How to use Claude to analyze marketing data with Supermetrics

You can use AI to analyze your marketing data from Google Ads, Meta Ads, LinkedIn Ads, Google Analytics 4, or any data sources by connecting Supermetrics to Claude. Once connected, you can ask questions about your marketing performance in plain language, get instant campaign performance tables, and generate executive summaries, without exporting a single CSV.

This guide is for marketers and analysts who spend too much time wrangling data and not enough time acting on it. You'll learn how the setup works, what kinds of analysis it handles well, and where BI tools are still the better choice.

Key takeaways

How does Supermetrics connect your marketing data to Claude?

Supermetrics connects to Claude via the Supermetrics MCP (Model Context Protocol), a direct, authenticated link between Claude and your marketing data sources. MCP is a standard that lets AI assistants access external tools and data in real time.

When you ask Claude a question about your campaigns, Claude uses the Supermetrics MCP to query your connected accounts directly. It does not pull from a cached file or a pasted dataset. It pulls fresh data from the source. So when you ask "What are my top performing Google Ads campaigns this week?", Claude queries your actual Google Ads account and returns a table ranked by ROAS, CPA, or conversions, whichever you want.

How to connect marketing data to Claude using Supermetrics

From the Supermetrics platform:

1. Log in to your Supermetrics account and connect your marketing data sources (Google Ads, Meta Ads, LinkedIn Ads, GA4, and others).
2. Enable the Supermetrics MCP server in Claude.
3. Start with a simple query: "What are my top-performing campaigns by ROAS in the last 30 days?"
4. Build from there. Add more channels, extend the date range, or try a workflow query that generates a deck or an executive summary.

From Claude

• In Claude, go to Customize → Connectors.
• Search for Supermetrics and enable it.
• If you’re an existing Supermetrics user, you’ll be prompted to log in to your Supermetrics account to complete the connection.

If you don’t have a Supermetrics account yet, click Sign up when prompted and create a free trial account. Once your account is set up, connect your marketing data sources in Supermetrics, then return to Claude. The connector will be ready to use.

What kinds of questions can you ask Claude about your marketing data?

Here are three levels of query that work well: simple, cross-channel, and workflow. A good rule of thumb is to start simple and build from there.

Simple queries answer a specific question about campaign performance. These are useful for daily check-ins or quick stakeholder updates.

• What are my top-performing Google Ads campaigns by ROAS in the last 30 days?
• Which Meta Ads campaigns have the highest CPA this week?
• Show me LinkedIn Ads performance for the last 7 days.

Cross-channel queries pull data from multiple data sources in a single request. This is where the time saving becomes dramatic, because what used to require separate exports and manual consolidation in Sheets now happens in a single prompt.

• Pull the last 90 days of performance data from my LinkedIn Ads and Facebook Ads accounts and show me a cross-channel comparison.
• Compare Google Ads and Meta Ads performance for Q1 vs. Q2 across conversions, CPA, and spend.

Workflow queries combine data retrieval with output generation. This is the most powerful mode. you're not just asking a question; you're commissioning a deliverable.

• You're a digital marketer for a hotel chain. Create a full-funnel marketing dashboard for the EVP of Marketing, showing performance across Facebook and Google Ads for the last 7 days.
• Create a marketing performance overview as a slide-ready deck, including a summary intro, individual channel deep dives, cross-channel comparisons, strategic recommendations, and next steps.
• Write a concise email summarizing these results to share with my CMO.

How do you run a full 90-day performance analysis with Claude?

Typically, a 90-day performance analysis takes a few days of manual work, pulling data, building a deck, and writing the summary email. With Supermetrics connected, you can run the entire process in a single session within 10 minutes.

Step 1: Pull the data

Start by asking Claude to retrieve the relevant data from your connected accounts:

"Pull the last 90 days of performance data from my LinkedIn Ads and Facebook Ads accounts."

Claude uses the Supermetrics MCP to query both platforms and returns top performers by conversions and ROAS, along with a cross-channel summary.

Step 2: Build the deck

Once you have the data, ask Claude to structure it as a presentation:

"Create a marketing performance overview as a slide-ready deck, including a summary intro, individual channel-level deep dives, cross-channel comparisons, strategic recommendations, a next-period forecast, and actionable next steps. Structure it into a clean, concise slide outline with titles, subtitles, bullet points, and insight callouts."

Claude generates a PowerPoint deck automatically. The structure, the headlines, and the insight callouts are all produced from your actual campaign data.

Step 3: Write the executive email

"Write a concise email summarizing the deck to share with my CMO."

Claude produces a ready-to-send email that covers the key findings. You review it, adjust the tone if needed, and send.

The whole workflow, from data to deck to email, runs inside a single Claude conversation. No switching tabs. No copying numbers between documents. No reformatting.

What does Claude actually show you when you query your data?

When you run a query through Supermetrics for Claude, you typically get a structured table of results alongside written insights. Here’s an example from a real query on a Google Ads account.

The output has two parts. First, a table ranked by ROAS showing spend, conversions, CPA, and return on ad spend for each campaign. Second, written callouts that flag what is working and what needs attention, like identifying a campaign with a low CPA but small budget as a hidden gem, or flagging high-spend campaigns with weak ROAS as candidates for reallocation.

Why is data from Supermetrics more reliable than pasting a CSV?

A pasted CSV gives Claude a static snapshot frozen at the time of export, which means any follow-up question about a different date range, metric, or breakdown requires a new export. Supermetrics queries live data. That means every time you ask Claude a question, it pulls the most current numbers from your Google Ads, Meta Ads, or LinkedIn accounts. You can add new metrics, change the date range, or ask a follow-up question without leaving the conversation.

