How to Create an Inventory Dashboard in Google Analytics with AI

If you run an e-commerce store, your product inventory data lives in one place - like Shopify or a PIM - and your website behavior data lives in another: Google Analytics. A common goal is to connect these two worlds to understand which marketing efforts drive interest in the products you actually have in stock. This article will show you how to skip the complicated technical setup and use a modern, AI-powered approach to build a single dashboard that tells the full story.

Why Bother Tracking Inventory and GA Data Together?

Connecting your on-hand stock levels with website traffic might not seem obvious at first, but it unlocks critical insights that neither platform can give you on its own. When you can see both datasets side-by-side, you can answer important questions like:

Which struggling products get a lot of attention? You might have a product with low sales but tons of page views. This isn't a "bad product," it's a conversion problem. Maybe the price is wrong, the images are bad, or the description is unclear. GA's traffic data shows you a product has demand, even if inventory data shows it isn't selling.
How much demand exists for out-of-stock items? Every page view on a "sold out" product page is a lost sale you can now quantify. Tracking this tells you exactly which products to reorder first and might even justify an email notification list for that item.
Are my marketing campaigns driving traffic to items we can't sell? It's a waste of advertising budget to send thousands of clicks to a product page that's been out of stock for weeks. A unified dashboard immediately flags this mismatch, allowing you to pause campaigns and redirect your spend.
Which slow-moving products should we promote next? Find products with high stock levels but low page views. These are your ideal candidates for a flash sale, an email campaign feature, or your next social media ad push.

Essentially, this approach moves you from just tracking sales to understanding the demand behind your products, letting you make smarter marketing and inventory decisions.

The Data You Need: From GA and Your Store

To build a useful dashboard, we need to bring together two different types of information. It sounds complex, but breaking it down shows how simple the pieces really are.

From your E-commerce Platform (like Shopify, WooCommerce, etc.):

Product SKU: The unique identifier for each product/variant. This is the "key" that will help us connect our two datasets.
Product Name: The customer-facing name of the item.
Inventory Level (Stock): The exact number of units you have available.
Price: The selling price of the product.
Total Revenue (per product): The total sales generated by that product.

From Google Analytics:

Item ID: This should match your Product SKU in your e-commerce platform. Ensuring these match is vital for blending the data.
Item Name: The product name tracked in GA4.
Item Views (a.k.a. Product Detail Views): The number of times visitors looked at a specific product page.
Adds to Cart: How many times a product was added to a shopping cart.
Sessions by Channel: The marketing channels (Organic Search, Paid Social, Email, Direct, etc.) that brought visitors to your product pages.

The goal is to analyze something like Item Views side-by-side with Inventory Level for the same product - all in one chart.

The Old Way vs. The AI-Powered Way

Historically, building a dashboard like this was a huge pain. E-commerce platforms and Google Analytics don't naturally talk to each other about stock levels. Getting this data into one place involved a few frustrating options:

Manual CSV Exports: The classic "Monday morning reporting" routine. You'd export product data from Shopify, traffic data from GA, and then spend hours Frankenstein-ing them together in a spreadsheet using VLOOKUP formulas. It's time-consuming, prone to errors, and the data is stale the moment you export it.
Developer-Heavy Solutions: Another path was using Google Analytics' Measurement Protocol to send "events" about your daily inventory counts directly to GA. This required custom code, a developer's time, and careful maintenance to ensure nothing broke. It was powerful but expensive and out of reach for most marketing teams.

Neither of these is ideal. The modern approach flips this on its head. Instead of trying to force inventory data into Google Analytics (or vice versa), you connect both platforms to an AI-powered analysis tool that can read and understand data from each source simultaneously.

How to Create the Dashboard with an AI Data Analyst

Think of using an AI data tool as hiring a junior analyst who is an expert in both Shopify and Google Analytics. You don't have to do the manual work, you just have to tell them what you want to see. The process is now about describing the outcome you want, not wrestling with the data yourself.

Step 1: Connect Your Data Sources in a Few Clicks

First, you need to grant the AI tool read-only access to your data. Good tools don't use dated CSV uploads, they use secure, direct integrations.

Connect Google Analytics: This usually involves a standard Google login (OAuth) where you simply select the Google Analytics account and property you want to use.
Connect Your E-commerce Platform: Similarly, you'll connect Shopify, WooCommerce, or your platform of choice through a secure, one-click authentication process. The tool then automatically begins to understand the structure of your product data.

With this, you've replaced hours of future exporting and data cleaning with about two minutes of setup. The tool now has a live, real-time connection to both stock levels and website traffic.

Step 2: Ask Plain-English Questions to Build Your Charts

This is where everything changes. Instead of dragging and dropping fields or writing formulas, you just type what you want to see in a chat interface. The AI translates your request into the charts and tables you need.

Let’s start simple and build up from there.

Prompt #1: Get your top products from GA.

The AI will query Google Analytics and instantly generate a table of your most popular products based on page views.

Prompt #2: Blend GA data with Shopify inventory.Now, let's bring in the inventory data. You can just ask for it as a follow-up.

The AI already knows the "Product SKU" and "Item ID" are the common fields. It automatically joins the two datasets and adds the inventory column right next to the page views. For the first time, you have live traffic and inventory data side-by-side without a spreadsheet.

Prompt #3: Find your best opportunity.Let's create something more strategic - a visualization of your underperforming products that have high demand but need a marketing push.

The resulting chart is pure gold. Products in the bottom-right corner are your hidden gems: they get tons of views (far to the right on the chart) but have low sales (near the bottom). You now have a data-driven list of products to promote.

Step 3: Keep Asking Questions to Uncover More Insights

The real power of this conversational approach is that each answer inspires a new question. You can drill down deeper and deeper without starting over.

You might follow up on your scatter plot with a question like:

Or you could build a safety net to prevent wasted ad spend:

Lastly, you can ask the AI to turn your collection of charts into a single, cohesive dashboard that you can refer back to at any time. Because the data connections are live, the dashboard will update automatically.

Must-Have Visualizations for Your Inventory Dashboard

Once you get the hang of asking questions, here are a few essential charts to create for your master inventory dashboard:

Top 10 Viewed Products with Stock Levels: A simple table that includes columns for Item Name, GA Item Views, Shopify Stock Level, and Shopify Revenue. This gives you a daily snapshot of supply and demand.
Views on Out-of-Stock Products: A KPI card or simple number showing the total page views on products with an inventory of 0 in the last 30 days. This quantifies your "missed opportunity" so you can prioritize restocking.
Sales Velocity vs. Stock Remaining: A report that shows items that are selling fast and are in danger of running out. You could ask for "a table of products with more than 10 sales in the last 7 days and fewer than 20 units in stock."
High Stock / Low Traffic Report: The opposite of the "hidden gems" report. This is a list of overstocked products that aren't getting any love online. Ask for "products with stock over 100 but fewer than 50 page views last month." This is your "clearance sale" list.

Final Thoughts

Building an inventory dashboard that pulls from Google Analytics and your e-commerce platform used to mean choosing between hours of frustrating spreadsheet work or a hefty developer bill. Today, the process is far simpler: connect your platforms once, then describe the charts you need in plain English.

At Graphed, we designed our platform to do exactly this. Instead of you needing to learn a complex BI tool or figure out how to join data from multiple sources like Google Analytics and Shopify, we enable you to just ask for what you need. Our AI understands the data structures of these platforms, allowing you to build real-time, cross-platform dashboards in seconds and finally get a clear, complete picture of your e-commerce performance.