers the evidence. Situations is where those three converge.

The strongest situations usually become visible when signals from multiple sources begin pointing to the same recurring conditions.

<table xmlns="http://www.w3.org/1999/xhtml" style="min-width: 511px;"><colgroup><col style="min-width: 25px;"><col style="width: 128px;"><col style="width: 179px;"><col style="width: 179px;"></colgroup><tbody><tr><td colspan="1" rowspan="1">Input</td><td colspan="1" rowspan="1" colwidth="128">Artifact Format</td><td colspan="1" rowspan="1" colwidth="179">What It Is</td><td colspan="1" rowspan="1" colwidth="179">What It Reveals</td></tr><tr><td colspan="1" rowspan="1">UX Metrics</td><td colspan="1" rowspan="1" colwidth="128">Dashboard, spreadsheet, exported report</td><td colspan="1" rowspan="1" colwidth="179">Behavioral and attitudinal measurements collected from product experiences</td><td colspan="1" rowspan="1" colwidth="179">Recurring friction, behavioral patterns, and engagement breakdowns</td></tr><tr><td colspan="1" rowspan="1">Analytics</td><td colspan="1" rowspan="1" colwidth="128">Dashboard, event logs, funnel reports</td><td colspan="1" rowspan="1" colwidth="179">Usage data, drop-off behavior, feature engagement, and session patterns</td><td colspan="1" rowspan="1" colwidth="179">Where the same workflow conditions keep producing the same outcomes</td></tr><tr><td colspan="1" rowspan="1">Usability Findings</td><td colspan="1" rowspan="1" colwidth="128">Notes, recordings, reports, screenshots</td><td colspan="1" rowspan="1" colwidth="179">Observed interaction problems during testing or live reviews</td><td colspan="1" rowspan="1" colwidth="179">Comprehension gaps and repeated hesitation points</td></tr><tr><td colspan="1" rowspan="1">Customer Interviews</td><td colspan="1" rowspan="1" colwidth="128">Transcript, notes, audio, video</td><td colspan="1" rowspan="1" colwidth="179">Conversations with users about workflows, frustrations, and goals</td><td colspan="1" rowspan="1" colwidth="179">Motivations, emotional context, and forces shaping behavior</td></tr><tr><td colspan="1" rowspan="1">Support Tickets</td><td colspan="1" rowspan="1" colwidth="128">Text threads, CRM exports, spreadsheets</td><td colspan="1" rowspan="1" colwidth="179">Customer-reported issues, complaints, and requests</td><td colspan="1" rowspan="1" colwidth="179">Recurring operational conditions and workflow friction</td></tr><tr><td colspan="1" rowspan="1">Surveys</td><td colspan="1" rowspan="1" colwidth="128">Forms, spreadsheets, exported reports</td><td colspan="1" rowspan="1" colwidth="179">Structured user feedback collected at scale</td><td colspan="1" rowspan="1" colwidth="179">Expectations, satisfaction patterns, and recurring concerns</td></tr><tr><td colspan="1" rowspan="1">Concept Testing</td><td colspan="1" rowspan="1" colwidth="128">Screenshots, prototypes, reports, videos</td><td colspan="1" rowspan="1" colwidth="179">Feedback gathered from evaluating ideas or flows with real users</td><td colspan="1" rowspan="1" colwidth="179">Early comprehension, trust, and confidence signals</td></tr><tr><td colspan="1" rowspan="1">Workflow Observations</td><td colspan="1" rowspan="1" colwidth="128">Notes, recordings, journey maps</td><td colspan="1" rowspan="1" colwidth="179">Observations from watching users complete tasks in context</td><td colspan="1" rowspan="1" colwidth="179">Environmental and operational forces shaping behavior</td></tr><tr><td colspan="1" rowspan="1">Helio Audience Signals</td><td colspan="1" rowspan="1" colwidth="128">Poll results, participant group data</td><td colspan="1" rowspan="1" colwidth="179">Behavioral and motivational data from defined audience segments</td><td colspan="1" rowspan="1" colwidth="179">Whether the same situation appears across different audience sources</td></tr><tr><td colspan="1" rowspan="1">Stakeholder Assumptions</td><td colspan="1" rowspan="1" colwidth="128">Notes, workshop docs, presentations</td><td colspan="1" rowspan="1" colwidth="179">Internal beliefs or opinions about user behavior and workflow conditions</td><td colspan="1" rowspan="1" colwidth="179">Organizational blind spots and unvalidated situational framing</td></tr></tbody></table>

