A new bulk creation feature was in prototype, but nobody knew whether it worked for the people who'd use it daily. Engineering wanted evidence before committing. One user group wouldn't tell the whole story; internal experts, paying customers, and external marketers each bring different context.

I ran usability testing across three groups: internal team members moderated, current customers unmoderated, external growth marketers unmoderated. I wrote the screeners, recruited participants, moderated the think-aloud sessions, and built the unmoderated tests. Then I synthesized everything into one cross-group view, separating what was universal from what was group-specific and scoring severity by product familiarity. The findings reshaped the plan: we cut a complex in-platform editing approach once research showed it was hard to use and rarely needed, and shipped the simpler, higher-value path first.

Before designing anything, we needed to understand how enterprise customers actually worked at scale, where the tooling fell short, and what they'd built to compensate. Foundational discovery: no prototype to test, just open questions about real workflows.

I ran discovery sessions with enterprise customers across retail, grocery, hospitality, media, and sports, then synthesized them into cross-interview documents by theme. The strongest signal recurred across every vertical: customers had independently built elaborate parallel spreadsheet systems outside the product because the in-platform experience didn't match how they actually worked. The same themes surfaced again and again, naming and discoverability at scale, export and audit gaps, a hard dependency on code for non-technical users. I turned each into a structured deliverable with quotes, implications, and next steps the team could design against.

One study at a time couldn't keep pace with the roadmap, and ad hoc recruitment was slow and inconsistent. We needed a repeatable way to source the right participants and run several studies in parallel without findings bleeding together, and it had to work across regions.

I founded a customer advisory community as a standing recruitment pool and designed the whole program: a hand-selected founding cohort of enterprise customers across travel, food, fintech, retail, and tech; a year-long cadence of an in-person kickoff, monthly virtual sessions, and quarterly events and newsletters; and a dedicated channel where members were answering each other's product questions within the first week. I ran the events and built the scoring model that expanded it across Europe, North America, and Asia-Pacific. With the pool in place I ran concurrent studies across product areas, holding firm that screener quality shapes who shows up and that parallel studies need clear synthesis boundaries to keep insights attributable.

Research only earns its keep when the study is built to answer the real question. Pick the wrong method, or frame things so loosely that any result confirms the plan, and you waste participants and produce findings nobody can act on.

I matched method to question deliberately: moderated think-aloud sessions to understand reasoning and probe on hesitation, unmoderated prototype tests for independent task completion at volume. I wrote study goals as falsifiable hypotheses with explicit success metrics, drew the scope lines so reviewers knew what the study could and couldn't produce, and authored the discussion guides that kept sessions consistent.