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How to Create a Product Management Dashboard in Google Sheets with AI

Cody Schneider•

Building a great product starts with understanding how people are using it, and that means turning raw data into clear, actionable insights. A product management dashboard is your mission control, giving you a high-level view of product health and performance. This guide will walk you through setting one up in Google Sheets and then supercharging it with built-in AI tools to get you from raw numbers to smart decisions faster.

Why a Product Dashboard Is a PM's Best Friend

A Product Management (PM) dashboard centralizes your most important key performance indicators (KPIs) into a single, easy-to-understand view. Instead of digging through multiple analytics tools every morning, you get an at-a-glance summary of what’s working, what isn't, and where you need to focus your attention. It's the key to making informed, data-driven decisions instead of relying on hunches.

So, why Google Sheets? It's free, universally accessible, and built for collaboration. But the real game-changer is the growing library of AI features that automate analysis and spot trends you might otherwise miss. It levels the playing field, making powerful data analysis available to everyone, not just data scientists.

Choosing the Right Product Metrics to Track

The first step in building any dashboard is deciding what to measure. A common mistake is trying to track everything. This leads to a cluttered, confusing dashboard that’s full of noise. Instead, focus on a handful of core metrics that directly reflect your current product goals. Organize them into logical categories.

Acquisition & Activation

These metrics tell you how effective you are at attracting new users and getting them to experience your product's core value for the first time.

  • New User Signups: The absolute number of new people creating an account. It’s a fundamental measure of growth.

  • Activation Rate: The percentage of new users who complete a key action that signals they've "activated" (e.g., for a SaaS project tool, it might be creating their first project). This measures how well you're delivering on your initial promise.

  • User Acquisition Cost (UAC): The total cost of sales and marketing to acquire one new customer. Keep an eye on this to ensure your growth is sustainable.

Engagement & Retention

Once users are on board, are they sticking around and using the product? These metrics answer that question.

  • Daily/Monthly Active Users (DAU/MAU): The number of unique users who engage with your product on a given day or month. The DAU/MAU ratio is a fantastic indicator of product "stickiness."

  • Session Duration: The average amount of time a user spends in your product per session. Longer sessions often correlate with higher engagement.

  • Feature Adoption Rate: The percentage of users who use a specific feature. This is great for understanding which features are resonating and which ones might need improvement or promotion.

  • Churn Rate: The percentage of users who stop using your product over a specific period. You want to keep this number as low as possible.

Business & Revenue

Ultimately, a successful product needs to support the business. These metrics connect product usage to financial health.

  • Monthly Recurring Revenue (MRR): For subscription-based businesses, this is the total predictable revenue you expect to receive each month. It's a key indicator of your company's health and growth trajectory.

  • Customer Lifetime Value (LTV): The total revenue a business can expect from a single customer account throughout their relationship.

  • Average Revenue Per User (ARPU): The average amount of revenue generated per user. This helps you understand the value of an average user.

Setting Up the Foundation in Google Sheets

A well-structured spreadsheet is crucial for a dashboard that’s easy to update and understand. The best practice is to separate your data, calculations, and presentation into different tabs.

Step 1: The "Raw Data" Tabs

The first rule of dashboard creation: never do your calculations in the same place you store your raw data. Create separate tabs for each data source. For example, you might have:

  • A "User Signups" tab, with columns for User ID, Signup Date, and Acquisition Source.

  • An "Events" tab, where you log key user actions like "Project Created" or "Feature Used," with corresponding timestamps.

  • A "Subscription Data" tab, with data exported from Stripe or your payment processor showing Customer ID, MRR, and plan type.

Keeping raw data pristine ensures that if you make a mistake in a formula, you can always go back to the original source without having to re-export everything. For truly automated reporting, you can use tools like Zapier or Make.com to automatically send new data to these tabs from your other apps.

Step 2: The "Calculations" Tab

This is where the magic happens. This intermediary tab is your workshop. It pulls from your "Raw Data" tabs and performs all the necessary calculations to generate your KPIs.

