How to Create an Insurance Dashboard in Looker

Creating an insurance dashboard in Looker turns your complex policy, claims, and underwriting data into a clear resource for making smarter decisions. Instead of digging through spreadsheets or static reports, you can build a live, interactive dashboard that highlights everything from agent performance to claim trends in real-time. This guide will walk you through the process of planning, building, and refining a powerful insurance dashboard in Looker.

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Why Build an Insurance Dashboard in Looker?

In the insurance industry, you're sitting on a mountain of data from different systems: policy administration, claims processing, your CRM, and underwriting software. A well-designed Looker dashboard acts as a single source of truth, centralizing key metrics to give you an immediate and accurate view of business health. This helps you move from reactive problem-solving based on last month's reports to proactive strategy based on what's happening right now.

A unified dashboard allows you to:

• Monitor Portfolio Health: Track your Gross Written Premium (GWP), renewal rates, and policy counts in one place.
• Analyze Claims Performance: Instantly see your loss ratio, average claims cost, and claim processing times to identify bottlenecks or rising risks.
• Evaluate Agent and Channel Performance: Compare quote-to-bind ratios and new business generated by individual agents or distribution channels.
• Identify Trends: Spot increases in claim frequency in certain regions or for specific policy types before they become major issues.

Before You Build: Planning Your Dashboard

Jumping straight into building without a clear plan is a quick way to create a dashboard that nobody uses. A few strategic planning steps will ensure your final product is focused, relevant, and genuinely useful.

1. Identify Your Audience and Their Goals

First, ask yourself: Who is this dashboard for? The metrics a C-level executive needs are vastly different from what a claims manager or a sales leader requires. Defining your audience helps you focus on the most relevant information.

• For Executives: They need a high-level overview. Focus on KPIs like Gross Written Premiums (GWP), Combined Ratio (the ultimate measure of profitability), year-over-year growth, and customer lifetime value (CLV). They care about the overall health and strategic direction of the business.
• For Claims Managers: This audience needs operational metrics. Focus on Claims Frequency, Average Claim Cost (Severity), Claims Processing Time, and potentially fraud indicators. Their goal is to manage claim costs and improve operational efficiency.
• For Sales & Underwriting Managers: Their focus is on growth and risk management. Key metrics include New Policies Written, Quote-to-Bind Ratio, Average Premium, and Policy Renewal Rate by agent and product line. They want to know what's selling, who is selling it, and if it's profitable.

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2. Select Your Key Performance Indicators (KPIs)

Once you know your audience, you can choose the right KPIs. Think of your dashboard as a story, your KPIs are the key plot points. Here are some essential metrics for a comprehensive insurance dashboard:

Sales & Growth Metrics

• Gross Written Premium (GWP): The total revenue from premiums before deducting reinsurance costs and commissions. This is your primary top-line growth metric.
• New Policies Written: The total number of new policies bound within a specific period.
• Policy Renewal Rate: The percentage of policies that are renewed by customers at the end of their term. A key indicator of customer retention.
• Quote-to-Bind Ratio: The percentage of quotes that result in a bound policy. This measures the effectiveness of your sales process and pricing.

Claims & Profitability Metrics

• Loss Ratio: (Incurred Losses + Adjustment Expenses) / Earned Premiums. This fundamental KPI measures the proportion of premium revenue that is paid out in claims.
• Combined Ratio: Loss Ratio + Expense Ratio. The definitive measure of underwriting profitability. A combined ratio below 100% indicates a profit, above 100% indicates a loss.
• Claims Frequency: The number of claims filed per number of policies in-force. Helps you spot trends in how often claims are occurring.
• Claims Severity: The average cost per claim. Helps you understand the financial impact of each claim.

3. Map Your Data Sources

Where does this all live? Your data is likely spread across multiple systems. Looker works by querying your existing data warehouse, so the first step is to ensure your sources are centralized and accessible. Common data sources include:

• Policy Administration System (PAS): The core system for policy information, premiums, and renewals.
• Claims Management System: The source for all claims data, from initial filing to settlement.
• CRM Software (e.g., Salesforce): Contains agent activity, customer interactions, and sales pipeline data.
• Billing Systems: For premium payment and financial data.

