Every review, one workbench. Sorted, scored, assigned.
Reviews, tickets and calls pile up in different tools, and nobody knows which complaint costs you most. Workbench puts them in one place and ranks them by the revenue behind them.
Stop guessing what to fix first.
What changes when your feedback is one ranked list, not a dozen tabs.
Tagged and grouped before you open it.
AI reads every review and tags it — bug, feature request, churn signal, competitor mention, or a bit of social proof for you.
The related ones group into themes, each with a written summary and an impact score so you know what to look at first.
Tune what AI flags →Kanban or table. Saved views per team.
Drag insights through New → Acknowledged → In Progress → Shipped on a kanban, or work them in a sortable table — so the whole team can see what's moving and nothing quietly slips through.
Filter by status, assignee, priority, area, date, or platform — then save the view and pin it to your sidebar.
Work your queue →Every request, with the money behind it.
See the MRR, churned revenue and open deals behind each request, so you build what keeps and wins customers.
Filter to any segment, like Enterprise accounts over $1k MRR, and the ranking follows.
Follow the money →Ship anywhere. Linear, Jira, Slack, email, webhook.
Send it to Linear, Jira, Slack, or a webhook. Each one lands fully formed — summary, the real customer quotes, a link back to dig in. Draft a follow-up to whoever left the review and send it from your own address. Or connect Claude or Cursor over MCP and ask your reviews questions without leaving your editor.
Push to your tools →From request to roadmap, without a spreadsheet.
Plan Now, Next and Later straight from what customers asked for. Size the work, spot quick wins, and drag a card to Shipped when it's done.
Plan from requests →Shipped it? Tell everyone who asked.
One click emails every customer who asked, quoting their own words. Their replies come back as new feedback.
Tell them it shipped →Rules that act while you're busy.
A churn signal on an open deal or a $10k MRR request? The right person hears in Slack, email, Linear or Jira, no board-watching.
Automate the busywork →Need to ask customers something specific?
Feedback Collection ships a block-based builder with AI-generated follow-ups, an embeddable widget, and trigger-based delivery. Every response feeds back into this same workbench.
Questions & answers
Which platforms can UseReviews ingest reviews from?
Apple App Store, Google Play Store, G2, Trustpilot, ProductHunt, any RSS feed, CSV bulk upload, our embedded widget, custom Smart Forms, and any external system via webhook. Most teams have their first three sources synced within ten minutes.
How accurate is the AI clustering?
Every cluster is editable and auditable — your team can re-tag, split, or merge any insight, and the AI uses those corrections going forward. Each workspace also configures its own thresholds and categories, so you tune the precision/recall trade-off to fit how your team actually works.
Can I push to tools other than Linear, Jira and Slack?
Yes. Native pushes include Linear, Jira, Slack, and email (via your own SMTP or Resend). For everything else, we expose configurable webhooks with retry-on-failure and full delivery history.
Can I use UseReviews from Claude or Cursor?
Yes. Our MCP server lets any MCP client read your reviews, insights and clusters, so you can ask questions about customer feedback right where you work. Setup is in the MCP docs.
Does it work with our existing customer data?
Drop in a Stripe key and customer profiles, plan tier, LTV, and purchase history land beside every review. You can also import contacts from CSV, segment by behaviour, and send AI-drafted email directly to any contact.
Connect your first source. See your first insight.
A few minutes to your first connected platform. Free plan included — no credit card.