Situations do not require perfect inputs. They require enough recurring signal across enough sources to see the same conditions producing the same behaviors. Sometimes a single session reveals a situation clearly. More often, a situation only becomes nameable after multiple signals converge across workflows, audiences, and time.

Observing for Situations

The first step in the cadence is Observe. Teams review signals not for isolated findings but for recurring conditions. The question is not what happened in this session — it is whether the same circumstances keep producing the same behavior.

As teams move through signals, they should watch for the following recurring conditions:

<table xmlns="http://www.w3.org/1999/xhtml" style="min-width: 482px;"><colgroup><col style="min-width: 25px;"><col style="width: 212px;"><col style="width: 245px;"></colgroup><tbody><tr><td colspan="1" rowspan="1">Condition</td><td colspan="1" rowspan="1" colwidth="212">What Teams Should Watch For</td><td colspan="1" rowspan="1" colwidth="245">Situation Type It May Signal</td></tr><tr><td colspan="1" rowspan="1">Repeated hesitation</td><td colspan="1" rowspan="1" colwidth="212">Users pausing, reconsidering, or stalling at the same point across sessions</td><td colspan="1" rowspan="1" colwidth="245">Comprehension breakdown or trust gap</td></tr><tr><td colspan="1" rowspan="1">Workflow avoidance</td><td colspan="1" rowspan="1" colwidth="212">Users skipping steps, finding workarounds, or abandoning predictable paths</td><td colspan="1" rowspan="1" colwidth="245">Effort or relevance mismatch</td></tr><tr><td colspan="1" rowspan="1">Contradictory signals</td><td colspan="1" rowspan="1" colwidth="212">Metrics and feedback pointing in different directions across the same workflow</td><td colspan="1" rowspan="1" colwidth="245">Perception and behavior misalignment</td></tr><tr><td colspan="1" rowspan="1">Confidence drop</td><td colspan="1" rowspan="1" colwidth="212">Delayed decisions, repeated revisiting, stalled progression despite task completion</td><td colspan="1" rowspan="1" colwidth="245">Trust or reliability condition</td></tr><tr><td colspan="1" rowspan="1">Engagement without retention</td><td colspan="1" rowspan="1" colwidth="212">Strong usage signals that do not convert to sustained return behavior</td><td colspan="1" rowspan="1" colwidth="245">Needs-behavior gap</td></tr><tr><td colspan="1" rowspan="1">Consistent drop-off point</td><td colspan="1" rowspan="1" colwidth="212">Users exiting at the same workflow stage across different sessions and audience segments</td><td colspan="1" rowspan="1" colwidth="245">Friction or expectation mismatch</td></tr><tr><td colspan="1" rowspan="1">Organizational blind spots</td><td colspan="1" rowspan="1" colwidth="212">Teams repeatedly missing or dismissing the same signals in stakeholder reviews</td><td colspan="1" rowspan="1" colwidth="245">Decision loop weakness</td></tr><tr><td colspan="1" rowspan="1">AI output noise</td><td colspan="1" rowspan="1" colwidth="212">AI-generated content accelerating production faster than teams can evaluate quality</td><td colspan="1" rowspan="1" colwidth="245">Signal credibility condition</td></tr></tbody></table>

The strongest situations usually become visible when:

• Multiple signal sources reinforce the same condition

• The same behavior repeats across different audience segments

• Metrics and stated feedback conflict in a consistent direction

• Friction appears at the same point across time and stage

• Early signals accurately predict later outcomes

The goal at this stage is not forcing a name onto a situation too early. The goal is gathering enough recurring signal to move into interpretation with confidence.

