How to Make a Circle Chart in Google Analytics with AI
Creating a circle chart - like a pie or donut chart - from your Google Analytics data should be a straightforward task, but it often isn't. You're just trying to get a simple, visual breakdown of your traffic sources or user demographics, not spend your afternoon wrestling with spreadsheets. This guide will walk you through how to create these visualizations, first the traditional way, and then the much faster way using AI.
What is a Circle Chart and When Is It a Good Idea?
Before building one, it helps to know when a circle chart is the right choice. Circle charts (both pie and donut charts) are designed to show a "part-to-whole" relationship. They're perfect when you want to visualize how different categories contribute to a total amount.
Think of it like slicing up a pizza. The whole pizza is your total website traffic, and each slice represents a different traffic source (Organic, Direct, Social Media, etc.). You can instantly see which slice is the biggest.
Use a circle chart when:
You're comparing a small number of categories (ideally 2-6). Too many slices make the chart cluttered and hard to read.
The parts must add up to 100%. For example, the percentage of users on desktop, mobile, and tablet must equal 100% of all users.
You want to provide a quick, high-level overview of the composition of your data.
Common examples for Google Analytics data include:
Traffic Sources: What percentage of sessions come from Organic Search, Paid search, Social, etc.?
Device Categories: How many of your users are on Desktop vs. Mobile vs. Tablet?
User Demographics: What's the breakdown of your audience by country or gender?
Top Channels: Which session default channel groups are driving the most new users?
For more complex comparisons over time or when dealing with many categories, a bar chart or line chart is often a better choice. But for a simple, compelling snapshot, the circle chart is an excellent tool.
The Traditional Method: Manually Making a Chart After Exporting from GA4
Google Analytics 4 has some built-in charting capabilities, but they can be limited, and customizing them isn't always intuitive. The most common "traditional" workflow involves exporting your data from GA4 and building the chart in a spreadsheet program like Google Sheets or Excel. It works, but it takes time and several steps.
Let's walk through an example of creating a chart for website traffic by device category.
Step 1: Get the Right Data from Google Analytics 4
First, you need to find the data inside your GA4 property. For our example, we'll look for user device types.
Log into your Google Analytics 4 property.
In the left-hand navigation menu, click on Reports.
Under the "User" collection, click on Tech → Tech details.
The default report dimension will likely be "Browser." We need to change this. Click the dropdown arrow next to "Browser" and select Device category.
Now you'll see a table showing sessions, users, and engagement metrics broken down by Desktop, Mobile, and Tablet. This is the raw data we need for our chart.
Step 2: Export Your Data to Google Sheets or Excel
Once you have the table displayed, you need to get it out of Google Analytics.
In the top right corner of the report, you'll see a "Share this report" icon (usually a box with an arrow). Click on it, then click "Download File."
You can choose to download the data as a CSV or PDF. For our purpose, a CSV (Comma Separated Values) file is what you want, as it can be opened by any spreadsheet program.
Step 3: Prepare the Data for Charting
This is where the manual work really begins. When you open your downloaded CSV file in Google Sheets or Excel, it won't be perfectly formatted. GA4 exports often include introductory rows, summary information, or blank columns that get in the way.
Delete any extra rows at the top of the spreadsheet (like the report title, date range, etc.).
You only need two columns for a pie chart: the category names (Desktop, Mobile, Tablet) and the numeric values (usually Sessions or Users). Delete all other columns to avoid confusion.
Ensure your numbers are formatted as numbers, not text.
After a bit of cleanup, you should have a clean, simple table with just two columns: Device category and Sessions.
Step 4: Build Your Circle Chart in the Spreadsheet
With your data nice and tidy, you're ready to create the visualization.
In Google Sheets:
Highlight the data you cleaned up in the previous step, including the column headers.
Go to the main menu and click Insert → Chart.
Google Sheets is pretty good at guessing what you want and will probably default to a pie chart. If not, the Chart Editor sidebar will appear on the right. Under "Chart type," find and select the Pie chart.
