How to Create an Insurance Dashboard in Google Sheets with AI

Building an insurance dashboard can feel complicated, but it doesn't have to involve expensive software or a data science degree. With Google Sheets and a little help from AI, you can create a powerful, real-time command center for your agency. This article will walk you through exactly how to track your key metrics, from policy renewals to agent performance, all within a familiar spreadsheet.

Why Use Google Sheets for an Insurance Dashboard?

While specialized business intelligence tools are powerful, they often come with steep learning curves and high costs. For many insurance agencies, agents, and brokers, Google Sheets is the perfect solution. It's accessible, collaborative, and entirely free.

A well-built dashboard gives you an at-a-glance view of your business's health, allowing you to quickly answer questions like:

• What is our policy renewal rate this quarter?

• Which agent is leading in premium sales?

• What's the current status of outstanding claims?

• Which marketing channels are bringing in the most valuable leads?

The goal is to move from reactive data-pulling to proactive decision-making. Instead of digging through different systems to find information, you have one central place to see what's working and where you need to focus your attention.

Gathering Your Key Insurance Data

An effective dashboard relies on good data. Before you start building, you need to identify where your most important information lives. For most insurance professionals, this data is spread across several platforms:

• Your CRM (like Salesforce or HubSpot): This holds all your client information, lead statuses, policyholder details, and interaction histories.

• Carrier Portals: This is where you find specific policy details, commission statements, and underwriting updates.

• Claims Management Software: This system tracks every claim's lifecycle, from initial filing to final payout, including status, timeline, and associated costs.

• Email & Marketing Platforms (like Mailchimp or Klaviyo): These platforms provide data on lead sources, campaign performance, and client engagement.

The biggest challenge is bringing this scattered data together. The traditional method involves manually downloading CSV files from each platform every week and pasting them into a spreadsheet - a tedious process that's prone to error. A better approach is to automate it. You can use tools like Zapier or Make.com to create workflows that automatically send new data from your applications directly into a designated Google Sheet, creating a "single source of truth."

Structuring Your Google Sheet for Success

Organization is the foundation of a great dashboard. A messy spreadsheet will only lead to confusion. The best practice is to structure your Google Sheet with separate tabs for different functions:

1. Raw Data Tab

This is where all your raw, untouched data goes. It acts as the database for your entire dashboard. Each new piece of data from your systems (whether pasted manually or piped in through automation) should be added as a new row. Keeping this data clean and separate from your analysis is critical.

Your "Raw Data" tab might have columns like:

2. Calculations Tab

Never build your charts directly from the Raw Data tab. Instead, create a second tab named "Calculations" or "Summary." This is where you'll create summary tables that organize and aggregate your data into formats that are easy to visualize. You can use Pivot Tables or formulas like SUMIFS and COUNTIFS to build these summaries.

For example, a summary table for agent performance might look like this:

This is where AI starts to make life much easier. Instead of wrestling with complex formulas, you can use AI-powered Google Sheets add-ons to generate these summaries for you using plain English prompts.

3. Dashboard Tab

This is the fun part. Your "Dashboard" tab is the clean, visual front-end where all your charts and key performance indicators (KPIs) will be displayed. This tab will pull data exclusively from your "Calculations" tab, ensuring it stays neat and updates automatically as your summary tables change.

Step-by-Step: Building Your Insurance Dashboard with AI Assistance

With your data organized, you're ready to start building the visualizations. Here’s a walkthrough of creating common dashboard elements, highlighting how AI can speed up the process.

Step 1: Create Your Main KPIs (Scorecards)

Scorecards are large, prominent numbers that display your most important top-level metrics. Start with a few essentials:

• Total Premiums Sold This Month/Quarter

• Policy Renewal Rate (%)

• Total Active Policies

• Average Claim Processing Time (Days)

To create a "Total Premiums Sold" scorecard, go to your "Calculations" tab and pick a cell. You can use an AI formula generator by prompting it: "sum the 'Premium_Amount' column in the 'Raw Data' tab if the 'Sale_Date' is in the current month."

The AI will likely generate a formula like this:

Once you have this number in your "Calculations" tab, go to your "Dashboard" tab, select a cell, type =, and reference the cell with the total. Then, format it with a large, bold font to make it stand out.

Step 2: Visualize Core Metrics with Charts

Now, let’s build some charts to provide more context. All charts should be created from the summary tables in your "Calculations" tab.

Chart 1: Policy Mix by Type (Pie Chart)

1. On your "Calculations" tab, create a small table summarizing policies sold by type. Prompt your AI add-on: "create a table showing the count of each 'Policy_Type' from the 'Raw Data' tab."

2. This will produce a table like:

1. Highlight this table, then go to Insert > Chart. Google Sheets will automatically suggest a pie chart.

2. Customize the colors and title, then copy and paste the chart into your "Dashboard" tab.

Chart 2: Claim Status (Donut Chart)

Follow the same process as above, but this time, prompt the AI to create a summary table for Claim_Status. A donut chart is a great way to visualize the breakdown of claims that are pending, approved, or denied, helping you spot bottlenecks in your process.

Chart 3: Agent Performance Leaderboard (Bar Chart)

Use your AI tool to generate a table that summarizes the total premium sold by each agent. Then, select that data and insert a bar chart to create an instant leaderboard. This encourages healthy competition and transparently showcases top performers.

Step 3: Make Your Dashboard Interactive

A static dashboard is good, but an interactive one is even better. Clicks, not code, are all you need to allow users to filter the data.

How to Add a Slicer:

1. In your "Dashboard" tab, go to Data > Slicer.

2. A slicer chip will appear. In the settings sidebar that opens, select your "Raw Data" tab as the data range.

3. For the "Column," choose a category you want to filter by, such as Agent_Name.

4. Move and resize the slicer on your dashboard. Now, anyone viewing the dashboard can choose a specific agent from the dropdown, and all your charts and KPIs (if they're set up correctly with Pivot Tables) will instantly update to show data only for that agent.

Adding slicers for Policy_Type, Lead_Source, or a date range can turn your dashboard into a powerful self-service analytics tool for your entire team.

Final Thoughts

Creating a detailed insurance dashboard doesn't require a massive budget or extensive technical skills. By organizing your data correctly in Google Sheets and leveraging the power of AI add-ons to handle formulas and summaries, you can build a dynamic, shareable dashboard that surfaces critical insights and helps you run your business more effectively.

While using Google Sheets is a massive step up from manual reporting, we built Graphed to take this process to the next level. Instead of piping data into a spreadsheet, you can connect your systems like Salesforce, HubSpot, or Google Ads directly to our platform. From there, you just ask questions in plain English, like "Show me a dashboard of policy sales by agent for the last quarter," and we instantly build a live, interactive dashboard for you. It automates the entire reporting workflow, from data connection to visualization, letting you focus on making decisions, not building reports.