Interpreting Signals

The second step is Interpret. Teams apply the four lenses from Techniques to look for convergence — points where multiple signals, across multiple sources, point to the same underlying conditions.

Interpretation is not summarizing what the data shows. It is asking why the same conditions keep producing the same result, and whether that answer holds across lenses.

<table xmlns="http://www.w3.org/1999/xhtml" style="min-width: 517px;"><colgroup><col style="min-width: 25px;"><col style="width: 201px;"><col style="width: 291px;"></colgroup><tbody><tr><td colspan="1" rowspan="1">Lens</td><td colspan="1" rowspan="1" colwidth="201">Interpretation Question</td><td colspan="1" rowspan="1" colwidth="291">What Convergence Looks Like</td></tr><tr><td colspan="1" rowspan="1">By Type</td><td colspan="1" rowspan="1" colwidth="201">Are perception, behavior, and performance reinforcing each other or diverging?</td><td colspan="1" rowspan="1" colwidth="291">High satisfaction with low completion consistently suggests a comprehension or trust condition, not a motivation failure.</td></tr><tr><td colspan="1" rowspan="1">By Time</td><td colspan="1" rowspan="1" colwidth="201">Are early signals predicting what happens later, or pointing in the wrong direction?</td><td colspan="1" rowspan="1" colwidth="291">Leading indicators that consistently miss lagging outcomes suggest the situation is structural, not temporary.</td></tr><tr><td colspan="1" rowspan="1">By Stage</td><td colspan="1" rowspan="1" colwidth="201">Does the situation hold in production, or only in controlled testing?</td><td colspan="1" rowspan="1" colwidth="291">A condition that appears in proxy tests but disappears in analytics suggests the testing environment is not capturing the real situation.</td></tr><tr><td colspan="1" rowspan="1">By Engagement</td><td colspan="1" rowspan="1" colwidth="201">Where in the progression from need to behavior to habit does the situation create friction?</td><td colspan="1" rowspan="1" colwidth="291">Strong needs-based signals with weak activity signals consistently point to a habit-formation condition rather than a relevance failure.</td></tr></tbody></table>

A situation is ready to name when at least two lenses point to the same recurring condition across different users, sessions, or audience segments. One lens showing a pattern is an observation worth tracking. Two lenses converging on the same condition is a situation worth naming.

Prompt Structure

AI Skills help teams move through the Observe → Interpret → Name cadence more consistently. Strong prompts explain the workflow or context, include specific signal evidence, reference the lens being applied, and focus on conditions rather than solutions.