This data typically needs to be consolidated into a data warehouse like BigQuery, Snowflake, or Amazon Redshift before you can effectively model it in Looker.

Building Your Insurance Dashboard in Looker: A Step-by-Step Guide

With a solid plan in place, you’re ready to start building. Looker's power comes from its unique modeling layer, LookML, which allows you to define your business logic once and reuse it everywhere.

Step 1: Get Your Data into Looker

Looker isn't a data storage tool, it's a querying and modeling platform. The first step is to connect Looker to the database or data warehouse where your insurance data is located. Once connected, your Looker developer can start a new project to begin defining the data model that your business teams can work with.

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Step 2: Define Your Business Logic with LookML

This is Looker’s secret sauce. Before you build charts, a Looker developer uses LookML (Looker Modeling Language) to define all your metrics, calculations, and data relationships. This ensures that every person in your organization is using the exact same definition for every metric. Instead of ten different versions of "Loss Ratio" floating around in various spreadsheets, you have one governed definition.

For example, to define Average Claim Cost, your developer might write LookML like this:

measure: total_claim_amount {
  type: sum
  sql: ${TABLE}.claim_amount ,,
  value_format_name: usd
}

measure: total_claims {
  type: count_distinct
  sql: ${TABLE}.claim_id ,,
}

measure: average_claim_cost {
  type: number
  sql: ${total_claim_amount} / ${total_claims} ,,
  value_format_name: usd
}

Creating this code-based model is the most technical part of the process, but once it's done, business users can explore the data and build reports without writing a single line of code.

Step 3: Create Individual Visualizations ("Looks")

In Looker, a single chart or data table is called a "Look." Using the "Explore" interface, you can select the fields and measures (defined in LookML) you want to analyze from a user-friendly dropdown menu, and Looker writes the SQL for you. This is where your KPI planning pays off.

Here are a few visualizations you could build:

• KPI Tiles (Single Value): For top-level metrics like GWP, Combined Ratio, and Active Policies. These give you a powerful at-a-glance view.
• Line Charts: Ideal for tracking trends over time. Use one to visualize GWP by Month or Claims Severity over the past 24 months.
• Bar Charts: A great choice for comparisons. Create a bar chart showing New Policies Written by Agent or Loss Ratio by Policy Type.
• Maps: Visualize geographic trends. Plot Claim Frequency by State or create a heatmap of Policy Concentration by Zip Code to understand risk exposure.
• Tables: For more granular detail. A table with the Top 10 Most Expensive Claims or Policies Up for Renewal Next Month can be very actionable.

Step 4: Assemble Your Looks into a Dashboard

A dashboard is simply a collection of these Looks. Create a new dashboard and begin adding the visualizations you built. Organize them logically based on the story you want to tell.

A good practice is to place your most critical, high-level KPIs (like GWP and the Combined Ratio) in large tiles at the very top. From there, you can flow down into more specific breakdowns by product, region, or time period.

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Step 5: Make It Interactive with Filters

A static dashboard has limited value. The real power of a Looker dashboard comes from its interactivity. Add dashboard-level filters at the top so users can slice and dice the data themselves.

Common filters for an insurance dashboard include:

• Date Range: Allow users to view data by month, quarter, year, or a custom range.
• Policy Type: Filter the entire dashboard to see metrics for Auto, Home, or Commercial lines.
• State or Region: Drill down into geographic performance.
• Agent or Agency: Let sales managers filter to see data for their specific team.

When a user selects a filter, all the reports on the dashboard will update automatically, empowering them to answer their own follow-up questions without needing to ask the data team for a new report.

Final Thoughts

Building an insurance dashboard in Looker organizes your critical business data into a single, interactive hub. By carefully planning your audience and KPIs, defining business logic centrally, and building insightful visualizations, you create a powerful tool that helps everyone from executives to claims managers make data-informed decisions with confidence.

If you don't have a technical team or the time required to learn a complex tool like Looker, achieving this level of clarity in your data analysis can feel out of reach. For this, we built Graphed. We connect to your data sources like Salesforce, HubSpot, financial platforms, and ad networks in seconds. Instead of a developer writing code, you can just ask questions in plain English - like "create a sales dashboard showing deal velocity by rep this quarter" - and Graphed builds a live, interactive dashboard for you instantly.