Jobs to Be Done Framework
Framework for discovering innovation based on a fundamental truth: customers don't buy products -- they "hire" them to do a specific job in their lives.
Core Principle
Job to Be Done = the progress a customer wants to make in specific circumstances.
Key elements of the definition:
- Progress (not goal, not solution) -- the customer wants to move from the current state to a better one
- Circumstances -- context determines the job, not customer attributes (demographics are useless)
- Hiring/Firing -- the customer actively chooses a product for the "job"
Scoring
Goal: 10/10. Score 1 point per satisfied row in the Quick Diagnostic (7 rows) plus up to 3 points for depth: +1 if all three job dimensions are evidenced, +1 if the job statement avoids any product/solution name, +1 if competition includes non-consumption. Bands: 9-10 = job stated without the product, all four forces mapped, three dimensions evidenced, non-obvious competition and Little Hire tracked; 5-6 = job named but one or two diagnostic rows fail (usually missing forces or emotional/social dimensions); <=3 = product-first framing, demographic segmentation, or Pull-only thinking. Always state the current score and the specific diagnostic rows to fix.
Three Dimensions of Every Job
Every job has three inseparable dimensions -- omitting any means failure:
| Dimension | Question | Example (milkshake) |
|---|---|---|
| Functional | What does the customer need to do? | Occupy myself during a boring commute |
| Emotional | How do they want to feel? | Have a small treat for myself |
| Social | How do they want to be perceived? | As a sensible parent (not buying donuts) |
Framework
1. The Job Statement
Core concept: A job statement captures the progress a customer seeks in a specific circumstance, in a structured format separating context, desired progress, and expected outcome.
Why it works: Because jobs are stable while solutions churn, anchoring on the job protects a roadmap from chasing features that the next technology shift makes irrelevant.
Key insights:
- Format: "When [circumstances], I want to [progress], so I can [outcome]"
- Circumstances matter more than demographics -- the same person has different jobs in different situations
- A well-written job statement never mentions your product or any specific solution
- Jobs are stable over time; solutions change but the underlying job persists
Product applications:
| Context | Application | Example |
|---|---|---|
| New product ideation | Define the job before brainstorming features | "When I'm commuting alone, I want something to occupy me and satisfy hunger, so I'm not hungry until lunch" |
| Feature prioritization | Evaluate whether a feature serves the core job | Features that advance the stated job beat nice-to-haves |
| Positioning & messaging | Use job statement language in copy | Lead with circumstance and progress, not product specs |
Copy patterns:
- "When you're [circumstance], you need [progress] -- that's exactly what [product] does"
- Lead with the situation the customer recognizes, not the product category
- Mirror the emotional and social dimensions alongside the functional one
See references/innovation-process.md when running an innovation project end-to-end -- the job-hunting methodology, the job atlas, and fill-in statement templates.
2. Forces of Progress (Push, Pull, Anxiety, Habit)
Core concept: The decision to "hire" a new product results from four forces: Push (frustration with the current situation), Pull (attraction of the new solution), Anxiety (fear of the new), and Habit (comfort with the current behavior). Change happens only when Push + Pull > Habit + Anxiety.
Why it works: Most innovation efforts only increase Pull while ignoring the anti-change forces -- which is why great products still fail to gain adoption.
Key insights:
- Push: "this annoys me"; Pull: "I want this"; Habit: "I've always done it this way"; Anxiety: "what if it doesn't work?"
- Reducing anxiety and habit is often more effective than increasing push and pull
- Passive seekers (vaguely aware of a problem) are easier to influence than active seekers who already have criteria
Product applications:
| Context | Application | Example |
|---|---|---|
| Onboarding design | Reduce anxiety with trials, guarantees, social proof | Money-back guarantee answers "what if it doesn't work?" |
| Switching campaigns | Make migration effortless to defeat habit | One-click data import from competitor |
| Content marketing | Awaken push in passive seekers by naming the frustration | "5 signs your current tool is costing you hours every week" |
Copy patterns:
- Address anxiety directly: "No lock-in, cancel anytime, your data is always yours"
- Name the push: "Tired of [frustration]? There's a better way"
- Reduce habit friction: "Switch in 5 minutes -- we import everything automatically"
See references/competitive-strategy.md when mapping competitors or writing positioning -- forces analysis, the non-obvious-competition tables, and the jobs-based positioning formula with worked examples.