<table xmlns="http://www.w3.org/1999/xhtml" style="min-width: 506px;"><colgroup><col style="min-width: 25px;"><col style="width: 201px;"><col style="width: 280px;"></colgroup><tbody><tr><td colspan="1" rowspan="1">Focus</td><td colspan="1" rowspan="1" colwidth="201">What It Helps Teams Understand</td><td colspan="1" rowspan="1" colwidth="280">Example Prompt</td></tr><tr><td colspan="1" rowspan="1">Signal Review</td><td colspan="1" rowspan="1" colwidth="201">Surfaces recurring conditions across collected inputs before applying a lens</td><td colspan="1" rowspan="1" colwidth="280">"Review these usability findings and interview transcripts and identify recurring conditions where the same friction appears across different users."</td></tr><tr><td colspan="1" rowspan="1">Lens Application</td><td colspan="1" rowspan="1" colwidth="201">Applies a specific lens to a set of signals to look for convergence</td><td colspan="1" rowspan="1" colwidth="280">"Using the By Type lens, identify whether perception, behavior, and performance signals in these analytics are reinforcing or contradicting each other."</td></tr><tr><td colspan="1" rowspan="1">Situation Drafting</td><td colspan="1" rowspan="1" colwidth="201">Helps teams write a draft situation statement from converging signals</td><td colspan="1" rowspan="1" colwidth="280">"Based on these signals, draft a situation statement that names the recurring condition, what triggers it, what users are trying to do, what stands in their way, and what success means here."</td></tr><tr><td colspan="1" rowspan="1">Situation Validation</td><td colspan="1" rowspan="1" colwidth="201">Tests whether a situation statement holds across audience segments and signal sources</td><td colspan="1" rowspan="1" colwidth="280">"Does this situation statement hold for both trial users and habitual users based on these signals? Where does it break down?"</td></tr><tr><td colspan="1" rowspan="1">Audience Cross-Check</td><td colspan="1" rowspan="1" colwidth="201">Checks whether the same situation appears across different audience sources</td><td colspan="1" rowspan="1" colwidth="280">"Compare these signals from Helio participants against the analytics data and identify whether the same conditions appear in both sources."</td></tr><tr><td colspan="1" rowspan="1">Stakeholder Framing</td><td colspan="1" rowspan="1" colwidth="201">Helps teams present a situation in terms that connect to business priorities</td><td colspan="1" rowspan="1" colwidth="280">"Summarize this situation and its business impact in terms a product leader or stakeholder could evaluate and act on."</td></tr><tr><td colspan="1" rowspan="1">Pattern Grouping</td><td colspan="1" rowspan="1" colwidth="201">Organizes scattered observations into recurring conditions before naming begins</td><td colspan="1" rowspan="1" colwidth="280">"Cluster these support tickets and session observations into recurring situational conditions rather than individual complaints."</td></tr></tbody></table>

Strong prompts usually:

• Provide real workflow context and specific signal evidence

• Name the lens or cadence step being applied

• Focus on conditions rather than jumping to solutions

• Ask the system to explain why the condition may be recurring

• Test whether the situation holds across different users or sources

Expected Outputs

The goal of the Situations workflow is to produce a named situation — a stable, shared description of a recurring condition that teams can design against and Measure can test. Rather than a long summary of research findings, the output is a structured situation statement supported by converging signal evidence.

Primary Situation Output

When a situation is ready to name, the output should focus on a single structured description that captures what the situation is, what evidence supports it, what triggers it, what users are trying to do, what stands in their way, and what success means in that context.

