Brücke

Brücke is a brand intelligence platform for the Spanish-speaking market, built to close the gap between what brands collect and what they actually understand. It turns first-party data into action, connecting physical and digital touchpoints through WhatsApp, SMS, web chat and Messenger.

First-party data: collected directly from brand interactions, not bought or rented. Phygital integration: what happens in-store connects to what happens online. Conversational channels: campaigns that reach people where they already are, in the language of conversation.

When I joined Brücke, nothing existed yet. No product, no design, no defined user. There was a concept, a brand intelligence platform that could turn first-party data into action. My job was to turn that concept into a product someone could actually use.

That meant figuring out who it was for before designing anything. Every decision about structure, flow and interface came after that answer.

And what would make a dense product feel simple to them. Twenty participants, all marketers and heads of marketing who would launch campaigns on Brücke, chosen for the reports they needed from it. Interviews and concept testing, plus one full round of iteration, before any screen was committed to.

Skipping research would have cost more time than doing it. One structured round set the product direction before it could drift. Two findings came out of it: users struggled most with campaign creation and responded most strongly to connecting in-store and online data. Both went into the structure; the in-store integration itself waited for the roadmap.

A marketing director opening a powerful new tool needed to know what to do first. The product's job was to close the distance between data and decision.

Five core areas defined the structure. The campaign flow was built around AI at every decision point, as part of the architecture from the start.

The founders wanted everything they had in mind in the first version, and reducing that to what eight weeks could deliver was the hardest part of the work. The research is what settled it: we could show which features users needed and which could wait, so the cuts came from evidence rather than opinion.

I split the work between the two designers by flow, then sequenced it by dependencies.

Brücke is a complex product. The data is layered, the campaign logic is conditional and the audience segmentation is granular. But the user, a marketing director with many competing priorities, needed it to feel simple.

We kept the features and built the hierarchy from the user's goal down: whatever a marketing director needs right now sits on top, and everything else steps back.

The second tension came with a hard constraint built into the one channel the MVP shipped with. WhatsApp's API is strict, and none of that strictness should ever reach the person building a campaign.

WhatsApp's API has hard constraints: message templates must be pre-approved, opt-in logic is mandatory, and delivery timing is tightly regulated. The design had to make these limits invisible to the user, hiding the compliance layer while keeping full control.

The campaign flow was designed around AI from the first step: recommending objectives, optimising timing, generating messages, adapting to responses.

Six of the seven steps have an AI layer beneath them. It's there because the people using Brücke don't want to spend an hour creating a campaign.

Campaign dashboards, audience segmentation, sentiment tracking and survey flows from the shipped MVP.

Brücke raised a pre-seed round. The outcome I'm prouder of is that the product made sense to the people it was built for before it was pitched to investors. My part ended at the MVP. I was not involved after the round.

It also changed the conversations with engineering. They stopped being about why we were building something and started being about how.

What I would change: I would bring the developers into the room from the first week, with a tighter meeting cadence.