Ripplux

A Shopify merchant running paid channels gets a different answer about what worked from every dashboard they open. Each platform claims the same sale, and the totals never add up to what the bank account says.

Spend decisions get made anyway, on the least bad numbers available. The merchant knows the attribution is wrong; what they do not have is a better option.

Early merchant outreach and user research ran alongside development from the start, not ahead of it. Conversations with store operators shaped what the product owed them while the product itself was being built.

The positioning decision: the dashboard answers the question a store operator actually asks — where the next dollar of ad spend goes — rather than exposing every dimension an analyst might want.

Multi-touch attribution data sits underneath. What was deliberately left out is everything an operator would not act on.

The information architecture turns multi-touch attribution data into a layout a non-technical store operator can read at a glance: what came in, which channels earned it, and what to do next.

Conceived, designed and built solo: problem discovery, research, information architecture, interface design and product strategy. Shipped iteratively, with each release narrowing the gap between the data and the decision.

Ripplux is live, helping Shopify merchants improve ad-attribution accuracy across paid channels. The work now is what it was at the start: listening to operators and taking away everything that is not the answer.