Sami Surakka

Context

Market research studies on Cambri combine quant and qual data from hundreds to thousands of respondents. For the enterprise research teams using the platform, turning that data into a clear, persuasive narrative is slow work: a good report can take days. Cambri set out to change that by building a reporting feature that could help teams deliver a high‑quality report in roughly an hour, without sacrificing the depth and nuance they needed.

Solution

I started by running a workshop to align on goals, constraints, and perspectives from across the business. From there, I defined a high‑level vision for the feature: a WYSIWYG editor that can compile and pull in data from across the platform so researchers don’t have to jump between studies, export results, and manually stitch them together. I validated the vision with key clients before implementation and used ongoing interviews to keep our direction grounded in their day‑to‑day reporting realities.

Impact

The reporting editor shipped and is now in use. The reporting editor serves both Cambri's managed services team and client users across the platform. Because of the slow and cyclical nature of research work, the pure time‑saving effect has been harder to measure so far, but the feature has already enabled new sales to close by demonstrating how quickly Cambri can take teams from raw data to polished insight.

Role

As Lead Product Designer, I owned the design vision for the feature from discovery workshop through implementation. I partnered closely with customer success, managed services and engineering on scope and trade‑offs, and led client validation and interviews to ensure we were solving the right reporting problems, not just adding another editor.

Beyond design, I built a shared three-month roadmap in Miro and embedded it into weekly planning, replacing ad-hoc release visibility that rarely extended beyond one to two weeks. I introduced a prioritisation framework scoring items on customer value, business value, and technical feasibility, which gave the team a repeatable way to sequence work against delivery capacity. As the roadmap stabilised, review cadence naturally dropped from weekly to roughly every two to three weeks, which was itself evidence the model was working. I also initiated cross-functional collaboration rituals across engineering, product, customer success, managed services, and revenue operations. Customer success collaboration took longer to stick. My initial efforts did not gain traction until the CS team began driving the process themselves, reinforcing that cross-functional practices need co-ownership in the partner function to sustain.

Reflection

Adoption initially lagged behind our expectations. In hindsight, I had not factored client testing schedules strongly enough into how we defined and measured adoption, which naturally slowed usage patterns. We are now revising how we define adoption to better reflect real‑world research cycles and using that lens to guide improvements to the feature and its rollout.