How to Create an E-commerce Dashboard in Excel with AI

Trying to understand your e-commerce store’s performance by bouncing between Shopify, Google Analytics, and your ads manager is like trying to put together a puzzle in the dark. You can feel the pieces, but you can’t see the big picture. This guide will show you how to pull all those pieces together by building a powerful e-commerce dashboard right inside Excel, using new AI tools to do the heavy lifting for you.

Why You Need a Central E-commerce Dashboard

Every decision you make - from adjusting ad spend to launching a new product - should be backed by data. An e-commerce dashboard isn’t just a collection of charts, it’s the control center for your business. It consolidates scattered metrics from various platforms into one clear, scannable view, allowing you to spot trends, identify problems, and find opportunities at a glance. What gets measured gets managed, and a good dashboard helps you focus on the metrics that actually matter for growth.

Instead of spending three hours every Monday pulling CSV files and wrestling with pivot tables, an effective dashboard gives you answers in minutes. It helps you understand the story behind your numbers: how your marketing campaigns are impacting sales, which products are your real winners, and where your customer journey might be breaking down.

Choosing the Right Metrics for Your Dashboard

A cluttered dashboard is just as useless as no dashboard at all. The goal is clarity, not complexity. Your dashboard should tell a story about your business performance. Start by organizing it into a few key areas that track the entire customer journey, from first click to repeat purchase.

Sales & Revenue KPIs

• Gross and Net Sales: The absolute top-line numbers. Gross sales is your total revenue, while net sales is that figure minus returns, allowances, and discounts. You need to see both.

• Average Order Value (AOV): This tells you how much customers spend on average per transaction. A rising AOV means your strategies to increase basket size (like upselling or product bundling) are working. Use the formula: Total Revenue / Number of Orders.

• Customer Lifetime Value (CLV): One of the most important metrics. It tells you the total revenue you can expect from a single customer over the entire course of your relationship. A high CLV indicates customer loyalty and good product-market fit.

• Purchase Frequency: How often does the average customer buy from you? Increasing this number is a key lever for growing revenue without constantly needing new customers.

Marketing & Acquisition KPIs

• Total Traffic & Traffic by Source: Where are your visitors coming from? Organic search, paid ads, social media, or email? Knowing this helps you understand which channels are driving awareness and where to double down on your efforts.

• Overall Conversion Rate: The percentage of website visitors who make a purchase. This is the ultimate health score for your online store. Use the formula: (Total Orders / Total Visitors) * 100.

• Customer Acquisition Cost (CAC): How much does it cost you to acquire a new customer? If your CAC is higher than your AOV or projected CLV, your business model isn’t sustainable. Use the formula: Total Marketing Spend / Number of New Customers.

• Return on Ad Spend (ROAS): For every dollar you spend on advertising, how many dollars in revenue are you getting back? This is a non-negotiable metric for any paid advertising campaigns. Use the formula: Total Revenue from Ads / Total Spend on Ads.

Inventory & Operations KPIs

• Top-Selling Products: Which of your products are the stars? Knowing this helps with inventory planning, marketing campaigns, and what to feature on your homepage.

• Inventory Levels: Tracking in-stock levels for your key products helps prevent stockouts that can kill momentum and frustrate customers.

• Order Return Rate: What percentage of orders are being returned? A high return rate might point to issues with product quality, descriptions, or fit.

Getting Your Data Ready for Analysis

This is where most reporting processes stall. Getting data out of platforms like Shopify, Google Analytics, Facebook Ads, and Klaviyo and into Excel is traditionally a manual, time-consuming drag.

The old method involves logging into each platform, setting date ranges, exporting a CSV file, and then trying to copy and paste it all into a single "master" spreadsheet. This is not only tedious but also incredibly prone to errors. One copy-paste mistake can throw off your entire report. Plus, the moment you finish, the report is already out of date.

