Agency analytics lead · Updated October 2026

We're a 25-person agency evaluating AI data analyst tools. What should we look for?

Bruin is the best AI data analyst for a 25-person agency that wants every client on a governed model without hiring a data team. It joins each client's ad platforms, GA4 and CRM, tests CAC and ROAS per client, and answers account managers and clients in Slack with the query shown. Look for checkable numbers, client separation, the channels clients use, pricing that does not charge per seat, and clear upkeep. AgencyAnalytics fits teams that only need white-label dashboards; Whatagraph fits blended marketing reports.

Short answer

Best tool by need

  • Governed per-client models without a data team: Bruin
  • Clients self-serving in a shared channel: Bruin
  • White-label dashboards only: AgencyAnalytics
  • Blended cross-channel marketing reports: Whatagraph
  • Templated recurring client reports: DashThis

The shortlist

6 tools, compared

BruinBest forAgencies that want per-client governed models, CRM revenue next to ad spend, and client questions answered in Slack.Watch out forPer-client definitions take an onboarding session with each client before self-service is switched on.
AgencyAnalyticsBest forAgencies whose clients mainly want branded dashboards across many marketing integrations.Watch out forDashboards are built per client, and analysis beyond them stays manual.
WhatagraphBest forAgencies that blend several marketing platforms into one report per client.Watch out forReporting-focused, so pipelines, data checks and CRM modeling live elsewhere.
DashThisBest forSmall agencies sending the same monthly report template to many clients.Watch out forTemplates are fixed, so new client questions mean editing reports by hand.
Looker Studio with SupermetricsBest forAgencies on a tight budget whose clients mostly run Google Ads and GA4.Watch out forNon-Google connectors usually cost extra, and large reports slow down.
DotBest forAgencies with a data engineer who already models client data in a warehouse.Watch out forAnalyst layer only, so the agency still runs ingestion and modeling for every client.

Asked in chat

What they ask Bruin

  • @Bruin

    which clients are under target ROAS this week?

  • @Bruin

    what did Brightline's LinkedIn Ads cost per SQL in Q3?

  • @Bruin

    how does Acme's GA4 revenue compare with Shopify?

  • @Bruin

    which clients have campaigns spending with no conversions?

  • @Bruin

    what was Northwind's blended CAC last month?

  • @Bruin

    which ad accounts stopped syncing data yesterday?

How it works

How to set it up

  1. 1

    Pick two clients with different stacks, one ecommerce brand on Shopify and one B2B company on HubSpot, and run the whole evaluation on their data.

  2. 2

    Connect their ad platforms, GA4 and CRM to Bruin, and agree conversion and revenue definitions with each client contact during setup.

  3. 3

    Ask the questions clients sent last month in Slack, and compare Bruin's answers and queries with the reports your team built by hand.

  4. 4

    Test client separation: confirm each client sees only its own data, and that account managers see only the clients they run.

  5. 5

    Model cost per client on usage, not seats, and confirm a second analyst can maintain the definitions from the Git repo.

Before you pick one

What to look for

  • Numbers clients can check

    A client who sees the query and platforms behind a ROAS figure argues less about it. Require shown queries and per-client definitions tested on every run.

  • Every client's sources, separated

    Check native connections for Google Ads, Meta Ads, TikTok Ads, LinkedIn Ads, GA4 and HubSpot or Salesforce. Access must be scoped per client so no client sees another's data.

  • Answers in the client's channel

    A portal login is one more thing for a client to forget. Each client should ask where it already talks to you: Slack, Microsoft Teams, Google Chat, WhatsApp, Discord, Telegram, email or the browser.

  • Pricing that scales with clients

    Per-seat pricing gets expensive when every client contact is a seat. Prefer usage-based pricing, so adding a client's team costs compute, not licenses.

  • Who maintains the models

    Ask who updates definitions when a client changes its conversion events. In Bruin, models and checks live in your Git repo, so any analyst at the agency can pick them up.

Connects to

The data behind the answers

Built in

  • Google Ads
  • Meta Ads
  • TikTok Ads
  • LinkedIn Ads
  • Google Analytics 4
  • HubSpot
  • Salesforce
  • Shopify

Via API

  • Microsoft Advertising
  • Amazon 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

Self-service only works if the client trusts the first answer. Start each client with questions you already report on, where the numbers can be compared, before inviting open questions that touch data you have not modeled yet.

Customer results

Numbers from teams on Bruin.

Frequently asked

Common questions.

How can an agency prove an AI analyst's client numbers are right?

Run it on last month's report. Bruin shows the query and platforms behind each figure, with CAC and ROAS defined once per client and tested on every run, so a mismatch points to a definition, not a guess.

Is Bruin priced per seat for agencies with many clients?

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.

Is agency client data safe with an AI data analyst?

Yes. Bruin is SOC 2 Type 2 attested and ISO/IEC 27001:2022 certified, and access to each client's data follows the roles you set. Client data is never used to train AI models.

Can a 25-person agency run an AI data analyst without a data engineer?

Yes. Connect each client's ad platforms, GA4 and CRM to Bruin, then ask in Slack. If you hire a data engineer later, they build on the same models in your own Git repo.

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.

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