NavigatorLab

The problem

Demand space work is some of the most useful strategy work a brand team can buy. However, it usually arrives as a static chart inside a long consulting deck. Six months later the market has changed, the deck is out of date, and nobody can question the model behind it. The analysis was sound, but the deck it arrived in could not be used.

We built this tool because we kept meeting this problem on our own engagements.

The build

NavigatorLab maps a market in three connected lenses. Consumer typologies describe who is buying. Consumption occasions describe when and why. Demand spaces sit at the intersection: a typology meeting an occasion, with a market size, a growth score, and a brand fit assessment attached. Each occasion's measured share is also the weight we propose for synthetic persona research in Challenges With Synthetic Personas and Their Best Use Cases.

The platform handles the full workflow: building and editing typologies and occasions, generating the demand space grid, sizing each space, scoring growth potential, and assessing which spaces fit the brand well enough to act on. AI assists with research synthesis and generates imagery vivid enough for a creative team to work from. Finished maps share as live decks that stay current.

The workflow

The front end is Angular with D3 driving the interactive space visualisations. Gemini powers the AI research and image generation. Firebase handles auth and hosting, with PostgreSQL behind the data layer. A strategist can operate the platform end to end, because every model assumption is visible and editable in the interface.

The outcome

A demand space map used to take six to eight weeks to deliver on our engagements. It now takes a working session. Clients keep access to the live map after the engagement ends, so the model gets updated as the market moves. Our consultants work with instruments we built ourselves.

Further reading

For where NavigatorLab sits in the wider picture, read The Shift From Advice to Decision-Making Systems.