How to Connect Google Analytics to Claude

Wishing you could ask your Google Analytics data questions and get plain English answers? You can use a powerful AI model like Anthropic's Claude to analyze your website's performance, but figuring out how to connect the two isn't always straightforward. This article walks you through the different ways to get your Google Analytics data into Claude for summary, analysis, and reporting.

Why Connect Google Analytics to Claude?

Google Analytics is a fantastic tool, but finding specific insights often means navigating complex reports and filtering data yourself. For marketers, founders, and content creators, the goal isn't just to look at data, it's to get actionable answers to important questions. That's where Claude comes in.

By feeding your GA4 data to Claude, you can transform raw numbers into clear narratives. It's like having a data analyst on standby, ready to:

• Summarize Performance: Instead of pulling numbers yourself, you can ask, "Summarize my website's performance last month based on this data," and get a coherent report.
• Identify Trends: Ask questions like, "What are the common themes among my top 10 blog posts this quarter?" or "Which traffic sources are trending up?"
• Explain Changes: Upload data from two different periods and ask, "Why did my traffic from organic search decrease in February compared to January?"
• Generate Copy for Reports: Give Claude data for the week and instruct it to "Write a three-paragraph summary of our marketing channel performance for my weekly team update."

Essentially, connecting GA4 to Claude bridges the gap between having data and understanding it, allowing you to move from analysis to action much faster.

Understanding the Core Challenge: No Direct Integration

It's important to know that you can't just log into your Claude account and click a button that says "Connect to Google Analytics." Unlike dedicated business intelligence tools, large language models like Claude are designed to work with data you provide them - typically in the form of text or file uploads.

Therefore, the process always involves two core steps:

1. Exporting your data from Google Analytics.
2. Importing or pasting that data into Claude with a clear prompt about what you want it to do.

How you accomplish these steps can range from a simple manual download to a fully automated workflow. Let's cover the most common methods.

Method 1: The Manual CSV Export (Simple and Straightforward)

This is the easiest and most accessible way to get your GA4 data into Claude, requiring no technical skills. All you need is access to your Google Analytics account.

Step-by-Step Guide:

1. Sign in to Google Analytics: Navigate to your GA4 property.
2. Open the Report You Need: Go to the report that contains the data you want to analyze. For example, if you want to analyze traffic sources, you might go to Reports > Acquisition > Traffic acquisition. If you want to analyze page performance, you could go to Reports > Engagement > Pages and screens.
3. Customize Your Report: Before exporting, make sure the report shows exactly what you need. Adjust the date range, add comparison periods, and use the filter bar to isolate specific data points. This ensures you're giving Claude clean, relevant information.
4. Download the Data as a CSV File: In the top-right corner of the report, you'll see a 'Share this report' icon (a square with an arrow pointing up). Click it, then select 'Download File,' and choose 'Download CSV.'
5. Upload the CSV to Claude: Open a new chat at claude.ai. Click the paperclip icon to attach a file and select the CSV you just downloaded from Google Analytics.
6. Ask Your Question: Now, write a clear prompt explaining the context and what you want Claude to do. This is the most important part!

Example Prompts for CSV Uploads:

• "This attached CSV is a 'Traffic acquisition' report from Google Analytics for last month. Please analyze it and tell me which three channels drove the most conversions. Present the results in a simple table."
• "Here is a CSV of my top landing pages from the last 30 days. Read the data and write a paragraph summarizing the performance. Which page had the highest user engagement?"
• "Analyze this demographics report. Are there any interesting takeaways about the age groups or countries visiting my website that I should share with my marketing team?"

This method is perfect for quick, one-off analyses. Its main limitation is that it's a manual process based on static data. If you need updated information tomorrow, you’ll have to repeat the export and upload steps.

Method 2: Using the Google Analytics API with Python (The Technical Approach)

If you're comfortable with code and need to pull GA data regularly, you can automate the process using APIs. This involves writing a simple script that fetches data directly from Google Analytics and then sends it to Claude for analysis - no manual downloads required.

This is an advanced method, but it opens the door to creating scheduled reports and more complex analytical workflows.

Prerequisites:

• A Google Cloud project with the Google Analytics Data API v1 enabled.
• Service account credentials (a JSON key file) to authenticate your access.
• Your GA4 Property ID.
• Python installed, along with the necessary libraries: pip install google-analytics-data anthropic pandas

Example Python Script:

This script authenticates with both Google and Anthropic, pulls your top 10 pages by sessions from GA4, and then asks Claude to summarize the performance.

import pandas as pd
from google.analytics.data_v1beta import BetaAnalyticsDataClient
from google.analytics.data_v1beta.types import (
    DateRange,
    Dimension,
    Metric,
    RunReportRequest,
)
import anthropic

# --- 1. CONFIGURATION ---
# Replace with your actual credentials and IDs
# IMPORTANT: Never hardcode secrets in production code!
# Use environment variables or a secret manager.
GA_PROPERTY_ID = "YOUR_GA4_PROPERTY_ID"
GOOGLE_APPLICATION_CREDENTIALS = "path/to/your/service-account.json"
ANTHROPIC_API_KEY = "YOUR_ANTHROPIC_API_KEY"