For example, to calculate your New User Signups for the current month, you might use a formula like this:

=COUNTIFS('User Signups'!B:B, ">=,"&EOMONTH(TODAY(),-1)+1, 'User Signups'!B:B, "<="&EOMONTH(TODAY(),0))

Here, you'd calculate your Churn Rate, Activation Rate, DAU, and every other key metric. This keeps your dashboard clean and focuses it solely on visualization, while all the heavy lifting happens here in the background.

Step 3: The "Dashboard" Tab

This is your presentation layer - the polished, final product you and your team will view daily. This tab should contain no complex formulas. Every number and chart should simply reference cells from your "Calculations" tab.

Set up a clean grid. Use large, bold fonts for your main KPIs so they're visible at a glance. We’ll design this in the next section.

Bringing Your Dashboard to Life

Now that the groundwork is laid, it's time to build the visual part of the dashboard.

1. Create Summary KPI Boxes

The top of your dashboard should feature the most critical numbers: Total Users, MRR, Active Users this Month, etc. Create simple boxes for those. To display your MRR, you just type = in a cell and click over to your "Calculations" tab to select the final MRR value you calculated. Simple and effective.

2. Visualize Trends with Charts

Numbers are great, but charts are better for spotting trends. Some must-have charts include:

  • Line Chart: Perfect for tracking metrics over time, such as User Growth, MRR Growth, or DAU over the last 30 days.

  • Bar Chart: Great for comparing categories, like Feature Adoption Rates or Traffic by Acquisition Channel.

  • Pie Chart: Use this carefully, but it can be effective for showing composition, such as the breakdown of users by subscription plan.

To create a chart, just highlight the data in your "Calculations" tab (e.g., Date and New Users), go to Insert > Chart, and customize it. Move the final chart to your "Dashboard" tab.

3. Use Conditional Formatting

Draw attention to important shifts with color. Use conditional formatting (Format > Conditional formatting) to turn a cell red if your churn rate increases above a certain threshold, or green if your activation rate hits its target. This makes monitoring your product's health a subconscious, instant process.

Supercharging Your Analysis with AI in Google Sheets

This is where things get really interesting. Google Sheets is not just a static grid anymore. Its AI features can help you uncover insights and automate tedious data cleanup.

Use the Explore Feature for Instant Analysis

Don't know where to start? Google can help. Lying in the bottom-right corner of your sheet is the "Explore" button (an icon with a sparkle). Highlight a range of your raw data - for instance, your user signup data - and click it. Explore will instantly analyze the data and suggest questions you can ask in plain English ("What is the distribution of Signup Date?"). Even better, it will generate charts and calculations for you automatically, which you can drag and drop right into your dashboard.

Automate Data Cleanup with Smart Fill

Often, your raw data isn't perfectly clean. Maybe you have a column with full names ("John Doe") and you need to create a column with email addresses ("johndoe@company.com"). Instead of writing a complex formula, you can now just start typing the pattern for the first two or three rows. Google Sheets' AI will recognize the pattern and offer to "fill" the rest of the column for you. It's an incredibly powerful way to speed up the data prep process.

Predict Future Performance with the FORECAST Function

Want to know where you're headed? The FORECAST function uses linear regression to predict a future value based on your historical data. Let's say you have monthly user growth data for the past year and want to estimate what it will be next month. You can use this simple formula:

=FORECAST(new_date, range_of_historical_data, range_of_historical_dates)

This adds a powerful predictive element to your dashboard, helping you set more realistic goals and anticipate resource needs.

Final Thoughts

Creating a product management dashboard in Google Sheets puts you firmly in control of your product’s narrative. By centralizing key metrics and using smart visualization techniques, you can turn a flood of data into a clear story. Layering on the native AI tools in Google Sheets takes it a step further, helping you move from simply reporting numbers to analyzing trends and predicting the future.

While Google Sheets is an amazing tool, keeping all of your raw data tabs in-sync with your live analytics tools still involves a lot of manual exporting and copy-pasting. That’s why we built Graphed. We automate the entire process by connecting directly to your tools like Google Analytics, Stripe, HubSpot, and Mixpanel. You can simply ask questions in plain English, and our AI builds real-time, interactive dashboards instantly, freeing you from spreadsheet management so you can spend your time building a better product.