There is also the question of where the numbers come from. Without a live data connection, Claude can produce plausible-looking figures that are quietly fabricated, a problem called hallucination. Supermetrics eliminates that risk at the source by pulling live data directly from your ad platforms. Claude works from accurate input data rather than invented ones. That said, derived calculations and aggregations are still performed by Claude, so it is worth spot-checking any figures you plan to share externally.

Finally, Supermetrics brings 15 years of marketing data expertise to how Claude interprets your data. It does not just know that ROAS and CPC are metrics. It understands how they relate to each other and what changes in one signal about the other. That context shapes the insights Claude surfaces.

Read Why most AI agents confidently get your marketing wrong (and how Supermetrics fixed it)

How to write prompts that get useful results

The quality of Claude's output depends directly on how clearly you ask. A vague question gets a generic answer. A specific instruction gets a result you can actually use.

Good prompts are clear and direct. Clear means Claude knows exactly which data to pull and how to use it. Direct means you give Claude an instruction, not a question.

Be clear: tell Claude what you want, what data to use, and what matters to you

A clear prompt answers four things:

1. What action do you want Claude to take? Generate insights, create a dashboard, build a slide deck?
2. Which data sources are you working with? Google Ads, Meta Ads, LinkedIn Ads, GA4?
3. What date range and which accounts?
4. Which metrics matter for this analysis? ROAS, CPA, conversions, spend?

Be direct: use instructions, not questions

Start with an action verb: Create, Write, Generate, Pull, Analyze. Do not ask Claude whether it can do something. Tell it what to do.

Prompt examples

The good prompt tells Claude exactly four things: what to do (create), what to create (a full-funnel dashboard), which data sources to use (Facebook and Google Ads), and the scope (last 7 days, Client A). That is the pattern to follow every time.

More examples across common marketing tasks:

You don't need to write perfect prompts from day one. Start with a simple query, review what Claude returns, then refine. If the output misses something you needed, add that constraint to your next prompt.

When should you use Supermetrics for Claude, and when should you use a BI tool?

The short version: Claude is faster to get started, and BI tools are easier to maintain. For recurring, standardized reporting, a BI tool wins on consistency and cost. For everything in between, Claude is hard to beat.

Claude is the better fit when:

• You need a quick answer and don't want to build a report first
• You're doing ad-hoc analysis — checking campaign performance, surfacing anomalies, answering one-off questions
• You need to pull from multiple platforms (Google Ads, Meta, LinkedIn) in a single workflow
• You're generating a short executive summary or a lightweight deck for a CMO or client

BI tools (Looker, Power BI, Data Studio) are the better fit when:

• You need a dashboard that multiple people check regularly, and that always looks the same. Claude can build dashboards, but each session consumes tokens, and the output can vary slightly between runs
• You're doing historical analysis beyond the API limits of your data sources — Supermetrics queries live APIs, so historical range is capped by each platform
• Your data already lives in BigQuery or Snowflake, and you have existing warehouse infrastructure — though Claude can help you write the queries to power those dashboards, too

Do you need technical skills to use Supermetrics for Claude?

Supermetrics for Claude requires no SQL, API configuration, or understanding of the MCP protocol. Marketers connect data sources through the Supermetrics platform and enable the connector in Claude in under five minutes.

What you do need:

• A Supermetrics account with your marketing data sources connected (Google Ads, Meta Ads, LinkedIn, GA4, and others)
• Claude with the Supermetrics connector enabled
• The ability to judge whether an AI output makes sense, which any experienced marketer can do

The one skill that makes a real difference is prompting. Being specific about what you want, naming the channel, the date range, the metric, and the format of the output, produces better results than vague queries. The more context you give Claude, the more useful the output.

Should you trust AI-generated marketing insights?

Supermetrics for Claude significantly reduces hallucination risk, but it does not eliminate the need for human review.

The Supermetrics for Claude connector grounds Claude's outputs in verified, live data from your actual marketing accounts, the same data you are already using to run reports in Data Studio or Google Sheets. That reduces hallucination risk significantly compared to asking Claude general marketing questions with no data connection.

For example, Layer, a marketing agency that adopted Supermetrics for Claude, ran multi-week validation testing on the outputs and found zero hallucinations or data errors. That kind of result is possible because Supermetrics pulls live data directly from ad platforms, ensuring Claude works from accurate source data rather than fabricated figures.

But reducing hallucination risk isn't the same as set and forget. You should still review the insights Claude surfaces, especially before sharing them with executives or clients. Claude can miss context that's obvious to a marketer. A campaign that looks underperforming might be in a test phase, or a spike in CPA might have a known explanation that isn't in the data.

The right model is: use Claude and Supermetrics to do the heavy lifting on data retrieval and initial analysis, then apply your judgment before the output goes anywhere important. That combination, trusted data infrastructure plus human review, is where the real value is.

Go from question to insight without leaving Claude

With Supermetrics for Claude, you can go from a question to a campaign table, a performance deck, or a CMO summary, all within a single conversation, from live data.

Start simple. Pick one channel, one date range, one question. See what Claude returns. Then build from there, like add channels, extend the date range, and try a workflow query. Most marketers find the biggest shift isn't the output itself; it's realizing how much time they were spending just getting the data into a usable shape.

Connect Supermetrics to Claude and run your first query.

Frequently asked questions