Dan Olsen's tool for turning Kano Model categorization into a strategic decision. Construction:
Reading the finished grid surfaces where your product is undifferentiated (matches on must-haves), where it's genuinely ahead (a performance row you outscore everyone on), and whether you have a delighter no one else offers. The intended output is a small, specific set of differentiators — typically one performance benefit to win plus one unique delighter — not a long feature list.
That output then feeds into the Lean Product Process: brainstorm solutions for the chosen benefit/delighter, spec an MVP, prototype, validate with customers, then build.
See Instagram's 2010 Strategy (Performance + Delighter Case Study) and Uber's Series A Positioning (Three-Dimension Case Study) for worked examples of the grid's output.
Rows are customer needs, already categorized via the Kano Model (must-have / performance / delighter) for a defined time frame. Columns are your product plus competitors — defined broadly in the spirit of Porter's alternatives/substitutes: any current way a customer meets the need, not just funded rivals (Excel, duct tape, a CSV export), similar in spirit to Competitive-Alternatives Mapping (Status Quo vs. Shortlist)'s status-quo-vs-shortlist framing. Cells score how well each competitor meets each need.
The output is a set of unique differentiators: find the performance row where competitors are weak or tied and commit resources there, plus any delighter unique to you. Olsen explicitly frames this as declining to fight a competitor's unbeatable strength and instead betting on the one dimension that's genuinely ownable. Feed the resulting strategy into the Lean Product Process to validate it before building.
A performance dimension's value to a given user scales with how often they'd invoke it, not just the per-unit improvement. Olsen's example: shaving 2 seconds off a Google search is worth roughly 100 seconds/day to a 50-query power user, but far less to someone who searches rarely — the same per-unit gain is worth more to heavier users of that dimension. When scoring a Product Strategy Grid, weight a performance win by the target segment's expected usage frequency, not just its raw magnitude.