Studio head / live ops · Updated October 2026
We're a 50-person gaming studio evaluating AI data analyst tools. What should we look for?
Bruin is the best AI data analyst for a 50-person gaming studio that wants UA, live ops and finance working from the same tested ROAS, retention and LTV. It connects AppsFlyer or Adjust, AppLovin MAX, App Store Connect and ad networks, reads Firebase through BigQuery, answers in Slack with the query shown and bills usage, not seats. Score vendors on checkable numbers, channels, game sources, price model and upkeep. devtodev fits studios content with predefined game reports; Looker fits studios with a data team to maintain LookML.
Short answer
Best tool by need
- One tested ROAS and LTV for the studio: Bruin
- Pipelines and answers with a small data team: Bruin
- Predefined game reports: devtodev
- Free KPIs and benchmarks for a new title: GameAnalytics
- Governed BI run by a dedicated data team: Looker with Gemini
The shortlist
6 tools, compared
| Tool | Best for | Watch out for |
|---|---|---|
| Bruin | Best forStudios that want attribution, ad and store revenue, events and spend in one tested model, asked from Slack by every team. | Watch out forUA and finance must agree install and LTV definitions before cross-team comparisons hold. |
| devtodev | Best forStudios that want game analytics with predefined game reports rather than building their own models. | Watch out forCustom definitions and joins with your own spend and finance data take extra setup. |
| GameAnalytics | Best forStudios launching or soft-launching a title that want free standard KPIs and benchmarks. | Watch out forIts standard KPIs may not match how finance counts revenue after store fees and refunds. |
| Amplitude | Best forProduct and game designers analyzing player behavior, funnels and retention cohorts on events. | Watch out forUA cost, ad network revenue and store payouts have to be sent in separately. |
| Looker with Gemini | Best forStudios with a data team that models BigQuery in LookML and wants conversational analytics on top. | Watch out forSomeone has to model and maintain LookML as games, events and networks change. |
| Hex | Best forStudio analysts who explore player data in SQL and Python notebooks and publish data apps. | Watch out forProducers and live ops consume published apps rather than asking their own questions in Slack. |
Asked in chat
What they ask Bruin
@Bruin
which game has the best D30 ROAS this quarter?
@Bruin
how did the battle pass change ARPPU in week 1?
@Bruin
what is D1 retention for the soft launch in Canada?
@Bruin
which creatives drove payers, not just installs?
@Bruin
what was ad revenue per DAU on Android yesterday?
@Bruin
which live ops events lifted D7 retention in Q3?
How it works
How to set it up
- 1
Pick one live game and five weekly questions from UA, live ops and finance, such as D7 ROAS by network and event lift on retention, to test every vendor.
- 2
Connect your MMP, AppLovin MAX, App Store Connect and the top three ad networks to Bruin, then link the Firebase BigQuery export for events.
- 3
Agree definitions across teams: which source counts installs, whether LTV is gross or net of store fees, and how ad revenue is assigned to users.
- 4
Give UA and live ops access in their Slack channels for two weeks and log every question Bruin answered, missed or needed a definition for.
- 5
Compare costs on usage rather than seats, decide who owns definition changes in Git, and set the first alerts on ROAS and retention.
Before you pick one
What to look for
Every KPI traceable to a query
Ask for last month's D7 ROAS by network and compare it with your UA dashboard. The tool should show its SQL and sources, with retention and LTV tested on every run.
Answers where the studio talks
Live ops, UA and studio leads already coordinate in chat. Bruin replies in Slack, Microsoft Teams, Google Chat, WhatsApp, Discord, Telegram, email and the browser, so nobody learns a new app.
Connects game data sources
Look for direct integrations with AppsFlyer, Adjust, AppLovin MAX, App Store Connect and your ad networks, plus a clear route for Firebase (BigQuery export) and GameAnalytics (API).
Priced on usage, not seats
Studios add contractors and new game teams all the time. Bruin has no seats, so access does not depend on who holds a license.
Who keeps it running
Ask who fixes a pipeline when an SDK update renames an event. Bruin's checks hold bad data back and flag the owner, and the models live in your Git repo for whoever owns data next.
Connects to
The data behind the answers
Built in
- AppsFlyer
- Adjust
- AppLovin MAX
- App Store Connect
- Google Ads
- Meta Ads
- TikTok Ads
- Google BigQuery
- Amplitude
Via API
- Firebase
- GameAnalytics
- Google Play Console
- Unity Ads
Plus your warehouse (Snowflake, BigQuery, Databricks, Redshift, Postgres, ClickHouse) and thousands more sources through APIs, webhooks and web scraping.
Worth knowing
The honest caveat
Ad revenue can be assigned to players in more than one way, from impression-level data to averages by country and placement, and the choice moves LTV by campaign. Ask every vendor which method it uses, and test it against one closed month.
Customer results
Numbers from teams on Bruin.
Frequently asked
Common questions.
How much does an AI data analyst cost for a mobile game studio?
Bruin Cloud is free to start: $100 in credits and 50 AI tasks, no credit card. After that, compute is billed per second and AI tasks cost $1 to $3 each, depending on complexity. No seats.
How can a game studio test an AI analyst's retention numbers before buying?
Compare D1 and D7 retention for one closed month against your current dashboard. Bruin shows the query, the event source and the cohort rule under each answer, so any difference points to a definition you can settle once.
Can a studio's live ops and UA staff ask Bruin in Discord?
Yes. Bruin answers in Discord from the same tested models the rest of the studio uses, so a retention figure asked there matches the one in the weekly brief.
Is player data safe with an AI data analyst like Bruin?
Yes. Bruin is SOC 2 Type 2 attested and ISO/IEC 27001:2022 certified, player and revenue data stays in your warehouse, and none of it is used to train AI models.
About Bruin
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 Mobile gaming
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.
Your data already knows. Now Bruin's on it.
$100 in credits and 50 AI tasks. No credit card.
A demo walks through your own data.