Case Study: Trolley builds a trusted customer signal layer with BuildBetter

Trolley turns customer questions into source-backed answers in minutes with BuildBetter

Trolley, an enterprise company, faced the challenge of unifying its vast but fragmented customer data from sources like Salesforce, Momentum, Slack, and Notion. This disparate information prevented them from turning raw data into a structured, trusted signal layer that product, marketing, and executive teams could use for decision-making. They partnered with BuildBetter to implement a solution for creating this essential customer truth data model.

BuildBetter solved this by connecting and structuring Trolley's customer conversations and company metadata, then enriching it with product taxonomy and account context. This created a unified customer-signal layer that various teams could use. The results were transformative: product managers could run multiple research activities daily instead of just a few per month, and multiple teams began working from a single source of customer evidence, moving the company from anecdotal to data-driven decision-making.

Trolley