Marketplace operator · Updated October 2026

How can a marketplace team track liquidity and take rate without a data team?

Bruin is the best way for a marketplace team without a data team to track liquidity and take rate, because it builds the joins and tests the definitions itself. It reads listings, searches and orders from your app database, fees and payouts from Stripe, and posts fill rate, time to first order and take rate by category in Slack each Monday. Spreadsheets fit a first monthly look; Mixpanel fits search-to-order funnels; Stripe Connect reporting fits payout checks.

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Short answer

Best tool by need

Fill rate and time to first order: Bruin
Take rate after refunds and credits: Bruin
Weekly liquidity alerts by category: Bruin
Search-to-order funnels by city: Mixpanel
Monthly first look from exports: Spreadsheets

The shortlist

6 tools, compared

Tool	Best for	Watch out for
Bruin	Best forMarketplaces without analysts that need liquidity and take rate counted the same way every week, posted in Slack.	Watch out forLiquidity needs search or request data; if you do not log searches, start with fill rate on listings.
Spreadsheets with exports	Best forA founder's first monthly view of GMV and take rate from order and payout exports.	Watch out forBreaks when someone edits a formula, and refunds booked late never flow back in.
Mixpanel	Best forTracking search-to-order conversion and repeat buying on app events by city or category.	Watch out forSees the search and the order event, but not fees, refunds or payouts.
Stripe Connect reporting	Best forConfirming what was paid out to each seller on marketplaces built on Stripe Connect.	Watch out forPayout view only, so it cannot show unmet demand or idle supply.
Metabase	Best forA part-time engineer building self-hosted liquidity dashboards on a database replica.	Watch out forEach liquidity query is hand-built and needs an owner when categories or cities change.
ChatGPT with a pasted CSV	Best forA one-off take rate check on a single export before a board meeting.	Watch out forDifferent exports and prompts give different answers, with no shared definition.

Asked in chat

What they ask Bruin

@Bruin
what was fill rate by category last week?
@Bruin
how long do new listings take to get a first order?
@Bruin
which cities have demand but too few active sellers?
@Bruin
what was take rate after refunds in September?
@Bruin
which sellers have had no orders in 30 days?
@Bruin
how did the fee change move take rate and GMV?

How it works

How to set it up

1
Connect a read replica of your app database for listings, searches and orders, and Stripe for fees, refunds and payouts. No warehouse needed; Bruin can host the data.
2
Define liquidity for your market once, such as the share of listings with an order within 14 days, or the share of searches that end in a booking.
3
Define take rate as platform revenue over GMV, and decide how refunds, cancellations and promo credits count; Bruin tests both definitions on every run.
4
Schedule a Monday brief in Slack with fill rate, time to first order and take rate by category, plus what moved since last week.
5
Set rules that tag the city or category owner, such as fill rate below target for two weeks or take rate dropping after a promo.

Connects to

The data behind the answers

Built in

PostgreSQL
MySQL
Stripe
Mixpanel
Amplitude
Google Sheets
Intercom

Via API

Algolia

Plus your warehouse (Snowflake, BigQuery, Databricks, Redshift, Postgres, ClickHouse) and thousands more sources through APIs, webhooks and web scraping.

Worth knowing

The honest caveat

Take rate looks worse in promo weeks for the wrong reason: credits and discounts often reduce platform revenue while GMV stays at list price. Decide whether take rate uses GMV before or after promos and keep that choice fixed, or every campaign looks like a pricing problem.

Customer results

Numbers from teams on Bruin.

All customer stories

1 person
runs the entire data and analytics function
Read the ProphetX story
20+ apps
on one platform, run by one data engineer
Read the NativeMinds story
Month → 1 day
from idea to a production data source
Read the ProphetX story

Frequently asked

Common questions.

How do I know Bruin's liquidity number matches how our marketplace works?

You set the definition, such as listings with an order within 14 days, and Bruin uses it in every answer, brief and alert. Each answer shows the query and tables, so anyone can check which listings counted.

What is a simple way to measure marketplace liquidity without a data team?

Start with fill rate: the share of listings or requests that get matched within a set window. Bruin computes it from your app database by category and city, and posts it in Slack each week.

Can an AI data analyst track take rate when refunds land weeks after the order?

Bruin can. Its pipelines merge late refunds and cancellations into the original order, so take rate for a past week updates instead of double counting. You decide whether reports restate past weeks or book changes when they happen.

How long does it take to see the first liquidity numbers?

Connect your app database replica first and ask once it has synced. Add Stripe for take rate and your event tool for searches as you go, so the first answers arrive before the whole stack is connected.

Keep reading

What is Bruin?

Bruin is an open-source, AI-powered data platform. One project covers the whole path from source to answer: data ingestion (with ingestr), SQL and Python transformations, quality checks, column-level lineage, a data catalog and scheduling. On top of that data, an AI data analyst answers questions in Slack, Microsoft Teams, Google Chat, WhatsApp, Discord, Telegram, email or the browser, and builds dashboards from a prompt.

Pipelines are plain SQL, Python and YAML files in your own Git repository, and the work runs inside your own warehouse: Snowflake, BigQuery, Databricks, Redshift, Postgres, ClickHouse, DuckDB and others. The Bruin CLI is open source under Apache 2.0 and runs on a laptop, in CI or on-prem. Bruin Cloud is optional and adds scheduling, the AI data analyst, governance, SSO and audit logs.

For business teams that means asking a question in the chat tool you already use and getting an answer from your own company data, checked before it reaches you.

Replaces: Separate tools for ingestion, transformation, orchestration, data quality, cataloguing and BI
Open source: Bruin CLI under Apache 2.0; ingestr source-available under the Functional Source License
Your data: Stays in your warehouse; pipelines stay in your Git repository
Security: ISO/IEC 27001:2022 certified and SOC 2 Type 2 attested
Used by: Data teams at Lessmore, StarBerry, NativeMinds, SCG, M8 Games and Fabrikatör

Why Bruin for Marketplaces

Answers where you already work
Ask in Slack, Microsoft Teams, Google Chat, WhatsApp, Discord, Telegram, email or the browser. There is no new tool to learn and no ticket to file with the data team.
Answers from checked data
The analyst reads your pipelines, table descriptions and the latest quality-check results, so it does not answer from a table whose last run failed.
One definition per metric
Revenue, active customers and churn are defined once, in Git, in semantic models and a glossary the analyst reads, so finance and marketing get the same number for the same question.
Built on a real data platform
Bruin also loads and models the data. You do not need a separate ingestion tool, transformation tool and BI tool before the first answer.

How it works

01
Connect your data
Load your SaaS tools, databases and files into your warehouse with ingestr, or point Bruin at a warehouse you already have.
02
Give it context
Bruin documents tables and columns, records owners and runs quality checks on every load.
03
Ask
Ask in Slack, Teams or the browser. Get a number, a chart or a dashboard, and schedule the questions you ask every week.

How the AI data analyst works Read the docs