Head of Marketing · Updated October 2026

How can marketing teams get campaign answers without waiting on the data team?

Bruin is the best way for marketing teams to get campaign answers without waiting on the data team: marketers ask in Slack and Bruin queries the connected ad, analytics and CRM data itself. Bruin uses the definitions the data team already maintains, shows the query and sources with every answer, and builds a campaign dashboard from one sentence. Looker Studio fits self-serve dashboards on Google data; ad platform reports fit questions about one channel; ChatGPT fits a quick look at an export.

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Short answer

Best tool by need

Ad hoc campaign questions in Slack: Bruin
Campaign dashboards without a ticket: Bruin
Self-serve charts on Google Ads and GA4: Looker Studio
Questions about one ad platform: Native ad platform reports
Complex modeling and new data sources: The data team

The shortlist

5 tools, compared

Tool	Best for	Watch out for
Bruin	Best forMarketers who want answers in Slack from ad, analytics and CRM data, using the data team's tested definitions.	Watch out forNew sources still need connecting once, so plan which ad accounts and tools to add first.
Tickets to the data team	Best forQuestions that need new data sources, custom modeling or a careful statistical read.	Watch out forRoutine campaign questions wait in the same queue as complex work.
Looker Studio (with Supermetrics)	Best forMarketers who want free self-serve dashboards on GA4 and Google Ads without asking anyone.	Watch out forCharts answer the questions they were built for, and a new question means building another chart.
Native ad platform reports	Best forFast answers about one platform's spend, reach and conversions, straight from Meta Ads Manager or Google Ads.	Watch out forEach platform grades its own work, so cross-channel comparisons do not add up.
ChatGPT with pasted CSVs	Best forA quick summary of one campaign export before a meeting.	Watch out forNo shared definitions, so a marketer and an analyst can get different CAC from the same data.

Asked in chat

What they ask Bruin

@Bruin
how did last week's newsletter do on signups?
@Bruin
which LinkedIn campaigns drove demos in September?
@Bruin
what is cost per lead by channel this month?
@Bruin
did the pricing page test change signup rate?
@Bruin
which keywords brought paying customers in Q3?
@Bruin
how much did we spend on TikTok vs plan?

How it works

How to set it up

1
Ask the data team to connect the marketing sources in Bruin, such as Meta Ads, Google Ads, LinkedIn Ads, GA4 and HubSpot, on top of the models they already run.
2
Agree with the data team on the definitions marketing uses most, like lead, MQL, CAC and sourced pipeline, so they live in one place and are tested on every run.
3
Add Bruin to the marketing Slack channel and ask the questions that used to become tickets; each answer shows its query for anyone who wants to check.
4
Describe the dashboards you keep requesting in one sentence each, such as spend and CAC by channel for the last 90 days, and let Bruin build them.
5
Send anything Bruin cannot answer yet, like a source that is not connected, back to the data team, and once they add it, everyone can ask about it.

Connects to

The data behind the answers

Built in

Meta Ads
Google Ads
LinkedIn Ads
Google Analytics 4
HubSpot Marketing Hub
Mailchimp
Customer.io

Via API

Marketo
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

Self-serve only works if marketing and the data team share definitions. If marketing counts an MQL one way in HubSpot and the data model counts it another, Slack answers will contradict the dashboard. Settle the lead and pipeline definitions with the data team before opening it up.

Customer results

Numbers from teams on Bruin.

All customer stories

4x faster
time to insight
Read the Workhy story
< 1 week
for Bruin to build a custom connector
Read the SCG story
Month → 1 day
from idea to a production data source
Read the ProphetX story

Frequently asked

Common questions.

Can a marketer check an AI answer about campaigns without asking the data team?

Yes. Bruin shows the query, the sources and the metric definition behind each answer, so a marketer can see which campaigns and dates were counted. An analyst can read the SQL later if a number looks off.

Do marketers need SQL to get campaign answers from Bruin?

No. Marketers ask in plain words, like cost per demo by LinkedIn campaign last month, and Bruin writes and runs the query. The SQL comes with the answer for anyone who wants it.

Can marketing build its own campaign dashboards without a data team ticket?

Yes. Describe the dashboard in a sentence and Bruin builds it from the same definitions it uses in chat, so the dashboard and the Slack answer show the same CAC.

Does the data team lose control when marketing asks Bruin directly?

No. The data team keeps the models and definitions in its own Git repo, and Bruin answers from them. Every change to a definition is versioned in Git, so the team can see who changed what and when.

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 Marketing

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