Jobs to Be Done skill for Claude Code

Find the progress customers hire you for. Claude writes job statements with no product in them, plans switch interviews that rebuild real purchase timelines from first thought to decision, and codes the forces that drive and block switching. For feature prioritisation it builds a job map with measurable outcome statements and opportunity scores, then turns every finding into a specific roadmap, positioning or messaging decision.

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description: Applies Jobs-to-be-Done to product decisions - solution-free job statements, switch interviews that reconstruct real purchase timelines and the four forces of progress (push, pull, anxiety, habit), universal job maps, desired outcome statements, opportunity scoring for underserved outcomes, and turning findings into roadmap opportunities, positioning, and messaging, while avoiding the common misuses. Use when asked to run JTBD research, write job statements or job stories, plan switch or churn interviews, build a job map, define outcomes, explain why customers buy or leave, or position a product against non-obvious competitors.

Try asking

  • Write a switch interview script for customers who moved to us from spreadsheets
  • Turn these five interview transcripts into job statements and the four forces
  • Build a job map and outcome statements for how finance teams close the month

Use it when

  • You need to know why customers buy, switch, or churn
  • Positioning or messaging feels feature-led and generic
  • Prioritising features against measurable customer outcomes
  • Competitors are unclear because people use spreadsheets or do nothing

Skip it when

  • You need an opportunity solution tree or cheap assumption tests — use product-discovery instead
  • You already have transcripts and want general themes and insights — use user-research-synthesis instead

How to check the result

Every job statement is solution-free with a circumstance and an executor, each job and force cluster shows how many distinct interviews support it, and each finding names the decision it changes.

The common mistake it prevents

Writing a feature as a job, such as 'get AI meeting summaries', and then using it to justify the roadmap the team had already chosen.

~/.claude/skills/jobs-to-be-done/SKILL.md

--- name: jobs-to-be-done description: Applies Jobs-to-be-Done to product decisions - solution-free job statements, switch interviews that reconstruct real purchase timelines and… license: MIT ---

JTBD work is done well when the job is stated without any product or solution in it, it is backed by real switching stories rather than opinions, the forces that block switching are known as well as the ones that drive it, and the findings change a concrete decision: what to build, whom to target, what to say, or what to stop doing.

Ground rules

  • A job is the progress a person is trying to make in a circumstance. It is stable over time and independent of any product. “Use our dashboard” is not a job; “know which shipments will be late before the customer does” is.
  • Evidence comes from what people did, not what they say they want. Interview about a specific past switch, never about hypothetical futures.
  • The competition is whatever people hire for the job today, including spreadsheets, an intern, a consultant, or doing nothing.
  • Pick one school per project and say which: switch / progress (Christensen, Moesta: why people change, forces, timeline; best for positioning, messaging, adoption) or outcome-driven (Ulwick, ODI: job maps and measurable outcomes; best for prioritising features in a known market). Mixing vocabularies confuses the team.
  • JTBD is a lens, not a replacement for usability testing, analytics, or experiments.

Choose the method

Decision to makeMethodOutput
Why do people buy, switch to, or churn from us?Switch interviewsTimeline, forces, job statements per segment
How should we position and message?Switch interviews + competing solutionsJob-based positioning, struggling moments, triggers
Which parts of the job are poorly served?Job map + outcome statementsMap of steps with outcomes
Which outcomes to prioritise, with numbers?Outcome survey + opportunity scoringRanked underserved outcomes by segment
Is a new market worth entering?Job map of the core job across current solutionsWhere all current solutions struggle

For general discovery (opportunity solution trees, assumption tests), use product-discovery; for synthesising existing transcripts into themes, use user-research-synthesis.