3. The Big Hire & Little Hire
Core concept: Two distinct decision moments: the Big Hire (purchase/signup, happens once) and the Little Hire (decision to use in the moment, happens repeatedly). Winning the Big Hire does not guarantee the Little Hire.
Why it works: Many products win the sale but lose the customer because they optimize only the purchase decision -- understanding both moments reveals where retention problems truly originate.
Key insights:
- Big Hire is driven by marketing, onboarding, and first impressions; Little Hire by product quality, UX, and ongoing value
- Big Hire anxiety is purchase risk; Little Hire anxiety is effort and learning curves
- Retention problems are almost always Little Hire failures -- purchased but never used
Product applications:
| Context | Application | Example |
|---|---|---|
| Retention analysis | Separate Big Hire from Little Hire metrics | Track "first use after signup" and "weekly active usage" apart from signup conversion |
| Product design | Optimize repeated usage, not just first impressions | Reduce daily-workflow friction even when onboarding is smooth |
| Customer success | Monitor Little Hire signals to predict churn | Declining usage frequency signals upcoming churn |
Copy patterns:
- Big Hire copy sells the promise: "Transform how you [job]"
- Little Hire copy sells ease: "One click and you're done"
- Re-engagement copy addresses the failure: "We've made [specific friction] easier"
See references/case-studies.md when you need a worked precedent to reason from -- full Big Hire / Little Hire breakdowns of SNHU, American Girl, and Intuit.
4. Competitive Landscape (Non-Obvious Competition)
Core concept: True competition is everything a customer can "hire" for the same job, often from completely different categories. Competitors are defined by the job, not by industry classification.
Why it works: Category-based analysis creates blind spots: a milkshake competes with bananas, bagels, and podcasts; Netflix competes with TikTok, sleep, and family conversation. Mapping the full landscape around the job reveals threats and opportunities traditional analysis misses.
Key insights:
- Non-consumption (doing nothing) is often the biggest competitor
- Workarounds and compensating behaviors reveal unserved jobs -- people hack, combine, and improvise
- Integrate where performance is "not good enough" for the job; modularize where it's "good enough"
- The best positioning answers "what job are we the best hire for?", not "how do we compare to similar products?"
Product applications:
| Context | Application | Example |
|---|---|---|
| Competitive analysis | Map all hires for the same job across categories | A PM tool competes with spreadsheets, sticky notes, email, and memory |
| Positioning strategy | Position against the real alternative | Position against "doing it manually", not a named competitor |
| Pricing strategy | Price against the job's value | If the job saves 10 hours/week, price against that time, not similar SaaS |
Copy patterns:
- "Stop using [workaround] for [job] -- there's a purpose-built solution"
- "You wouldn't hire a [bad fit] to [job] -- so why are you using [current hack]?"
- Position around the job outcome, not feature comparison charts
5. Customer Discovery Interviews
Core concept: Don't ask customers "what do you need" -- they don't know. Instead, reconstruct the purchase timeline (first thought, search, purchase, usage) to uncover the real job.
Why it works: Customers rationalize decisions after the fact and can't articulate latent needs; walking backward through concrete events reveals the true circumstances, forces, and tradeoffs that drove behavior.
Key insights:
- First thought: "When did you first look for a solution? What was happening in your life? What frustrated you?"
- Search: "What alternatives did you consider? What eliminated options? Who did you talk to?"
- Purchase: "Where were you? What ultimately convinced you? What were you afraid of?"
- Usage: "Is it doing what you expected? What surprised you? What's still missing?"
- Signals of undiscovered jobs: workarounds, non-consumption, compensating behaviors, negative emotions toward current solutions
- Ask only about past events, never hypotheticals ("would you...", "do you wish...") -- a question that names your solution or a benefit leads the subject and produces confirmation, not discovery
Product applications:
| Context | Application | Example |
|---|---|---|
| New market entry | Interview recent switchers | Reconstruct what pushed them away and pulled them in |
| Churn reduction | Interview churned customers on their timeline | Was it Big Hire (wrong expectations) or Little Hire (poor daily experience)? |
| Feature discovery | Interview customers using workarounds | Spreadsheets alongside your product reveal an unmet job dimension |
Copy patterns:
- Use exact customer language from interviews in marketing copy
- "We heard you say [verbatim quote] -- so we built [feature]"
- Frame benefits in the circumstances and emotions customers actually described
6. Designing for the Job
Core concept: Build the entire experience -- features, metrics, organization -- around helping the customer accomplish their job, not around internal capabilities or feature parity.
