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How to Create a Mobile App Dashboard in Excel with AI

Cody Schneider•

Building a mobile app dashboard in Excel can feel like a necessary evil. You know you need to track your performance, but wrestling with endless CSVs, complex formulas, and pivot tables can quickly become a full-time job. This guide will walk you through how to create a useful mobile app dashboard in Excel and show you how AI can drastically simplify the entire process, turning hours of tedious work into a few straightforward steps.

Why Build a Mobile App Dashboard in the First Place?

Before jumping into the “how,” let’s quickly cover the “why.” A dashboard isn’t just a collection of pretty charts, it’s a command center for your mobile app. It gives you a single, clear view of the most important metrics that determine your app's success.

A well-built dashboard helps you:

  • Track Key Performance Indicators (KPIs) at a glance: Instantly see your daily active users, download trends, and revenue without digging through multiple platforms.

  • Understand User Behavior: Identify which features are popular, where users are dropping off, and how a new update impacts engagement.

  • Spot Trends and Anomalies: Quickly notice if a crash rate is spiking after a release or if a marketing campaign is driving a surge in installs.

  • Make Data-Driven Decisions: Stop guessing and start making strategic choices based on what the data is actually telling you.

Step 1: Gather Your App's Key Data

You can't build a dashboard without data. Most app developers and marketers find themselves juggling information from several different sources. The most common starting points include:

  • App Store Connect: Apple’s hub for tracking iOS app performance. You can export data on impressions, downloads, sales, subscriptions, and crash reports.

  • Google Play Console: The Android equivalent, providing data on installs, uninstalls, ratings, revenue, and technical performance issues.

  • Mobile Analytics Platforms: Tools like Google Analytics 4, Mixpanel, Amplitude, or Firebase offer deep insights into user behavior. This is where you’ll find metrics like active users, session duration, screen flows, and event completions.

  • Advertising Platforms: If you're running ads on platforms like Meta Ads (Facebook/Instagram) or Google Ads, you'll need to export performance data to track your return on investment.

For this process, you'll typically be exporting this data as CSV files. A good routine is to create a dedicated folder where you save these weekly or daily reports, making sure to use a consistent naming convention (e.g., app-store-downloads-2024-10-21.csv).

Step 2: Identify and Prioritize Your KPIs

Trying to track everything at once is a recipe for a cluttered, useless dashboard. Start by focusing on the metrics that matter most to your app's goals. While every app is different, most dashboards focus on a few key areas.

Essential Mobile App KPIs to Track:

  • User Acquisition Metrics:

    • Downloads/Installs: The total number of new installs.

    • Cost Per Install (CPI): How much you’re spending to acquire each new user.

  • Engagement Metrics:

    • Daily Active Users (DAU) & Monthly Active Users (MAU): The number of unique users who open your app in a given day or month.

    • Session Length: The average time a user spends in your app per session.

    • Retention Rate: The percentage of users who return to your app over time (e.g., on Day 1, Day 7, Day 30). This is a critical indicator of value and stickiness.

  • Performance Metrics:

    • Crash Rate: The frequency of app crashes per unique user. High rates can lead to bad reviews and uninstalls.

    • Load Time: How quickly your app launches and becomes interactive.

  • Monetization Metrics:

    • Average Revenue Per User (ARPU): The average amount of revenue you generate from each user.

    • Lifetime Value (LTV): A prediction of the total revenue a user will generate throughout their time using your app.

    • Conversion Rate: The percentage of users who complete a desired action (e.g., make a purchase, subscribe, complete a tutorial).

Step 3: Building Your Dashboard in Excel (The Traditional Way)

Once you have your data and KPIs, it's time to build the dashboard. The traditional process in Excel is manual but powerful. We’ll use the example of visualizing daily active users (DAU) to walk through the steps.

1. Import and Clean Your Data

First, open a blank Excel workbook. Go to the Data tab, select From Text/CSV, and find the analytics report you exported.

Data cleaning is the most time-consuming step. You'll often need to:

  • Change date formats so Excel can recognize them.

  • Remove unnecessary columns.

  • Find and remove duplicate rows.

  • Ensure numbers are formatted as numbers, not text.

2. Organize with Tables and PivotTables

After your data is clean, select it all and press Ctrl+T (or Cmd+T on Mac) to turn it into an official Excel Table. This makes it easier to manage and reference in formulas.

