Graphed LogoGraphed
Login

How to Create a Sales Report in Google Analytics with AI

Cody Schneider•

Creating a sales report in Google Analytics should be simple, but the reality is often a frustrating cycle of clicking through menus, wrestling with dimensions, and trying to make sense of the GA4 interface. This tutorial cuts through the noise. We'll walk you through how to manually build a valuable sales report in Google Analytics, then show you how AI can completely transform the process, turning hours of work into a few seconds.

First Things First: Is Your E-commerce Tracking Set Up Correctly?

Before you can report on sales, you have to be tracking them. This is the single most important prerequisite. Without proper e-commerce tracking, Google Analytics has no sales data to show you, no matter how skilled you are with its reporting tools. For your reports to work, GA4 needs to receive information when a user takes specific actions on your site.

While a full setup is beyond the scope of this article, here’s a quick checklist of the essential e-commerce events you need to be tracking, typically through Google Tag Manager (GTM):

  • view_item: When a user views a specific product page.

  • add_to_cart: When a user adds an item to their shopping cart.

  • begin_checkout: When a user starts the checkout process.

  • purchase: The most critical event, fired when a user completes a transaction. This event should include parameters like transaction ID, value, currency, tax, shipping, and details about the items purchased.

If you're not seeing any data in the 'Monetization' or 'Ecommerce purchases' reports in GA4, it's almost certain that your e-commerce tracking is either missing or misconfigured. You might need a developer's help, or you can often use a pre-built Shopify or WooCommerce integration to handle this, but it’s a non-negotiable step.

How to Manually Build a Sales Report in GA4

Once you've confirmed that sales data is flowing into Google Analytics, you can start building reports. The standard 'Ecommerce purchases' report is a good starting point, which you can then customize to fit your specific needs.

Step 1: Navigate to the Monetization Reports

In the left-hand navigation panel of Google Analytics, follow this path:

Reports → Monetization → Ecommerce purchases

By default, this report shows you a list of your products along with metrics like Item views, Add-to-carts, Items purchased, and Item revenue. A line chart at the top visualizes this data over time.

Step 2: Customize Your Dimensions and Metrics

This default report is useful, but its true power comes from customization. Let’s say you don’t just want to know what sold, but how it sold — which marketing channels are actually driving revenue?

  1. Click the pencil icon in the top-right corner of the report screen to open the 'Customize report' interface.

  2. On the right panel, click on 'Dimensions'. This is where you can change how your data is grouped. The default is 'Item name'. You can add other dimensions like 'Item ID', 'Item brand', or, for our example, 'Session source / medium' to see which channels are driving purchases.

  3. Drag and drop 'Session source / medium' to be your primary dimension.

  4. Next, click on 'Metrics'. Here you can add, remove, or reorder the data points you see in the report. Make sure key metrics like 'Transactions', 'Ecommerce revenue', and 'Ecommerce conversion rate' are included.

  5. Click the blue 'Apply' button at the bottom right.

You now have a custom report showing exactly which marketing sources (e.g., 'google / organic', 'facebook / cpc') are generating the most revenue for your business.

Step 3: Save Your Report for Easy Access

Once you’re happy with your new report view, don’t lose it! Click the 'Save' button in the top right, and choose 'Save as new report'. Give it a clear name like "Sales Report by Channel." This will store it in the 'Library' section of GA4 so you and your team can access it again with one click.

For More Advanced Analysis: Use the Explore Hub

Sometimes you need to slice and dice your data in ways that the standard reports can't handle. That's what the 'Explore' hub is for. It lets you build fully custom pivot tables, funnel explorations, and segment overlaps.

For example, you could create a 'Free-form exploration' using 'Session source / medium' as your rows, 'Device category' as your columns, and 'Ecommerce revenue' as your value. This would create a pivot table showing you the revenue from each channel, broken down by desktop, mobile, and tablet users.

The downside? The Explore hub has a much steeper learning curve. It's incredibly powerful but not very intuitive for everyday users.

The Problems with Manual Sales Reporting

If the steps above feel a bit clunky, you're not alone. Manually building reports in Google Analytics, especially for team members who aren't data experts, comes with a few significant headaches.