Why it works: When every decision answers "will this help the customer better accomplish their job?", teams avoid feature bloat and build coherent products; if you can't answer it, you don't understand the job yet.
Key insights:
- Replace customer satisfaction metrics with "did the job get done?"
- Replace NPS with "reasons for hiring and firing"; replace feature usage with "progress on the job"
- Organize teams and processes around jobs, not internal capabilities or product components
Product applications:
| Context | Application | Example |
|---|---|---|
| Metrics design | Measure job completion | "Time from problem to resolution", not "features used per session" |
| Product roadmap | Prioritize across job dimensions | A functional fix that ignores the emotional dimension may not move the needle |
| Organizational alignment | Structure teams around jobs | A "morning commute job" team owns content, packaging, and distribution |
Copy patterns:
- "Built for [the job], not for [the category]"
- "Everything you need to [job] -- nothing you don't"
- Emphasize outcome and progress, not features and specifications
See references/organizational-change.md when adoption is the bottleneck rather than the analysis -- escaping the feature-factory trap, winning executive buy-in, and managing the change.
Common Mistakes
| Mistake | Why It Fails | Fix |
|---|---|---|
| Defining jobs narrowly around your product | Misses the real competitive landscape | Define the job from the customer's perspective, never mentioning your product |
| Ignoring emotional and social dimensions | Functional-only jobs miss why customers choose and stay | Always complete all three dimensions |
| Confusing jobs with goals or tasks | Goals too abstract ("be healthy"), tasks too specific ("click button") | Jobs = progress in specific circumstances |
| Only increasing Pull | Great products fail when switching costs and fear stay high | Map all four forces; design interventions for Anxiety and Habit |
| Winning the Big Hire, ignoring the Little Hire | High acquisition, high churn -- purchased but never used | Track and optimize repeated usage separately from purchase |
| Asking customers "what do you want?" | Rationalization and incremental feature requests | Use timeline-based interviews reconstructing actual behavior |
| Defining competition by category | Blind spots from adjacent categories and non-consumption | Map every alternative hire for the job, including doing nothing |
Quick Diagnostic
| Question | If No | Action |
|---|---|---|
| Can you state the job in one sentence without mentioning your product? | Product-focused, not job-focused | Write: "When [circumstances], I want to [progress], so I can [outcome]" |
| Have you mapped all four forces? | Over-investing in Pull, ignoring barriers | Design specific interventions for Anxiety and Habit |
| Do you know the emotional and social dimensions? | May win functionally but lose on experience | Run discovery interviews on feelings and social context |
| Have you identified non-obvious competitors? | Competitive blind spots | List everything hireable for the job, including non-consumption |
| Are you tracking Little Hire separately from Big Hire? | Can't tell acquisition problems from retention problems | Separate purchase-conversion and repeated-usage metrics |
| Can your team explain how each feature serves the job? | Building without strategic grounding | Require proposals to name the job dimension served |
| Have you interviewed customers about their purchase timeline? | Job understanding based on assumptions | Run 10+ interviews reconstructing first-thought-to-usage |
When the inline Quick Diagnostic above is not enough -- you are diagnosing a symptom (low signups, high churn, "used wrong") or need JTBD-specific metrics -- see references/diagnostics.md: the "why aren't they buying" symptom table, churn-pattern tables, and traditional-vs-JTBD metric swaps.
Further Reading
For the complete methodology, case studies, and deeper insights:
- "Competing Against Luck: The Story of Innovation and Customer Choice" by Clayton M. Christensen, Taddy Hall, Karen Dillon, and David S. Duncan
About the Author
Clayton M. Christensen (1952-2020) was the Kim B. Clark Professor of Business Administration at Harvard Business School, best known for the theory of disruptive innovation introduced in The Innovator's Dilemma (1997). He developed Jobs to Be Done as a practical innovation methodology in Competing Against Luck (2016) and was repeatedly ranked the world's #1 management thinker by Thinkers50.