<table xmlns="http://www.w3.org/1999/xhtml" style="min-width: 497px;"><colgroup><col style="min-width: 25px;"><col style="width: 223px;"><col style="width: 249px;"></colgroup><tbody><tr><td colspan="1" rowspan="1">Output</td><td colspan="1" rowspan="1" colwidth="223">What It Should Contain</td><td colspan="1" rowspan="1" colwidth="249">Example</td></tr><tr><td colspan="1" rowspan="1">Situation Name</td><td colspan="1" rowspan="1" colwidth="223">A short, descriptive label that teams can use as shared vocabulary</td><td colspan="1" rowspan="1" colwidth="249">"Onboarding confidence breakdown"</td></tr><tr><td colspan="1" rowspan="1">Summary</td><td colspan="1" rowspan="1" colwidth="223">A concise explanation of the recurring condition and the context it appears in</td><td colspan="1" rowspan="1" colwidth="249">"Users can technically complete onboarding but consistently leave uncertain and unsupported, reducing confidence in early product decisions."</td></tr><tr><td colspan="1" rowspan="1">Trigger</td><td colspan="1" rowspan="1" colwidth="223">The condition, pressure, or goal that sets the situation in motion</td><td colspan="1" rowspan="1" colwidth="249">Users encounter the first decision point requiring product understanding before context has been established.</td></tr><tr><td colspan="1" rowspan="1">What users are trying to do</td><td colspan="1" rowspan="1" colwidth="223">The progress the user is seeking in this specific context</td><td colspan="1" rowspan="1" colwidth="249">Complete setup and feel confident enough to act on the product's recommendations.</td></tr><tr><td colspan="1" rowspan="1">What stands in their way</td><td colspan="1" rowspan="1" colwidth="223">The friction, uncertainty, or constraint shaping behavior</td><td colspan="1" rowspan="1" colwidth="249">Recommendations appear before users understand the scoring system behind them.</td></tr><tr><td colspan="1" rowspan="1">What success means here</td><td colspan="1" rowspan="1" colwidth="223">How the user defines resolution, and what failure costs them</td><td colspan="1" rowspan="1" colwidth="249">Completing setup with enough confidence to act, rather than completing it and still feeling uncertain.</td></tr><tr><td colspan="1" rowspan="1">Evidence</td><td colspan="1" rowspan="1" colwidth="223">The converging signals across lenses and sources that support the situation</td><td colspan="1" rowspan="1" colwidth="249">High completion rate (By Stage), low trust scores (By Type), drop in return visits after week one (By Engagement), support questions about score meaning (Collecting).</td></tr><tr><td colspan="1" rowspan="1">Audience</td><td colspan="1" rowspan="1" colwidth="223">Which audience segments the situation appears in, and whether it varies by source</td><td colspan="1" rowspan="1" colwidth="249">Consistent across trial users and new paying users. Less pronounced in habitual users.</td></tr><tr><td colspan="1" rowspan="1">Why it matters</td><td colspan="1" rowspan="1" colwidth="223">The operational, user, or business impact of the unresolved situation</td><td colspan="1" rowspan="1" colwidth="249">Users who do not understand the product early are less likely to return, reducing retention and increasing support costs.</td></tr><tr><td colspan="1" rowspan="1">Lenses applied</td><td colspan="1" rowspan="1" colwidth="223">Which of the four lenses surfaced the situation and where they converged</td><td colspan="1" rowspan="1" colwidth="249">By Type and By Engagement converged on the same confidence gap. By Time confirmed it is structural, not temporary.</td></tr><tr><td colspan="1" rowspan="1">UX Metrics</td><td colspan="1" rowspan="1" colwidth="223">The metrics most useful for validating whether the situation is improving over time</td><td colspan="1" rowspan="1" colwidth="249">Comprehension, Trust, Completion Rate, Return Visits (week one to week two)</td></tr></tbody></table>

Example Situation Statement

In AI Skills or stakeholder reviews, a summary format is often more useful than the full table. Here is an example:

Situation: Onboarding confidence breakdown

Users can technically complete onboarding but consistently leave uncertain about what the product is telling them and what they should do next. Evidence across By Type and By Engagement lenses shows high completion paired with low trust and weak return behavior in the first two weeks.

The trigger is the first decision point requiring product understanding before context has been established. Users are trying to complete setup and feel confident enough to act, but recommendations appear before they understand the system behind them. Success would mean finishing setup with enough confidence to act, not just enough to finish.

This situation is consistent across trial users and new paying users. If left unresolved, teams are likely to improve visual polish or completion flows instead of addressing the underlying comprehension condition.

Recommended UX metrics:

• Comprehension

• Trust

• Completion Rate

• Return visits, week one to week two

Multiple Situations

In some workflows, more than one situation becomes visible at the same time. When this happens, the output should begin with a summary table before exploring each situation individually.

<table xmlns="http://www.w3.org/1999/xhtml" style="min-width: 457px;"><colgroup><col style="min-width: 25px;"><col style="width: 218px;"><col style="width: 214px;"></colgroup><tbody><tr><td colspan="1" rowspan="1">Situation</td><td colspan="1" rowspan="1" colwidth="218">Evidence</td><td colspan="1" rowspan="1" colwidth="214">Lenses That Converged</td></tr><tr><td colspan="1" rowspan="1">Onboarding confidence breakdown</td><td colspan="1" rowspan="1" colwidth="218">High completion, low trust, weak return behavior in week one</td><td colspan="1" rowspan="1" colwidth="214">By Type, By Engagement</td></tr><tr><td colspan="1" rowspan="1">Recommendation avoidance</td><td colspan="1" rowspan="1" colwidth="218">Low recommendation CTR despite high engagement with score display</td><td colspan="1" rowspan="1" colwidth="214">By Type, By Time</td></tr><tr><td colspan="1" rowspan="1">Workflow rework loop</td><td colspan="1" rowspan="1" colwidth="218">Users repeatedly returning to earlier steps after progressing</td><td colspan="1" rowspan="1" colwidth="214">By Stage, By Engagement</td></tr></tbody></table>

