A continuous, unfiltered feed of how customers really talk.
Research teams fight to get unfiltered customer signal at a useful cadence. Burrow finds the communities where your customers discuss the category, then tracks them, so recent threads and sentiment shifts arrive every week. It turns scattered community noise into a structured, ongoing research feed.
What gets in the way
- unfiltered customer signal is hard to get on a cadence
- interviews are slow and recruited samples are biased
- community insight is scattered across many platforms
- you cannot watch sentiment move over time
Searches a researcher runs
Paste any of these into Burrow, or write your own.
Example reports
built for customer research teams
A budgeting app for couples
A budgeting app for couples that automatically splits shared expenses and tracks goals together.
Pricing software for B2B SaaS founders
Pricing software for B2B SaaS founders doing $10k to $100k MRR.
A habit-focused fitness app for busy people
A habit-focused fitness app that builds a daily 15-minute workout streak for busy people.
Where Burrow looks first
Every search covers all eight platforms. For customer research teams, the strongest signal usually comes from these.
Questions from customer research teams.
A static list is written once and rots. Burrow scores every community against your exact positioning, ranks it for buyer fit, and attaches threads from the last seven days so you can confirm the room is still active before you spend time there. For researchers, the difference is showing up where unfiltered customer signal is hard to get on a cadence instead of guessing.