  • It's Slow and Repetitive: Building that "Sales Report by Channel" didn't take an entire day, but what happens when your manager immediately asks, "Great, now can you show me this but only for last quarter and broken down by product category?" You're back to clicking, dragging, and customizing all over again. Reporting becomes a constant cycle of manual data pulls.

  • The Interface Isn't Intuitive: Understanding the difference between 'Item scope' dimensions, 'Session scope' dimensions, and 'User scope' dimensions takes time. It’s powerful, but it’s not designed for the marketer who just needs a quick answer before a meeting.

  • Data Lives in Silos: Your Google Analytics sales report shows you a shopper's final steps, but what about the journey that led them there? How much did you spend on a specific Facebook ad that resulted in a specific GA4 purchase? GA4 can't tell you that on its own. It's just one piece of the puzzle, and stitching performance data together from your ad platforms, CRM, and Shopify requires exporting CSVs and fighting with spreadsheets.

  • It Limits Curiosity: Often, an initial chart or table leads to a follow-up question. "Why did revenue spike on Tuesday?" "Are we getting more traffic from the UK, or are those visitors just converting better?" Manually rebuilding a report for each new question is so tedious that people often stop asking.

A Faster Way: Use AI to Create Your GA4 Sales Reports

This is where things get interesting. Instead of learning the intricacies of a complex analytics tool, you can simply ask for the report you want using plain English. AI tools designed for data analysis connect directly to your Google Analytics account and act as your personal data analyst.

How Natural Language Reporting Works

The entire process is designed to remove friction. After a one-time connection to your Google Analytics account, you can simply type your request into a chat interface.

Forget hunting for the right dimension. Just ask:

"Create a line chart of my ecommerce revenue in GA4 for the last 90 days."

The AI understands what "ecommerce revenue" means within the context of GA4, interprets "last 90 days," and instantly generates the exact line chart you asked for, pulling live data from your account.

The real magic lies in the ability to drill down with follow-up questions. Say the chart looks great, but you need more detail. You can just continue the conversation:

"Okay, now show that as a table and break it down by traffic source."

Instantly, the view changes to a table showing each marketing channel's revenue contribution.

"Filter that for just the US traffic."

And just like that, the report is filtered. This conversational approach turns data analysis from a chore into an exploration. You can follow your curiosity and dig deeper into what a chart is telling you without ever leaving the interface or manually re-building a report.

From a Single Source to a Complete Picture

AI tools don't have to stop at Google Analytics. The biggest analytics challenge for most businesses is that their data is scattered across a dozen different platforms. Your ad spend is in Facebook Ads, your conversion data is in Google Analytics, your customer data is in HubSpot, and your final sales data is in Shopify.

An AI data analysis tool can connect to all of these sources. This allows you to ask much bigger, more valuable questions:

  • "What was my total Shopify revenue vs. Facebook ad spend for the 'Summer Sale' campaign?"

  • "Create a funnel report showing leads from Google Ads, MQLs from Salesforce, and closed-won deals."

  • "Which Klaviyo email flow has the highest ROI when you factor in my Shopify AOV?"

These are the questions that truly drive business growth — and they're nearly impossible to answer with manual reporting without hours of spreadsheet wrangling. With AI, a manager can get a birds-eye view of business performance, tracked against their core KPIs, in one simple dashboard.

Final Thoughts

Knowing how to navigate Google Analytics to get sales data is a valuable skill. By customizing GA4's native templates or using the Explore hub, you can get a solid overview of your e-commerce performance. But this manual method is often slow, requires technical knowledge, and keeps your data trapped in silos.

At the end of the day, digging through analytics platforms is a means to an end. It's why we built Graphed to be an easier, more intuitive way to connect to your platforms like Google Analytics, ask questions, and get insights in seconds. Instead of wrestling with data tables, you can create real-time sales dashboards just by describing what you want to see. We connect directly to all your key sources, from GA4 and Shopify to your ad platforms and CRM, so you can stop cobbling together reports and start making better, faster decisions.