When multiple situations emerge simultaneously, prioritizing which to address first follows the same logic as User Needs:

• Which situation is blocking the others? A comprehension or trust breakdown usually needs to be resolved before workflow or engagement improvements will hold.

• Which situation has the strongest evidence? Prioritize situations supported by convergence across multiple lenses and multiple sources over those visible through only one.

• Which situation connects most directly to a business outcome? When evidence is roughly equal, the situation most tied to a measurable outcome is usually the right starting point.

Next Steps

Once a situation has been named, the next step is deciding where the team needs more clarity, evidence, measurement, or alignment inside the Decision Map.

<table xmlns="http://www.w3.org/1999/xhtml" style="min-width: 506px;"><colgroup><col style="min-width: 25px;"><col style="width: 242px;"><col style="width: 239px;"></colgroup><tbody><tr><td colspan="1" rowspan="1">Next Step</td><td colspan="1" rowspan="1" colwidth="242">Summary</td><td colspan="1" rowspan="1" colwidth="239">Why It Is Useful</td></tr><tr><td colspan="1" rowspan="1">Collecting</td><td colspan="1" rowspan="1" colwidth="242">Gather additional signals to strengthen the situation or test whether it holds across more sources</td><td colspan="1" rowspan="1" colwidth="239">Useful when the situation is visible but not yet supported by enough converging evidence</td></tr><tr><td colspan="1" rowspan="1">Hunches</td><td colspan="1" rowspan="1" colwidth="242">Form hypotheses about what is creating the conditions inside the situation</td><td colspan="1" rowspan="1" colwidth="239">Useful when the situation is named but the cause is not yet clear enough to test</td></tr><tr><td colspan="1" rowspan="1">Concepts</td><td colspan="1" rowspan="1" colwidth="242">Explore design directions that address the conditions inside the situation</td><td colspan="1" rowspan="1" colwidth="239">Useful when the situation is well-evidenced and the team is ready to generate possible responses</td></tr><tr><td colspan="1" rowspan="1">Questioning</td><td colspan="1" rowspan="1" colwidth="242">Design questions that surface attention, comprehension, and friction inside the situation</td><td colspan="1" rowspan="1" colwidth="239">Useful when the team needs to measure how the situation is experienced before designing against it</td></tr><tr><td colspan="1" rowspan="1">Findings</td><td colspan="1" rowspan="1" colwidth="242">Turn the situation into usable understanding that Measure can build on</td><td colspan="1" rowspan="1" colwidth="239">Useful when the situation is strong enough to anchor a test or a concept evaluation</td></tr><tr><td colspan="1" rowspan="1">Audience</td><td colspan="1" rowspan="1" colwidth="242">Check whether the situation appears consistently across different audience segments and sources</td><td colspan="1" rowspan="1" colwidth="239">Useful when the situation is visible in one source but not yet confirmed across others</td></tr><tr><td colspan="1" rowspan="1">Workflows</td><td colspan="1" rowspan="1" colwidth="242">Evaluate whether organizational or operational conditions are contributing to the situation</td><td colspan="1" rowspan="1" colwidth="239">Useful when the situation appears to have a systemic cause beyond the product experience itself</td></tr></tbody></table>

The goal is not following a rigid sequence. Different situations lead teams to different next steps depending on the strength of the evidence, the type of conditions involved, and what the team most needs to reduce uncertainty. The next step should always be driven by what moves the work forward, not by what comes next in a process.

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