Next, use a PivotTable to summarize the data. Select your table, go to the Insert tab, and click PivotTable. Drag the 'Date' field into the Rows area and your 'Active Users' field into the Values area. Instantly, you have a chronological summary of your DAU.

3. Create Visualizations

A list of numbers isn't a dashboard. You need charts. Select your PivotTable, go to the PivotTable Analyze tab, and click PivotChart. A line chart is perfect for showing a trend over time, like DAU.

Create separate charts and PivotTables for each KPI you want to track. You might use a bar chart for downloads by country or a pie chart for revenue by purchase type.

4. Assemble the Dashboard Sheet

Create a new sheet in Excel and name it "Dashboard." This is where you’ll put everything together. Copy and paste your charts onto this sheet. To display headline KPIs like yesterday's total DAU, you can use a formula like GETPIVOTDATA to pull a specific value from a PivotTable and display it in a large, easy-to-read font.

After arranging your charts and metrics, you can use Excel Cell Slicers and Timelines to add interactive filters, allowing you to easily view data for specific date ranges, user segments, or app versions.

This process works, but it's slow. Every time you want to update it, you have to repeat the CSV export, cleaning, and sometimes even the chart creation process. This is where AI changes the game.

Step 4: Supercharge Your Dashboard with Excel AI

AI tools, both within Excel and as external assistants, are designed to eliminate the most tedious parts of data analysis. Instead of manually performing tasks, you can use natural language to describe what you need.

Automating Data Cleaning with AI

Excel's built-in Ideas (or Analyze Data on the Home tab) can automatically detect patterns and cleaning opportunities in your dataset. But even more powerful is using an AI assistant to handle complex cleaning without formulas.

For example, instead of writing nested formulas to extract a user's country from a messy string of text, you can ask an AI tool: “Create a new column called 'Country' and extract the country name from the 'Location' column.” It can handle irregularities that would normally require complex REGEX formulas.

Generating Formulas with Plain English

Stuck trying to remember the syntax for VLOOKUP or INDEX/MATCH? AI can write the formulas for you. For your mobile app dashboard, you could ask:

"Write an Excel formula to calculate the week-over-week growth percentage for downloads located in cells B2:B8 (this week) and C2:C8 (last week)."

The AI will give you the exact formula to copy and paste, saving you from trial, error, and hunting through forums.

Getting Chart Recommendations and Insights

Sometimes the hardest part is knowing how to visualize your data. With AI, you can simply ask. Highlight your data table and ask: "Show me installs by device type as a donut chart" or "Suggest the best way to visualize user retention over 30 days."

Many AI tools go a step further and find insights automatically. After analyzing your data, an AI might tell you: "You saw a significant increase in user sessions from Germany last Wednesday, correlating with the start of your marketing campaign." This moves you from a reactive analysis (building a report) to a proactive discovery (being told what's important).

Example: Building a Retention Cohort Chart with AI Assistance

A cohort retention chart is one of the most valuable - and most difficult to create - visualizations for an app. It shows what percentage of users acquired on a given day return on subsequent days.

The Traditional Way: This requires multiple PivotTables, layers of calculations, complex formulas to look up values, and meticulous conditional formatting to create the signature heatmap look.

The AI-Assisted Way: Drop your user activity CSV into an AI-powered analysis tool and simply ask:

“Using the user sign-up date and last-seen date, create a cohort retention analysis table showing the percentage of users who return on Day 1, Day 7, Day 14, and Day 30. Then, create a heatmap from this table.”

The AI can generate the structured pivot table or even the final formatted chart, condensing a multi-hour task into a few minutes.

Final Thoughts

Excel is a surprisingly powerful tool for building a mobile app dashboard, giving you complete flexibility to analyze your metrics. The manual process of exporting, cleaning, and visualizing data can be demanding, but leveraging AI assistants helps automate the most painful parts. By using plain-language prompts, you can generate formulas, charts, and even surface key insights without being an Excel wizard.

While AI makes building dashboards in Excel far easier, the foundation still relies on manual data exports and updates. For those who want to skip the spreadsheet wrangling entirely, this is where we built Graphed to help. We connect directly to your data sources like App Store Connect, Google Analytics, Shopify, and more, so your dashboards are always live and update automatically. You can build comprehensive, shareable reports simply by describing what you want to see, letting you get instant answers and stay focused on growing your app.