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How to Create a CRM Dashboard in Looker

Cody Schneider••8 min read

Building a CRM dashboard is one of the best ways to get a clear, real-time snapshot of your entire sales operation, from lead generation to closed deals. While most CRMs have built-in reporting, piping that data into a powerful BI tool like Looker (now part of Google Cloud) opens up a new level of customization and cross-platform analysis. This guide will walk you through how to connect your CRM to Looker and build a robust dashboard to track your most important sales metrics.

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What Exactly is a CRM Dashboard (and Why Use Looker)?

A CRM dashboard is a visual control center that centralizes your sales KPIs into a single, easy-to-understand view. Instead of digging through different reports within Salesforce, HubSpot, or whichever CRM you use, you get a high-level overview of performance in one place. Common metrics include:

  • Sales pipeline health (deals per stage)
  • Lead volume and source effectiveness
  • Deal conversion rates
  • Sales cycle length
  • Individual and team performance against quotas
  • Revenue forecasts

While native CRM analytics are useful for quick checks, building your dashboard in Looker offers a few key advantages. You can blend CRM data with information from other sources - like marketing analytics from Google Analytics or ad platforms, and financial data from Stripe - to get a full-funnel view of your business. Looker also provides deeper customization, reusable data models, and more advanced visualization capabilities than what’s typically available inside a CRM.

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Before You Begin: Planning Your Dashboard

Jumping straight into building without a plan is a recipe for a confusing dashboard that no one uses. Before you connect any data, take a few minutes to define what you want to achieve. Ask yourself and your team:

  1. Who is this dashboard for? A dashboard for front-line sales reps will look very different from one designed for the VP of Sales or the CEO. Reps might need to see their personal pipeline and activity metrics, while executives will want high-level revenue trends and forecasts.
  2. What questions should it answer? Get specific. Good questions lead to good dashboards. For example: "Which of our marketing campaigns are bringing in the highest-value leads?" or "How is our sales team in the EMEA region performing compared to the NA team this quarter?"
  3. What are our most important KPIs? Based on your questions, list the metrics that matter most. Start with the essentials: revenue, pipeline value, conversion rate, and lead source. You can always add more detail later.

You’ll also need to make sure you have the right permissions. To follow this guide, you'll need developer-level access in Looker to create new connections and model data, as well as credentials to access your CRM's underlying database or data warehouse.

Step 1: Connecting your CRM Data to Looker

The first step is getting your sales data flowing into Looker. The exact method depends on your CRM and your data infrastructure. Some companies might use a data pipeline tool like Fivetran or Stitch to pull CRM data into a data warehouse (like BigQuery, Snowflake, or Redshift). Others might connect directly to a replica database.

For this walkthrough, we'll assume your data is in a warehouse, which is a common and robust setup. The steps are generalized but apply to most database connections.

  1. Navigate to the Admin panel in Looker.
  2. Under the Database section, click on Connections.
  3. Click the Add Connection button.
  4. Configure the connection settings:
  5. Once you've filled everything out, click Test These Settings to ensure Looker can successfully connect. If it’s successful, click Add Connection.

Your data source is now available for Looker to query. The next (and most critical) part is telling Looker how to interpret it.

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Step 2: Building the Foundation with LookML

This is where Looker’s real power comes into play. Unlike drag-and-drop tools, Looker uses a modeling layer called LookML. Think of LookML as a "recipe book" for your data. You define your metrics, table relationships, and business logic once in a LookML model, and everyone in the company can then explore that curated data without writing SQL themselves. This ensures consistency and makes self-service analytics possible.

To start, you’ll need to create a LookML project for your new CRM connection.

  1. First, make sure you are in Development Mode (toggle this on from your personal settings).
  2. Navigate to the Develop section and click on Manage LookML Projects.
  3. Click New LookML Project.
  4. Give your project a name (e.g., "crm_analytics"), choose a starting point (like "Blank Project" or "Generate Model from Database Schema"), and select the database connection you created in the previous step. Creating a model from the schema is a great way to start, as Looker will automatically create a base set of files for the tables it finds.