# --- 2. AUTHENTICATION ---
client_options = {"api_endpoint": "analyticsdata.googleapis.com"}
ga_client = BetaAnalyticsDataClient.from_service_account_file(
    GOOGLE_APPLICATION_CREDENTIALS, client_options=client_options
)
claude_client = anthropic.Anthropic(api_key=ANTHROPIC_API_KEY)


# --- 3. PULL DATA FROM GOOGLE ANALYTICS API ---
request = RunReportRequest(
    property=f"properties/{GA_PROPERTY_ID}",
    dimensions=[Dimension(name="pagePath")],
    metrics=[Metric(name="sessions"), Metric(name="engagementRate")],
    date_ranges=[DateRange(start_date="30daysAgo", end_date="today")],
)

response = ga_client.run_report(request)

# --- 4. FORMAT DATA FOR CLAUDE ---
# Convert the API response into a readable string or pandas DataFrame
rows = []
for row in response.rows:
    rows.append({
        "Page Path": row.dimension_values[0].value,
        "Sessions": row.metric_values[0].value,
        "Engagement Rate": f"{float(row.metric_values[1].value) * 100:.2f}%"
    })
df = pd.DataFrame(rows)
data_for_claude = df.to_string() # Convert DataFrame to a string for the prompt

# --- 5. SEND DATA AND PROMPT TO CLAUDE ---
prompt=f"""
Here is some Google Analytics data showing my top 10 pages by sessions for the last 30 days:

{data_for_claude}

Please do the following:
1. Summarize the overall performance in a short paragraph.
2. Identify the top three performing pages.
3. Call out which page has the best engagement rate.
"""

message = claude_client.messages.create(
    model="claude-3-sonnet-20240229", # Or your preferred model
    max_tokens=1024,
    messages=[
        { "role": "user", "content": prompt}
    ]
).content[0].text

This script completely removes manual work, making it ideal for creating automated reporting systems that run daily or weekly.

Method 3: Automation Tools as Middle-Ground (Zapier & Google Sheets)

What if you're not a developer but want something more automated than manual CSV downloads? You can use no-code automation platforms like Zapier or Make, often using Google Sheets as a bridge.

A very robust and popular way to do this is with the official Google Analytics Add-on for Google Sheets. This free extension lets you automatically pull GA4 data into a spreadsheet on a schedule.

Automated Workflow Steps:

1. Install the Google Analytics Add-on: Open a new Google Sheet, go to Extensions > Add-ons > Get add-ons, and search for "Google Analytics." Install the official add-on.
2. Create a Report: In your sheet, go to Extensions > Google Analytics > Create new report. Configure the report by telling it which GA4 property to use, what metrics and dimensions to pull, and the date range.
3. Schedule It to Run Automatically: Once your report is configured, go to Extensions > Google Analytics > Schedule reports. You can set your report to refresh automatically every hour, day, week, or month. The Google Sheet will now always contain fresh data.
4. Connect it to Claude: Now that your data is automated, you have a few ways to get it to Claude:

This Google Sheets method is an excellent middle-ground. It automates the most tedious part - exporting the data - while keeping the analysis step flexible and simple.

Best Practices for Prompting Claude with GA Data

Getting your data into Claude is only half the battle. To get truly useful insights, you need to write effective prompts. Simply uploading a file and saying "analyze this" will give you generic results.

Follow these tips for better analysis:

• Provide Clear Context: Start your prompt by explaining what the data is. For example, "This is top-of-funnel traffic data for my e-commerce blog for Q1." This orients Claude so it knows how to frame its analysis.
• Ask Specific Questions: Avoid vague requests. Instead of "What do you see?", ask, "Based on this channel data, which marketing campaign drove the highest ROI, assuming an average customer value of $50?"
• Define Your Metrics and Goals: Tell Claude what success looks like for you. For example, "For us, the most important metric is the newsletter signup conversion rate. Analyze this data and tell me which blog posts are best at driving signups."
• Request a Specific Output Format: Guide Claude to give you the answer in the most useful format. Ask for "a bulleted list," "a markdown table," "a three-sentence summary for a slide deck," or "a paragraph I can send to my boss." This saves you from having to reformat the response later.

Final Thoughts

Getting Google Analytics data into Claude unlocks a faster, more intuitive way to understand your website's performance. Whether you use a simple manual CSV export for a quick look, an automated API script for regular reporting, or a Google Sheet to bridge the gap, the key is to feed the AI clean data and then ask clear, specific questions.

Manually exporting data or setting up APIs can still be a hurdle to getting quick answers. For this reason, we designed Graphed to be the simplest way to get insights from your analytics. Instead of exporting CSVs or writing code, you just connect your Google Analytics account once. From there, our purpose-built AI already understands all your metrics and dimensions, so you can immediately ask questions in plain English - like "Compare my organic traffic versus paid traffic this month" - and get back live, interactive charts and dashboards without any friction.