--- name: value-proposition-canvas description: "A two-sided customer-profile and value-map discipline: jobs, problems, and hoped-for benefits on one side; products & services, problem fixes, and benefit claims on the other — with any benefit claim that isn't actually proven yet visible for what it is, not dressed up as a settled fact. Use when: You have real, evidenced customer jobs, problems, and hoped-for benefits (a value hypothesis or CTQ tree is the natural upstream input) and want to check how tightly your actual offering maps onto them. Not for: You don't have real evidence of the customer's actual jobs, problems, and hoped-for benefits yet — a value hypothesis or discovery work first, then a map built from what it actually shows. You already have a message architecture built from the same evidence and just need the standing message, not a second diagnostic view — use that directly instead of duplicating the exercise." --- # Value proposition map A two-sided customer-profile and value-map discipline: jobs, problems, and hoped-for benefits on one side; products & services, problem fixes, and benefit claims on the other — with any benefit claim that isn't actually proven yet visible for what it is, not dressed up as a settled fact. Family: Problem definition · Format: .xlsx · Domain: commercial ## What it is A value proposition map is a one-page, two-sided picture: the customer's jobs, problems, and hoped-for benefits on one side, and your products & services, problem fixes, and benefit claims on the other — each problem fix and benefit claim naming exactly which problem or benefit it addresses, not a generic list of features. Real strength shows up as a tight match between the two sides; real weakness shows up as a problem or benefit with nothing genuinely addressing it, or a feature with no real customer problem or benefit underneath it to justify it. ## When to use it Use it when: - You have real, evidenced customer jobs, problems, and hoped-for benefits (a value hypothesis or CTQ tree is the natural upstream input) and want to check how tightly your actual offering maps onto them. - You want a second, complementary view of the same evidence a message architecture already organized as a tree — this one built to expose feature-market fit gaps a tree's own shape doesn't surface as directly. - You want to see honestly which problem fixes and benefit claims are backed by real proof and which are still a hope. Not when: - You don't have real evidence of the customer's actual jobs, problems, and hoped-for benefits yet — a value hypothesis or discovery work first, then a map built from what it actually shows. - You already have a message architecture built from the same evidence and just need the standing message, not a second diagnostic view — use that directly instead of duplicating the exercise. ## How to fill it in - **customer-jobs** — What is the buyer actually trying to get done? - **customer-pains** — What's getting in the way, or making it worse? Grounded in real evidence, not a guess. - **customer-gains** — What outcome would make this a clear win for the buyer? - **products-services** — What do you actually offer that touches these jobs? - **pain-relievers** — How specifically does what you offer remove or ease a named pain? Name the pain it addresses, not a generic benefit. - **gain-creators** — How specifically does what you offer produce a named gain? Name the gain it addresses, and whether it's actually proven yet. ## What good looks like The example below organizes the exact same evidence the message architecture and value hypothesis worked examples already established for Beacon Analytics — the same three needs, the same 48-hour and $310K figures — as a two-sided map instead of a tree, and is honest that the weakest column (spreadsheet trust) still has no real benefit claim behind it. Full worked example, on-screen and as a downloadable .xlsx: https://www.katafacts.com/katas/value-proposition-canvas ## Common mistakes - **Listing a problem fix or benefit claim that doesn't actually name which problem or benefit it addresses.** — A feature floating with no named pain or gain underneath it is exactly the mismatch this map exists to expose — every entry on the value-map side should trace to a specific entry on the customer side. - **Writing benefit claims as aspirations rather than proven results.** — The whole value of this map is seeing which parts of the offer are actually proven — treating a hope as a proven benefit hides the exact gap a consistency audit would later need to catch. - **Filling in the value-map side before the customer side is grounded in real evidence.** — A map built from an assumed persona's jobs and pains produces a confident-looking match that isn't actually testing anything real — start from real discovery or a value hypothesis, not a guess. ## What it connects to Upstream: - **Message architecture** (`message-architecture`) — The same needs and proof points a message architecture organizes as a tree are what this map maps as jobs, problems and hoped-for benefits versus problem fixes and benefit claims — two views of one set of evidence, not two separate sources of truth. - **Value hypothesis** (`value-hypothesis`) — A deal-specific value hypothesis that's actually worked is real evidence for this map's customer-side entries — not invented from an assumed persona. ## Where AI helps Judgement — stays with you: - Deciding whether a problem fix genuinely addresses the problem it's paired with, or just sounds related - Deciding whether a benefit claim is actually proven or still an unproven hope Analysis — AI helps: - Drafting each section's bullets from a rough description or real deal evidence - Flagging a section that's too thin to mean anything yet, rather than padding it Drudgery — automated: - Formatting the map and keeping every section on one page - Exporting to xlsx in the house format --- Value proposition map is licensed [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). Attribution: Katafacts (katafacts.com). ## Using this skill Apply this method as part of whatever broader task, instructions, or deliverable you're already working on -- it's a method to use, not a standalone conversation to start. There is no generation tool for this catalogue yet, so draft the artifact's actual content yourself, following the fields above, the same way a person filling this out by hand would. The canonical guide page and a downloadable worked example (.xlsx) are at https://www.katafacts.com/katas/value-proposition-canvas.