Workflow

- [ ] 1. Name the decision the research must inform and the school you will use
- [ ] 2. Define the job executor and draft a hypothesis job (solution-free)
- [ ] 3. Recruit recent switchers (to, away, and non-switchers who looked)
- [ ] 4. Run switch interviews and/or job-map interviews
- [ ] 5. Code forces or outcomes per interview; cluster across interviews
- [ ] 6. Write final job statements with evidence counts
- [ ] 7. Translate into opportunities, positioning, and specific decisions

Job statements

Formats; pick one and use it consistently:

Job (core functional): <verb> + <object> + <contextual clarifier>
  "Get paid for completed client work"            (not "send invoices in our app")

Job story (switch school): When <situation>, I want to <motivation>, so I can <expected outcome>.
  "When a client pays late, I want to chase it without souring the relationship,
   so I can keep cash steady and keep the client."

Quality checks for a job statement:

CheckFailsPasses
Solution-free“Track time with a mobile app”“Know how many billable hours I worked this week”
Stable over decades“Post on Instagram”“Keep customers thinking of my shop”
Has a circumstance“Manage money”“When income varies month to month, cover fixed bills”
Executor is clear“Users want reporting”“Ops manager at a 40-person e-commerce firm”
Includes the why“Export CSV”“…so I can show leadership the numbers before they ask”

Also capture emotional and social dimensions (“look in control in front of the COO”) and related jobs (the jobs before and after the core one). These often explain choices that features cannot.

Switch interviews and the four forces

Reconstruct the timeline from first thought to purchase, then code four forces:

ForceDirectionQuestion that surfaces it
Push of the situationToward change“What was going wrong? What happened that day?”
Pull of the new solutionToward change“What did you picture being different after?”
Anxiety of the newAgainst change“What worried you about switching? What almost stopped you?”
Habit of the presentAgainst change“What did you like about the old way? What did you have to give up?”

A switch happens only when push plus pull outweigh anxiety plus habit. Most teams invest only in pull (features); many losses are caused by unaddressed anxiety (migration risk, looking foolish, team adoption) and habit.

For the full script, timeline stages, and the per-interview coding card, read references/switch-interview-guide.md before planning or running interviews.

Job maps (outcome-driven school)

Map the core job as steps the executor goes through, independent of any solution. Ulwick and Bettencourt’s universal job map has eight steps:

Define → Locate → Prepare → Confirm → Execute → Monitor → Modify → Conclude
Example job: "Prepare a monthly financial close" (finance controller)
Define:   determine which accounts and entities are in scope this month
Locate:   gather bank statements, invoices, payroll reports
Prepare:  reconcile and categorise transactions
Confirm:  verify balances tie out before posting
Execute:  post journal entries and close the period
Monitor:  check for late adjustments and variances
Modify:   correct errors and re-run reports
Conclude: lock the period and distribute reports

Not every job uses all eight steps and some repeat; the map is a checklist for missed steps, not a template to force-fit.

Outcome statements

For each step, collect desired outcomes as measurable statements:

<direction> + <metric> + <object of control> + <contextual clarifier>
Minimize the time it takes to match bank transactions to invoices when amounts differ slightly
Minimize the likelihood of posting an entry to the wrong period

Rules: direction is minimise (occasionally maximise), metric is time, likelihood, or number; no solutions, no adjectives like “easy” or “intuitive”; one outcome per statement.

Opportunity scoring

Survey a representative sample of job executors on each outcome: importance and current satisfaction, typically on a 5-point scale. Convert each to the share rating 4 or 5 (top-two-box), scaled 0 to 10, then:

Opportunity = Importance + max(Importance - Satisfaction, 0)

High importance with low satisfaction marks underserved outcomes (build here); low importance with high satisfaction marks overserved ones (room for simpler, cheaper offerings). Rank relatively within the study and look for segments that score differently; the segment split is often the most useful finding.

