Marketplace operator · Updated October 2026
What is the best AI data analyst for marketplaces?
Bruin is the best AI data analyst for marketplaces that need both sides of the market in one answer: supply, demand, GMV, take rate and payouts. It joins your app database, Stripe, Amplitude or Mixpanel events, HubSpot and Zendesk into one tested model and answers in Slack with the query shown. Amplitude or Mixpanel fit funnel analysis on buyer or seller events; Stripe Connect reporting fits payout checks; Sigma fits teams with a modeled warehouse that prefer spreadsheets.
Short answer
Best tool by need
- Liquidity and take rate across both sides: Bruin
- GMV, refunds and payouts reconciled: Bruin
- Buyer and seller funnels on events: Amplitude or Mixpanel
- Checking seller payouts: Stripe Connect reporting
- Analyst-built pricing and matching studies: Hex
The shortlist
6 tools, compared
| Tool | Best for | Watch out for |
|---|---|---|
| Bruin | Best forMarketplaces that want supply, demand, GMV and payouts joined, with one tested take rate and answers in Slack. | Watch out forMatching logic lives in your app database, so Bruin needs a replica or export of it. |
| Amplitude or Mixpanel | Best forProduct teams tracking buyer and seller funnels, activation and retention on app events. | Watch out forEvents alone miss refunds, payouts and take rate, which live in billing and the database. |
| Stripe Connect reporting | Best forChecking seller payouts for marketplaces that pay sellers out through Stripe Connect. | Watch out forCovers payments only, so listings, search and supply data sit elsewhere. |
| Sigma | Best forOps and finance teams that want spreadsheet-style BI and AI features on a modeled cloud warehouse. | Watch out forNeeds a modeled warehouse first, including the join between listings and orders. |
| Looker with Gemini | Best forLarger marketplaces standardizing metrics in a LookML semantic model with conversational analytics on top. | Watch out forSomeone has to model and maintain LookML as categories and fee rules change. |
| Hex | Best forMarketplace analysts building SQL and Python notebooks for pricing or matching studies, shared as data apps. | Watch out forAimed at analysts; ops managers view published apps instead of asking follow-ups themselves. |
Asked in chat
What they ask Bruin
@Bruin
what was take rate by category last month?
@Bruin
which cities have more buyers than active sellers?
@Bruin
how long does a new listing wait for a first order?
@Bruin
which sellers had payouts held this week?
@Bruin
what share of Q3 GMV came from repeat buyers?
@Bruin
did the fee change lower seller sign-ups?
How it works
How to set it up
- 1
Point Bruin at a read replica of your app database for listings, orders and users, then connect Stripe for charges, refunds and payouts.
- 2
Add Amplitude or Mixpanel events for search and checkout, plus Zendesk for disputes, so each order links to the session and ticket behind it.
- 3
Define GMV, net revenue and take rate once, including how refunds, cancellations and promo credits count, and Bruin tests them on every run.
- 4
Let category and city managers ask in Slack, such as which cities need supply this week, with the query attached to each answer.
- 5
Schedule a Monday marketplace brief on GMV, take rate and fill rate by category, and set rules for payouts stuck past their usual date.
Connects to
The data behind the answers
Built in
- PostgreSQL
- Stripe
- Amplitude
- Mixpanel
- Zendesk
- HubSpot
- Google Analytics 4
- Braze
Via API
- Segment
Plus your warehouse (Snowflake, BigQuery, Databricks, Redshift, Postgres, ClickHouse) and thousands more sources through APIs, webhooks and web scraping.
Worth knowing
The honest caveat
GMV and net revenue drift apart on marketplaces: refunds, cancellations, seller-funded discounts and promo credits all land after the order. Decide which date each one books to before tracking take rate weekly, or last week's number keeps changing.
Frequently asked
Common questions.
How do I know an AI data analyst's take rate is right for our marketplace?
Bruin shows the query and the order, fee and refund tables behind every take rate it reports. Take rate, GMV and net revenue each have one definition, tested on every run, so finance and ops quote the same figure.
How is Bruin different from Amplitude or Mixpanel for a marketplace?
Amplitude and Mixpanel hold the events: searches, views and checkouts. Bruin joins those events with orders, payouts, fees and support tickets, so you can ask which sellers turn searches into revenue, not only clicks.
Can marketplace city managers ask Bruin questions from a phone?
Yes. City managers can ask from a phone in Slack, Microsoft Teams, Google Chat, WhatsApp, Discord, Telegram, email or the browser, and get the same tested numbers as the office.
Can an AI data analyst show buyer and seller metrics in one place?
Yes. In Bruin, buyers, sellers, listings and orders sit in one model, so one question can cover demand, supply and the match between them, such as search-to-order rate by city next to active sellers.
Your data already knows. Now Bruin's on it.
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