This generates several files. The most important ones are:

  • Model files (.model): Here you define which tables ("views") belong together in an "Explore." An Explore is the starting point for a user to query data.
  • View files (.view): Each view file corresponds to a table in your database (e.g., deals, contacts, companies). In these files, you define your dimensions and measures.

A simple dimension for a deals table might look like this:

dimension: deal_stage {
  type: string
  sql: ${TABLE}.deal_stage ,,
}

And a measure to calculate the total value of all deals would be:

measure: total_deal_value {
  type: sum
  sql: ${TABLE}.deal_amount ,,
  value_format_name: usd
}

You'll build out these views for all your core CRM objects - opportunities, accounts, leads, users/reps, etc. The initial investment in defining your business logic in LookML pays off immensely by making your data reliable and easy for anyone to use.

Step 3: Creating Your Key Visualizations

With your LookML model defined, you can now start building the actual dashboard in Looker. The process involves creating individual visualizations - called "Looks" or "Tiles" - from your Explores and then arranging them on a dashboard.

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Example Visualizations for a CRM Dashboard

Let's create a few of the most valuable charts every sales team needs.

1. Sales Pipeline Funnel

This chart gives an at-a-glance view of how many deals are in each stage of your sales process.

  • From your CRM Explore, select the dimension for Deal Stage and the measure for Deal Count.
  • Order the stages to match your sales process.
  • Under Visualization, choose "Funnel."
  • Save this visualization as a Look and add it to your dashboard.

2. Revenue vs. Quota Over Time

Stakeholders want to see progress against goals. A combination chart is perfect for this.

  • Select your time dimension (e.g., Close Date Month) and your 'won' revenue measure (e.g., Total Won Value). You'll also need a measure for your quota (this might come from your CRM or even a separate Google Sheet).
  • Choose the Column visualization type.
  • In the visualization settings, you can plot your quota as a line, giving you a clear bar-vs-line comparison.

3. Lead Source Performance

Understand which channels are driving the most value.

  • Select the Lead Source dimension and the Total Won Value measure.
  • Choose a Bar chart visualization to easily compare the sources.
  • Bonus: You could also add a measure for Lead to Deal Conversion Rate to see which sources produce leads that are most likely to close.

4. Sales Rep Leaderboard

Encourage friendly competition and track individual performance.

  • Select the Sales Rep Name dimension and any key performance measure, like Deals Won Count or Total Won Value.
  • A simple Table visualization works great here. You can sort it by your chosen metric to create the leaderboard.

Step 4: Putting It All Together and Final Touches

Once you've created your key visuals as Looks, you can combine them into a single dashboard.

  1. Navigate to the folder where you saved your Looks and click New > Dashboard from the top right.
  2. Give your dashboard a name and start adding your saved Looks or create new tiles from scratch.
  3. Arrange the tiles logically. Put the most important "headline" metrics - like total revenue and pipeline value - at the top.

To make your dashboard truly interactive and useful, be sure to:

  • Add Dashboard Filters: Create dashboard-level filters for things like Date Range, Sales Rep, and Region. This allows users to slice and dice the data to answer their own specific questions without having to edit the individual tiles.
  • Schedule Deliveries: Set up automated email schedules to send a PDF or a link to your dashboard to stakeholders every Monday morning or at the start of each month.
  • Set Up Alerts: Set thresholds so you’re notified when a KPI hits a critical value, such as if your pipeline value drops below a certain point or exceeds the quota.

Final Thoughts

Building a meaningful and informative CRM dashboard in Looker enables you to move away from transforming data manually and move towards intelligent visualizations that answer key business questions. By centralizing your data into a real-time view, you empower your team to make data-driven decisions.

The whole process may seem technical, especially with LookML, but the effort you invest will be accessible for your team without needing advanced SQL skills. Tools like Graphed can further simplify this process, allowing you to focus on insights rather than technical complexities. With Looker, you're not just creating dashboards - you're setting the stage for your team to become data explorers and analysts.

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