Studio head / live ops · Updated October 2026

What AI tool can a live ops manager use to answer data questions in Slack?

Bruin is the best AI tool for a live ops manager who wants data answers in Slack without waiting on an analyst. It joins game events from Firebase in BigQuery, store purchases, AppLovin MAX ad revenue and attribution, so a question like how the weekend event moved D7 retention returns the lift, sample size and query in the thread. Dot fits studios that already have a modeled warehouse and only need a chat layer; GameAnalytics fits quick checks on standard KPIs in its dashboard.

Try for free Book a demo

Short answer

Best tool by need

Event and offer lift asked in Slack: Bruin
A/B test readouts with sample size: Bruin
Slack answers on top of existing models: Dot
Standard KPI checks in a dashboard: GameAnalytics
Deep behavioral funnels on player events: Amplitude

The shortlist

6 tools, compared

Tool	Best for	Watch out for
Bruin	Best forLive ops managers who want event lift, offer results and retention answered in Slack from joined game and revenue data.	Watch out forEvent and test calendars must be logged in one table, or overlapping effects get blended.
Dot	Best forStudios with a modeled warehouse that want a chat-first analyst answering live ops questions in Slack.	Watch out forIngestion, modeling and checks stay with your data team, since Dot covers the analyst layer.
GameAnalytics	Best forChecking standard game KPIs like retention and revenue per user in a ready-made dashboard.	Watch out forDashboard-first, so ad hoc follow-ups that join UA spend need another tool.
Amplitude	Best forGame designers exploring player funnels, progression drop-off and behavioral cohorts.	Watch out forA separate app to learn, and revenue from stores and ad networks has to be sent in.
ChatGPT or Claude with files	Best forA one-off look at an exported event report pasted into a chat.	Watch out forSees only the pasted file, and two people asking get two different retention numbers.
Asking the data team	Best forComplex one-off analyses where an analyst designs the method and checks the result by hand.	Watch out forAnswers often arrive after the event has ended, too late to change the offer.

Asked in chat

What they ask Bruin

@Bruin
how did the weekend event move D7 retention?
@Bruin
which offer sold best in the Starter Pack test?
@Bruin
did the energy refill price change hurt ARPDAU?
@Bruin
how many players finished the event's final stage?
@Bruin
what was revenue per payer during the sale vs before?
@Bruin
which segment churned after the level 40 difficulty spike?

How it works

How to set it up

1
Connect the Firebase BigQuery export for events, App Store Connect for purchases, AppLovin MAX for ad revenue and AppsFlyer or Adjust for install source.
2
Create a live ops calendar in Google Sheets with every event, offer, sale and A/B test, including start, end, platform and target segment.
3
Define the readout metrics once with the team: D1 and D7 retention, ARPDAU, payer conversion and event participation, each tested on every run.
4
Invite Bruin to the live ops Slack channel and ask about each event the day after it ends, checking lift, sample size and the query in the thread.
5
Schedule a daily live ops brief for the morning stand-up and set an alert when revenue per DAU drops below the four-week average during an event.

Connects to

The data behind the answers

Built in

Google BigQuery
App Store Connect
AppLovin MAX
AppsFlyer
Adjust
Google Sheets
Amplitude
Google Analytics 4

Via API

Firebase
GameAnalytics
Google Play Console

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

Worth knowing

The honest caveat

Live ops readouts mislead when an event overlaps an A/B test, a sale or a store feature. Log every event, offer and test with start and end times in one calendar table, so each readout shows what else was running instead of crediting the event with everything.

Customer results

Numbers from teams on Bruin.

All customer stories

~33%
fewer A/B tests to run
Read the M8 Games story
45%+
day-1 retention on their flagship game
Read the M8 Games story
95% faster
error detection and resolution
Read the Spektra Games story

Frequently asked

Common questions.

Can an AI data analyst measure the lift from a live ops event?

Yes. Ask Bruin how an event, offer or A/B test moved retention and revenue, and it returns the lift with its sample size and the query behind it.

How does a live ops manager know Bruin's answer is right?

Every answer shows the SQL, the event tables and the date range used. Retention and ARPDAU have one definition, checked before Bruin answers, so the number in Slack matches the studio dashboard.

Can live ops managers ask data questions without SQL?

Yes. Ask in plain words in Slack, like payer conversion during last week's sale, and Bruin writes and runs the query, with the SQL attached for anyone who wants to check it.

Can Bruin send a daily live ops brief to the studio?

Yes. Schedule a morning brief with DAU, revenue, retention and any running events or tests, posted to the live ops channel with what moved and why.

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 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.

How the AI data analyst works Read the docs