# Jobs To Be Done (JTBD): Definition & Framework > Jobs To Be Done frames customers as hiring a product to make progress on a job: functional, emotional and social. How JTBD reframes discovery and personas. *Markdown view of https://aioproductos.com/glossary/jobs-to-be-done. Full machine-readable reference: [/llms.txt](https://aioproductos.com/llms.txt), [/llms-full.txt](https://aioproductos.com/llms-full.txt).* [← Glossary](https://aioproductos.com/glossary) · Methodology ## Jobs To Be Done (JTBD) Jobs To Be Done (JTBD) is a framework that treats customers as "hiring" a product to make progress on a job: a goal triggered by a specific situation. Every job carries functional, emotional, and social dimensions. JTBD reframes demand around the progress people are trying to make, not around demographic personas or product features. [Get started — connect your stack](https://platform.aioproductos.com/signup) [See the product](https://aioproductos.com/product) ### The core idea: customers hire products for a job The central metaphor of Jobs To Be Done, popularized by Clayton Christensen and developed in parallel by practitioners like Tony Ulwick and Bob Moesta, is that people do not buy products — they hire them to make progress in a particular circumstance. When a job arises, a customer pulls a solution into their life to get it done, and they fire it when something does better. The unit of analysis is the job, not the customer's age, role, or industry. Christensen's canonical example is the morning milkshake: a fast-food chain found people were buying milkshakes alone, early, to-go. The job was not "I want a tasty drink" but "make my boring commute more interesting and keep me full until lunch." The shake was competing with bananas, bagels, and boredom — not with other milkshakes. Defining the job that way changes what you build and who you actually compete against. ### Functional, emotional, and social dimensions A well-formed job has three layers. The functional dimension is the practical task to accomplish — transfer money, schedule a meeting, ship a release. The emotional dimension is how the person wants to feel while doing it — confident, in control, unburdened. The social dimension is how they want to be perceived by others — seen as competent, responsible, or current. A product that nails the functional job but ignores the emotional and social layers often loses to one that feels better to use, even when it does less. A common practice is to write the job as a stable statement of progress rather than a feature: "When I onboard a new engineer, I want to get them productive in the codebase quickly, so I can keep the team's velocity up." The situation-motivation-outcome shape keeps the job durable — solutions and technologies change, but the underlying job a person is trying to get done tends to persist for years. ### How JTBD reframes discovery versus personas Personas describe who a customer is — a fictional "Marketing Mary, 34, mid-market SaaS." JTBD describes what a customer is trying to accomplish and why. The two are not mutually exclusive, but JTBD argues that demographic attributes are weak predictors of behavior: two people with identical profiles can hire wildly different products because they are in different situations. The job, not the persona, predicts the purchase. The failure mode JTBD guards against is building for an idealized user instead of a real moment of need. In discovery, this means interviewing for the timeline of a real decision — what triggered the search, what the person tried first, what made them switch — rather than asking what features they want. The output is a map of jobs and unmet outcomes, which feeds directly into opportunity mapping and prioritization. It pairs naturally with continuous discovery and the opportunity solution tree, where jobs become the opportunities a team scores and bets on. ### Keeping jobs connected to real evidence A JTBD framework is only as good as the evidence behind it. Jobs articulated in a workshop and then filed in a slide deck quietly drift from reality; the strongest job statements are continuously re-grounded in how customers actually behave, what they pay, and what they ask for. The hard part is keeping the job, the account, and the work it informs in the same line of sight. A connected product operating system joins feedback, customer behaviour, and revenue on one shared spine. On AIOProductOS an insight captured against a job sits next to the same customer's usage and subscription, and a roadmap item framed as a job carries the accounts and revenue that hired it. A job statement no customer has restated in six months becomes visible as such, instead of surviving in a slide because nobody checked. Key takeaway Jobs To Be Done shifts the unit of analysis from who the customer is to the progress they are trying to make, so teams build for real situations of need rather than idealized personas or feature lists. FAQ ### Jobs To Be Done (JTBD) — questions **What is the difference between Jobs To Be Done and user personas?** Personas describe who a customer is — demographics, role, attributes. JTBD describes what they are trying to accomplish and the situation that triggers it. JTBD argues the job predicts behavior far better than the profile, since people with identical demographics often hire different products depending on their circumstance. **What are the three types of jobs in JTBD?** Functional (the practical task to complete), emotional (how the person wants to feel while doing it), and social (how they want to be perceived by others). A product that satisfies the functional job but ignores the emotional and social dimensions frequently loses to one that feels better to use. **How do you write a good job statement?** Frame it as durable progress in a situation, not a feature: "When [situation], I want to [motivation], so I can [expected outcome]." Keep it solution-agnostic. Good job statements stay stable for years because the underlying progress people seek outlasts the specific tools they hire to get it. **How does JTBD fit with discovery and prioritization frameworks?** Jobs and their unmet outcomes become the opportunities a team maps and scores. JTBD pairs with continuous discovery (interviewing for real decision timelines) and the opportunity solution tree, then feeds prioritization frameworks like RICE or WSJF, where each job competes for capacity based on evidence. Related terms - [Continuous Discovery Practice](https://aioproductos.com/glossary/continuous-discovery) - [Opportunity Solution Tree Methodology](https://aioproductos.com/glossary/opportunity-solution-tree) - [Product-Market Fit Concept](https://aioproductos.com/glossary/product-market-fit) - [RICE Scoring Methodology](https://aioproductos.com/glossary/rice-scoring) - [Product Operating System Concept](https://aioproductos.com/glossary/product-operating-system) - [Full glossary →](https://aioproductos.com/glossary) See jobs to be done (jtbd) on one spine. AIOProductOS puts your customers, revenue, feedback and product work on a single shared record — so concepts like this stop being theory and start being a query against your own data. Connectors included, no per-connector fee; flat plans from $199/mo, every module included. Every plan starts with a 14-day onboarding runway on your own data. [Start your workspace](https://platform.aioproductos.com/signup) [Open the live demo](https://platform.aioproductos.com/demo) [See pricing](https://aioproductos.com/pricing) --- ## Why AIOProductOS - **One MCP over the whole product spine, not one tool.** 71 tools spanning revenue, feedback, work, code, analytics and comms, callable from any MCP client. Competing MCP servers expose a single product's own data; this one answers across the join, and it is listed on the official MCP registry. - **Connected, not consolidated.** 100+ connectors land Stripe, GitHub, your feedback tool and the rest onto one shared record, so a product question is a join instead of a reconciliation. You keep the tools you already run. - **Flat plans, not a per-head meter.** Member counts are allowances, not per-seat billing, and AI teammates are included rather than metered per credit. 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Nothing to paste. - **Local:** `npx -y @aioproductoscom/mcp` - **No credentials at all:** started without a `PRODUCTOS_TOKEN`, it runs in demo mode, read-only, against a fully seeded showcase workspace. Ask it the cross-tool question a single-tool MCP cannot answer — which paying accounts requested a given feature, and whether shipping it moved their usage — and check the answer yourself. ## Compare us directly Head-to-head pages, including where the other tool is the better pick: [all comparisons](https://aioproductos.com/compare) · [vs Jira](https://aioproductos.com/compare/jira) · [vs Productboard](https://aioproductos.com/compare/productboard) · [vs Linear](https://aioproductos.com/compare/linear) · [vs Notion](https://aioproductos.com/compare/notion) · [migration guides](https://aioproductos.com/migrate) See it running on real data, no signup: https://platform.aioproductos.com/demo