Use the "Customize" tab in the Chart Editor to adjust the colors, add a title like "Website Sessions by Device," and change the font or labels.
And there you have it — a circle chart made from Google Analytics data. This process is effective, but it involves logging into GA4, navigating to the right report, exporting a file, cleaning it up, and finally building the chart. If your boss asks a follow-up question or wants the same report next week, you have to do it all over again.
The A.I. Way: Create a Circle Chart in Just a Few Seconds
Instead of manually finding, exporting, and building, you can now use AI-powered analytics tools to do the heavy lifting for you. These platforms connect directly to your Google Analytics account, so the data is always live. To create a chart, you simply ask for it in plain English.
This approach transforms reporting from a multi-step chore into a simple conversation.
How A.I.-Powered Chart Creation Works
The process is incredibly simple because the complexity is handled for you. After connecting your GA4 account (which is typically a one-time, 3-click setup), you can start asking for visualizations immediately.
Instead of the four-step manual process, you just type a prompt, such as:
“Show me a pie chart of website sessions by device category for the last 30 days.”
What happens next feels like magic, but it's just technology. The AI platform:
Understands Your Request: It parses your natural language, recognizing key elements like the chart type ("pie chart"), the metric ("sessions"), the dimension ("device category"), and the time frame ("last 30 days").
Queries Your Live Data: It automatically pulls the relevant data directly from your Google Analytics property in real-time. There are no static CSV files involved.
Generates the Visualization: It builds the correct chart for you instantly.
The result is a clean, accurate circle chart in seconds, with zero manual data wrangling.
More Examples of Natural Language Prompts:
"Create a donut chart showing the top 5 countries by new users this year."
"What is the breakdown of my traffic sources this month? Show it as a circle chart."
"Compare revenue from organic search vs paid search for last quarter in a pie chart."
Why A.I. is a Far Better Approach for GA4 Reporting
This isn't just about saving a few minutes. Adopting an AI-driven workflow fundamentally improves how you and your team interact with your data.
1. Incredible Speed and Efficiency
The most obvious benefit is speed. A task that takes 10-15 minutes manually is done in under 30 seconds. This adds up. Teams that run weekly reports often dedicate Monday mornings to downloading CSVs and updating dashboards. With AI, a recurring report becomes an automated, live dashboard that's always ready, freeing your team to focus on analyzing the insights, not just gathering them.
2. No Experience or Technical Skills Required
You no longer need to be a spreadsheet expert or a master of GA4’s labyrinthine interface. If you can ask a question, you can get insights. This democratizes data access, empowering marketers, content creators, and junior team members to answer their own questions without needing to wait for a data analyst. It fosters a more data-informed culture throughout the entire organization because data becomes accessible to everyone.
3. Effortless Drill-Down and Analysis
Analytics is an iterative process. A chart often leads to another question. With the manual method, each new question means repeating the export-and-build process. With an AI tool, it's just a follow-up conversation.
Imagine your pie chart shows that "Organic Search" is your biggest traffic driver. Your next question might be, "Okay, interesting. Now show me a bar chart of the top landing pages just for organic traffic." You can just type that and instantly get the next layer of detail, allowing you to explore your data at the speed of thought.
4. Always Live and Accurate
A downloaded CSV is a snapshot in time. The minute you export it, it's already out of date. Reports built this way are stale. Since AI tools connect directly to the source, your charts and dashboards are always reflecting the very latest data. If your site got a huge traffic spike five minutes ago, you’ll see it reflected in your chart immediately.
Final Thoughts
Creating circle charts from your Google Analytics data should be a simple process for getting quick, visual insights, but the manual method of exporting CSVs and fighting with spreadsheets has always made it a tedious chore. By leveraging AI, you can completely skip the manual work and move straight to the answer.
This is exactly why we built Graphed. We turn hours of data pulling into seconds of conversation. Simply connect your Google Analytics account once, and you can create live, interactive dashboards using natural language. A prompt like “build a dashboard showing my top traffic sources as a pie chart and my best-performing content in a table” generates a real-time report instantly, getting you the insights you need faster than ever before.