Fairing vs Dovetail
Side-by-side trajectory, velocity, and editorial themes.
Fairing pushes survey data into the tools merchants already use to act on it.
Fairing is a post-purchase survey and attribution tool for e-commerce. Recent work makes response data more actionable and portable — a Shopify Analytics sync, Klaviyo and Hazel integrations, in-app comparison periods, and bulk recategorization — plus a new hosted landing page that extends surveys beyond the post-purchase moment.
Fairing is moving from collecting survey responses toward embedding that data wherever merchants already analyze and act — Shopify, Klaviyo, Hazel — while tightening its own analytics and API. New API rate limits suggest programmatic usage is growing enough to formalize.
Expect more destination integrations and deeper in-app analytics; the hosted landing page hints at further expansion of survey delivery channels beyond the post-purchase flow.
Dovetail is turning its research repository into an AI analyst that reads, computes, and cites.
Dovetail has shifted its center of gravity from storing research to answering questions over it. The last month is almost entirely about the chat layer: persistent multi-turn context, code execution with inline charts, admin-curated Docs as context, and a new deep research mode. The MCP server is gaining write tools, making the repository operable by outside agents.
The arc points to an analytical agent that works across both qualitative and quantitative data and can be driven programmatically. Each release widens what chat can pull in and what it can do, from running code to sustaining reasoning across turns. Dovetail is positioning the chat surface, not the project, as the primary way users interact with their research.
Expect deep research mode to gain agentic follow-through that writes results back to Docs, and the MCP write surface to keep expanding toward full repository control from external tools.
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