A slightly better approach is to use tools like Zapier or Make.com to pipe data from these sources into a central Google Sheet. From there, you can connect your Excel workbook to the Google Sheet. While this adds a layer of automation, it still requires setup and maintenance. For our purposes, let's assume you've used one of these methods to gather your core sales and traffic data into a clean table inside a single Excel sheet.

Example Data Table Structure

For your dashboard to work, you need your data organized in a simple, flat table. Here’s a basic example of what that might look like:

Building Your Excel Dashboard with AI

Once your data is clean and organized, the fun starts. In the past, this meant spending hours writing SUMIFS formulas, building complex PivotTables, and meticulously designing charts. While those methods still work, AI features built directly into Excel can build most of your dashboard for you in seconds.

Method 1: Using Excel's Built-In "Analyze Data" Feature

Excel's "Analyze Data" tool (previously called "Ideas") is an incredible starting point. It uses AI to scan your dataset, identify patterns, and automatically generate charts and PivotTables that might be interesting. You can also ask it questions in plain English.

Here’s how to use it:

1. Click any cell inside your data table.

2. Go to the Home tab on the ribbon and click the Analyze Data button on the far right.

3. A pane will open on the right-hand side with suggested charts and analyses.

4. Look for a good starting point, like "Total Sale by Traffic Source," and click Insert PivotChart. Excel will instantly create a new worksheet with the fully functioning PivotTable and chart.

5. You can ask your own questions at the top of the pane. Try typing: "monthly sales in a line chart" or "top 5 products by units sold".

This is the fastest way to generate the core visualizations for your dashboard. Create each chart on a separate sheet first, then you can copy and paste just the finished charts onto a single "Dashboard" worksheet later.

Method 2: Leveraging Copilot for Custom Calculations and Charts

If you have a Microsoft 365 Copilot subscription, you have an even more powerful AI assistant. Copilot can understand much more flexible requests. It can clean your data, add new calculated columns, and generate complex analysis without you writing a single formula.

With your data table selected, you can ask Copilot for things like:

• "Add a column to calculate the AOV for each transaction." (if you have order data)

• "Show an area chart of sales by month for the 'Apparel' category."

• "Create a summary that highlights our top 3 traffic sources and their total sales."

• "Write a formula in cell K2 that calculates the month-over-month growth in sales."

This transforms the dashboard creation process from manual construction into a simple conversation. It's like having a data analyst on your team helping you build the report.

Designing Your Dashboard Layout

After using AI to generate your key charts, it's time to assemble them into a clean, easy-to-read dashboard.

1. Create a new, blank worksheet and name it Dashboard.

2. Copy each chart you've created (not the PivotTable, just the chart itself) and paste it onto your Dashboard sheet.

3. Arrange the charts logically. Place your most important, high-level KPIs (like total sales and AOV) at the top. Place more detailed charts (like sales by product) below.

4. Add Slicers for interactivity. Click on any PivotChart, go to the PivotChart Analyze tab, and click Insert Slicer. Choose a field like "Date" or "Traffic Source." This adds a clickable filter button that controls multiple charts at once, letting you drill down into your data without leaving the dashboard.

Final Thoughts

Creating an e-commerce dashboard in Excel used to be a frustrating process reserved for spreadsheet experts. With new AI features, that barrier is gone. Anyone can now connect their data, ask plain-language questions, and produce a powerful, insightful dashboard that helps them make smarter decisions and grow their business faster.

We believe getting these insights should be simple. While building your own dashboard in Excel is a great step forward, it still requires manual CSV wrangling, and the report is only as recent as your last data export. At Graphed , we automate the entire process by connecting directly to your tools like Shopify, Google Analytics, and Facebook Ads. Instead of downloading files, you just ask questions like, "Show me a dashboard of my marketing funnel" or "Which products have the best ROAS this month?" We build a real-time dashboard for you in seconds that updates automatically, so you're always making decisions based on live data, not outdated spreadsheets.