Jtbd Mapper

jtbd-mapper

Agent: UX Research Lead

L2 UX research lead (1x) (moved from Product, now reports to Head of Design) responsible for planning and leading user research to directly inform design decisions.

Department ethos: ideal-design.md

Skill Description

Maps jobs-to-be-done from research data to build a structured understanding of user motivations, desired outcomes, and the circumstances that trigger action.

When to Use

• When customer discovery or user research sessions have been completed and raw findings need to be structured into a jobs-to-be-done framework.
• When the product team needs a shared vocabulary for discussing user needs that goes beyond feature requests to underlying motivations.
• When prioritisation discussions are stuck on competing feature ideas and reframing around user jobs can break the deadlock.

Workflow

1. Data Consolidation: Gather all research inputs (interview transcripts, session notes, survey responses, support tickets) into a single repository for analysis. Deliverable: consolidated research data set.
2. Job Statement Extraction: Analyse the data to identify discrete jobs users are trying to accomplish. Write each as a job statement in the format: "When [situation], I want to [motivation], so I can [expected outcome]." Deliverable: raw job statement list.
3. Job Hierarchy Construction: Organise job statements into a hierarchy: core functional jobs, related emotional jobs, and social jobs. Group sub-jobs under parent jobs where appropriate. Deliverable: JTBD hierarchy map.
4. Outcome Mapping: For each core job, identify the desired outcomes users use to measure success and the pain points that indicate failure. Deliverable: job-outcome matrix.
5. Circumstance Documentation: Document the specific circumstances (triggers, constraints, context) under which each job becomes active. Deliverable: circumstance annotations on the JTBD map.
6. Validation & Prioritisation: Review the JTBD map with stakeholders, validate against quantitative data where available, and prioritise jobs by frequency, intensity, and current underservedness. Deliverable: prioritised JTBD framework.

Anti-Patterns

• Feature-as-job confusion: Writing job statements that describe product features ("I want to filter by date") rather than underlying motivations ("I want to find the most recent relevant item quickly"). Why: feature-level jobs lock thinking into current solutions and prevent discovering better approaches.
• Ignoring emotional and social jobs: Focusing only on functional jobs and omitting the emotional ("I want to feel confident I chose correctly") and social ("I want my team to see me as organised") dimensions. Why: emotional and social jobs often drive adoption, retention, and willingness to pay more than functional ones.
• Single-source mapping: Building the JTBD framework from one research method or one user segment. Why: jobs derived from a single source reflect that source's biases; triangulation across methods and segments produces more robust frameworks.
• Static framework: Treating the JTBD map as a one-time deliverable that never gets updated. Why: user jobs evolve as markets, technology, and user expectations shift; an outdated framework misdirects product investment.

Output

On success: Produces a prioritised JTBD framework containing job statements (functional, emotional, social), job hierarchy, outcome matrix, and circumstance documentation. Delivered as a structured document or visual map accessible to product, design, and engineering teams.

On failure: Report which jobs could not be clearly articulated (e.g., insufficient data for a segment), what additional research is needed, and recommend targeted follow-up studies to fill gaps.

Related Skills

• customer-discovery-planner-uxr — Discovery research produces the raw data this skill consumes.
• jtbd-to-stories-uxr — Translates the JTBD framework into actionable design requirements and user stories.
• user-feedback-synthesiser — Synthesised feedback themes can inform and validate job identification.