From findings to decisions

FindingDecision it should drive
Strong push, weak pullMessaging should name the struggling moment; the product is not yet clearly better
Anxiety blocks trialsReduce risk: migration help, free import, guarantees, references from similar customers
Habit blocks adoptionMake the switch small: keep familiar formats, import existing work, incremental rollout
Event 1 / Event 2 patternsTime sales and marketing to the trigger (new hire, audit, quarter-end)
Competing solution is non-consumptionMarket to people doing nothing; compare against the manual way, not competitors
Underserved outcomes cluster in one stepRoadmap theme for that step; success metric is the outcome statement
Overserved outcomesSimplify, unbundle, or offer a lower tier

Positioning built on the job:

For <executor> who <struggling moment / push>, <product> is the <frame of reference>
that <progress made>. Unlike <what they hire today>, it <the difference that resolves anxiety or habit>.

Common misuses

  • Job statements that are features in disguise: “Get AI summaries of meetings.” Ask “why?” until the product disappears.
  • Personas renamed as jobs: demographics do not cause purchases; circumstances do.
  • Asking customers what their job is: they answer with features. Infer the job from the switching story.
  • Too broad: “Be more productive” cannot guide a decision. Too narrow: “Click export”. Aim for a job an executor would recognise and a team could design for.
  • Only interviewing happy customers: switchers away and people who looked but stayed explain the forces against you.
  • Counting mentions instead of people: one talkative participant is still one data point.
  • Research with no decision attached: if no finding could change the plan, do not run it.
  • Treating outcome survey scores as precise: small samples and mixed segments give noisy rankings; report sample size per segment.

Verification

  • Every job statement passes the quality table (solution-free, circumstance, executor, why).
  • Each job and force cluster lists the number of distinct interviews supporting it, with quote references.
  • Forces against switching (anxiety, habit) are recorded for every interview.
  • Outcome statements follow the direction-metric-object-clarifier format with no solutions.
  • Each finding maps to a named decision or open question; unsupported claims are cut.

Output contract

# JTBD findings: <product / segment> — <dates>
Decision informed: <...>   School: switch | outcome-driven   Interviews: <n by segment>

## Jobs (ranked by evidence)
### Job 1: <statement>  (<n> of <N> interviews)
- Executor and circumstance:
- Emotional / social dimensions:
- Competing solutions hired today:
- Forces: push / pull / anxiety / habit (with quote refs)
- Triggers: Event 1 / Event 2 patterns

## Job map and underserved outcomes (if outcome-driven)
| Step | Outcome statement | Importance | Satisfaction | Opportunity | n |

## Implications
| Finding | Decision / recommendation | Owner |

## Open questions and next research

Bundled files

Loaded only when a step in the skill needs them. Review them here before installing.

references/switch-interview-guide.md 121 lines · 5.8 KB
# Switch interview guide

Read this when planning, running, or coding a switch interview. A switch interview
reconstructs one real purchase or switching decision as a timeline, then extracts the
forces that caused it. It is a story about the past, told in detail, not an opinion survey.

## Recruiting

- Recruit people who **recently** switched: bought, signed up, upgraded, cancelled, or
  moved to a competitor. Recency matters because memory of the struggle fades; within the
  last few months is a practical target.
- Include both directions: people who switched to the product and people who switched away
  or chose something else. Non-buyers who looked and stayed with the old way are valuable.
- Talk to the person who made the decision, plus the user if different (B2B often has both).
- Plan 8 to 12 interviews per segment; stop when new interviews stop adding new forces.
- 45 to 60 minutes, recorded with consent, two interviewers (one leads, one notes forces).

## Timeline stages

Use these stages (from the Re-Wired Group / jobstobedone.org timeline) as the spine:

1. **First thought**: the first moment they realised the current way was not good enough.
2. **Passive looking**: noticing alternatives without acting.
3. **Event 1**: something that turned noticing into looking (a deadline, a failure, a new boss).
4. **Active looking**: researching, comparing, trialling, asking people.
5. **Event 2**: what made them decide now (budget approved, trial ending, crisis).
6. **Decision, purchase, and consumption**: choosing, buying, first use, and what they
   expected versus what happened.

