Last-touch attribution meant every program that nurtured a prospect along the way counted for nothing unless it was the final touchpoint before a deal closed. Marketing teams were investing across dozens of channels and programs with almost no reliable signal about what was actually working. There was no Program Effectiveness product, no framework, and no shared definition of what effectiveness even meant across the CMO, demand generation, and campaign management teams.

The hardest part was that nothing existed to design from. Three user groups, three different levels of analysis, three sets of questions — all needing to be served from one coherent product. Before a single wireframe was drawn, the framework had to be defined: what decisions does each user need to make, and what information do they need to make them confidently?

I started with discovery sessions across all three user groups. Five core questions emerged and became the product spec. EffectTrack was designed as one major section within a broader marketing analytics platform, with each of the five sub-tabs answering exactly one question for a specific audience.

For sub-tab 4, two complementary views were designed from the same underlying data: a Sankey chart for the visual multi-touch story, and a tabular view for campaign managers who needed specific numbers to take back to budget conversations.

The moment that stayed with me was when users saw channel and content broken out together for the first time.

Stakeholder usage increased 5x within the first quarter of launch, with all three user groups actively using the product for their own decisions. Program teams moved from defending budgets with anecdote to presenting pipeline contribution with data. The question stopped being "did this campaign work?" and started being "which combinations of this campaign worked, and how do we do more of that?" That shift — from outputs to decisions — is what good analytics products should do.