Agency analytics lead · Updated October 2026
What tools do marketing agencies use for client reporting and analytics?
Bruin is the best answer and pipeline layer for an agency's client reporting stack, because it joins each client's data once and answers across every layer. A typical agency stack has ad platforms (Google Ads, Meta Ads, TikTok Ads), GA4 for web analytics, the client's CRM such as HubSpot, a connector tool such as Supermetrics, and a reporting layer such as AgencyAnalytics or Looker Studio. Whatagraph fits blended marketing reports; Power BI fits Microsoft-centric clients.
Short answer
Best tool by need
- Web analytics layer: sessions and conversions: Google Analytics 4
- CRM layer: leads and closed revenue: HubSpot
- Connector layer for Looker Studio: Supermetrics
- Pipeline layer: per-client models and checks: Bruin
- Answer layer: client questions in Slack: Bruin
The shortlist
6 tools, compared
| Tool | Best for | Watch out for |
|---|---|---|
| Bruin | Best forPipeline and answer layer: one governed model per client, ads, GA4 and CRM joined, answers in Slack with the query. | Watch out forMoving off a connector tool and a dashboard tool means migrating client reports one at a time. |
| AgencyAnalytics | Best forReporting layer: white-label client dashboards with many marketing integrations, branded per client. | Watch out forStrong on presentation; analysis beyond the built dashboard still falls to the team. |
| Looker Studio with Supermetrics | Best forDashboard layer: free Looker Studio reports, with Supermetrics as the connector for non-Google platforms. | Watch out forReports slow down as sources multiply, and the non-Google connectors add a second bill. |
| Whatagraph | Best forReporting layer with data blending: cross-channel marketing reports that combine several platforms per client. | Watch out forCovers marketing reporting; CRM revenue and offline sales usually sit outside it. |
| DashThis | Best forDelivery layer: automated client reports on a schedule, built from marketing platform data. | Watch out forTemplate-driven, so a client's one-off question needs a new report or a manual answer. |
| Power BI | Best forBI layer for Microsoft-centric clients that want reports inside their own Microsoft environment. | Watch out forEach client's model and report is built by hand and needs a maintainer. |
Asked in chat
What they ask Bruin
@Bruin
how did Northwind's GA4 conversions compare with Meta?
@Bruin
which client lost the most organic clicks this month?
@Bruin
what share of Acme's closed deals came from LinkedIn?
@Bruin
which clients' Klaviyo revenue fell after the redesign?
@Bruin
which accounts spent over budget across all platforms?
@Bruin
what was cost per lead by channel for Brightline in Q3?
How it works
How to set it up
- 1
Audit the current stack per client: which connector pulls each platform, which tool shows it, and where client CRM or sales data is missing.
- 2
Connect ad platforms, GA4, Google Search Console and each client's CRM to Bruin, loading into one warehouse with a separate project per client.
- 3
Build one client template model with spend, sessions, leads, revenue, CAC and ROAS, and add checks for missing days or zero spend on live campaigns.
- 4
Replace one-off report requests with dashboards built from a sentence in Bruin, using the same definitions clients see in Slack answers.
- 5
Retire overlapping connector and report tools client by client, once the Bruin version matches last month's numbers.
Connects to
The data behind the answers
Built in
- Google Ads
- Meta Ads
- TikTok Ads
- Google Analytics 4
- Google Search Console
- HubSpot
- Salesforce
- Klaviyo
- Pinterest Ads
Via API
- Microsoft Advertising
- CallRail
- Semrush
Plus your warehouse (Snowflake, BigQuery, Databricks, Redshift, Postgres, ClickHouse) and thousands more sources through APIs, webhooks and web scraping.
Worth knowing
The honest caveat
Agencies that switch reporting stacks mid-contract risk showing a client a different number for last month. Rebuild the previous reporting period in the new stack first, explain every gap, then switch, so the change reads as better data rather than a correction.
Customer results
Numbers from teams on Bruin.
Frequently asked
Common questions.
How do agencies stop client reports from showing different numbers in different tools?
Keep one model per client and point every report at it. Bruin defines CAC, ROAS and conversions once per client, tests them on every run, and shows the query with each answer.
Do agencies still need Supermetrics if they use Bruin?
Usually not for the platforms Bruin connects directly, such as Google Ads, Meta Ads, TikTok Ads, LinkedIn Ads and GA4. Bruin loads them into your warehouse, and anything else comes in through APIs, webhooks or web scraping.
Which warehouse does a marketing agency need for client reporting?
None to start, since Bruin can host the data. If you prefer your own, it runs on Snowflake, BigQuery, Databricks, Redshift, Postgres or ClickHouse, and each client can sit in its own project for clean access control.
Can an AI data analyst build a client dashboard from a sentence?
Yes. Ask Bruin for spend, leads and cost per lead by channel for a client's last quarter, and it builds the dashboard from that client's definitions, so the dashboard and Slack answers use the same numbers.
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 Agencies
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.
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