## Script

Open (2 minutes):

```text
We're trying to understand how people decide to start using tools like this. There are
no right answers. I'll ask about small details; that helps us understand the decision.
```

Anchor the purchase (5 minutes):

- When did you sign up / buy? What day of the week was it? Where were you?
- Who else was involved? Who paid?
- What did you use before? What else did you consider?

Go back to the first thought (10 minutes):

- When did you first realise you needed something different? What was happening?
- What were you doing at the time? What had just gone wrong?
- How were you handling it before? What did that cost you (time, money, embarrassment)?

Passive and active looking (15 minutes):

- After that, what did you do? Did you start looking straight away? Why or why not?
- What happened that made you actually start looking? (Event 1)
- Where did you look? Who did you ask? What did you try first?
- What made you rule options out? What almost stopped you?

Deciding (10 minutes):

- What made you decide that day rather than the week before or after? (Event 2)
- What were you worried about when you signed up? What did you do about the worry?
- What did you expect would be different after switching?

Consumption (5 minutes):

- What happened the first time you used it? Did it match what you expected?
- What did you stop doing, or stop using, because of it?

Close (3 minutes):

- If you had to explain to a colleague why you switched, what would you say?
- Is there anything about the decision we did not ask about?

## Interviewing technique

- Ask for specifics: dates, places, people, numbers, the exact words used in a meeting.
  Specific detail jogs real memory and exposes rationalisation.
- When an answer is general ("we needed better reporting"), ask "Tell me about the last
  time that was a problem" until you get a concrete episode.
- Reflect contrasts: "So it wasn't price, it was the fact that your boss saw the error?"
  People correct wrong summaries readily, which surfaces the real cause.
- Never pitch, defend the product, or explain features during the interview.
- Note emotional language (embarrassed, relieved, scared, annoyed); those mark the forces.

## Coding the forces

After each interview, fill one card:

```markdown
## Interview P07 — switched from spreadsheets to <product>, Mar 2026, ops manager, 40-person company
Timeline: first thought (Nov: missed shipment, customer escalation) → passive looking
(saw competitor demo at a meetup) → Event 1 (Jan: new COO asks for weekly on-time report)
→ active looking (trialled 2 tools, asked peers on Slack) → Event 2 (quarter-end review
date set) → decision (bought annual plan; integration with Shopify was the tiebreaker).

Push (situation): "I spent Friday afternoons rebuilding the same report"; missed shipment visible to the customer
Pull (new solution): "I pictured walking into the Monday meeting with the numbers already there"
Anxiety (new): data migration would break order history; team would not adopt it
Habit (present): team already knew the spreadsheet; macros the founder wrote
How anxiety was resolved: vendor imported 6 months of orders during the trial
Job statement: When the leadership team asks how operations are doing, I want reliable
numbers without rebuilding them by hand, so I can look in control and fix problems before customers notice.
Competing solutions considered: spreadsheet + macros, hiring a part-time analyst, competitor X
```

## Cross-interview analysis

1. Put every force from every card on a board, grouped by force type.
2. Cluster similar forces; count interviews per cluster (people, not mentions).
3. Look for patterns in Event 1 and Event 2: these are the moments marketing and sales
   should meet.
4. Group interviews whose push and pull clusters match; each group is a candidate job.
5. Write one job statement per group with the evidence count, and list the anxieties and
   habits that nearly blocked the switch for that group.

## Red flags in your own data

- All forces are pulls about features: you interviewed about the product, not the struggle.
- No anxiety or habit recorded: you did not ask what almost stopped them.
- Every story starts at sign-up: you skipped the first thought.
- Only happy customers: you missed the people who looked and chose otherwise.

About this skill

Written and maintained by the Claude Skills editors to the same editorial standard as every skill in the directory: a selective trigger, a real workflow, known pitfalls and a verification step. First published , last updated . MIT licensed.

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