Navigation strategy (Lucid Maps)

Summary

A multi-phase strategy effort that translated an ambiguous starting point into an AI-forward navigation roadmap, anchored by a global concept evaluation of more than 350 participants across nine candidate concepts and five audience segments. I led the workshops, designed the evaluation methodology, authored the synthesis and recommendations, and shaped the resulting product pillars.

The starting condition

A common situation in product organizations: the team knows a product area needs to evolve, but no one knows in which direction. Multiple plausible roadmaps. No principled way to choose between them.

Navigation in 2025 was at exactly this point. The next generation of in-car navigation could go in many directions, toward AI trip planning, toward cross-device continuity, toward parking and arrival experiences, toward 3D and AR visualization, toward autonomy integration. Several of these would compound on each other. Several would conflict. The question wasn’t which features to build; it was which categories of capability the platform should organize itself around.

The framework

The work followed a structure I’ve used variations of across several product areas: stakeholder workshop to map the problem space, concept generation across an opportunity map, structured concept evaluation with real users, synthesis into roadmap pillars.

The workshop produced nine candidate concepts, spanning the range from incremental improvements to next-generation directions. The next question was how to evaluate them in a way that would actually inform a roadmap rather than produce a pile of survey data.

The evaluation

The evaluation combined a quantitative survey of more than 350 participants with open-text analysis and 1:1 interviews. A few design choices did the real work:

Five audience segments spanning the EV adoption spectrum, from EV drivers to less-tech-fluent passengers, so the synthesis could ask not just whether a concept was desirable but to whom.

Four concept metrics (desirability, purchase influence, uniqueness, usefulness) chosen to separate whether something is attractive from whether it actually changes behavior.

A $100 investment-allocation exercise that made participants distribute a fixed budget across the nine concepts, forcing real tradeoffs rather than isolated ratings.

A three-lens feature-level evaluation (use likelihood, standout appeal, irrelevance) that surfaced patterns within concepts: breakout features, and strong features buried inside concepts that underperformed overall. It let good features survive a weak parent concept.

What came out of it

Of the nine concepts, four emerged as universally validated across all five segments, and those four anchored the AI-forward direction of the resulting roadmap. Five concepts were polarizing or underperformed at the concept level, but the feature-performance analysis surfaced specific features inside them worth elevating separately.

The synthesis fed directly into product direction: the validated concepts became foundational pillars of the navigation roadmap.

Validating the direction is cheaper than building the wrong thing

Strategy work at this stage isn’t really research, and it isn’t really product. It’s the structured conversion of ambiguity into a defensible direction. The most useful thing a senior researcher can do at this point in a product’s lifecycle is to bring a framework that’s rigorous enough to be trusted and flexible enough to actually fit the question.

For AI-forward navigation specifically, the cost of building the wrong thing is high. The candidate directions were all expensive bets if pursued, and they didn’t all compound. Validating the direction before the engineering commitment was the part that mattered.