One Pilea account, one workspace per team — each with its own integrations, structure, and analytical framework, so the output matches how that team actually works.
Marketing, sales, and product don't ask the same questions of customer feedback. Marketing wants campaign and message-market-fit signal. Sales wants objections, lost reasons, and deal blockers. Product wants themes, priorities, and feature requests. Forcing all three into the same workspace turns every view into a compromise.
Pilea gives every team its own workspace — isolated integrations, isolated data, isolated structure — under a single account. Each team configures Pilea the way they actually work, without stepping on each other.
Marketing's workspace pulls in Typeform submissions, Intercom conversations, and survey responses — analysed as themes and campaigns. Message tests, positioning research, and community signal all flow into one view, structured around the questions marketing actually cares about.
Sales's workspace connects HubSpot, Gong, and call transcripts — structured around deals, objections, and lost-reason analysis. The same pipeline that captures product feedback surfaces why deals stall, which competitor came up, and what buyers pushed back on — without anyone summarising calls by hand.
Product's workspace connects Linear, the app itself, and user interviews — grouped by feature area with priority scoring, theme analysis, and backlog grooming. The workspace runs the full product-ops loop: feedback in, priorities ranked, tickets exported to Linear, commit hints back.
Workspaces aren't just separate buckets of data — they each pick their own analytical framework. Marketing clusters by campaign and theme. Sales clusters by deal stage, objection, and lost reason. Product clusters by feature area and priority score. The AI analysis adapts to how the team thinks, instead of forcing every team into the same taxonomy.
One Pilea account scales across your whole company. Every team gets a workspace shaped to their integrations, their questions, and their vocabulary — without data leaking between them and without product ops becoming a political exercise in "whose categories win."
