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How to Create a Sales Dashboard in Looker with AI

Cody Schneider•

Creating a sales dashboard is one of the most effective ways to get a real-time pulse on your business, but the process has historically been clunky and slow. This guide shows you how to build a powerful sales dashboard in Looker (now part of Google Cloud) step-by-step, and how new AI capabilities are making it faster and more intuitive to turn your sales data into actionable insights.

Why Build a Sales Dashboard in Looker?

Before diving into the “how,” it’s worth understanding the “why.” Your sales data from platforms like Salesforce, HubSpot, or a custom CRM is a goldmine. Manually exporting CSVs every week to paste into a spreadsheet is not only tedious but also means your decisions are always based on outdated information. A dedicated Looker dashboard offers a far better way to work.

  • A Single Source of Truth: Everyone on your sales team, from reps to leadership, looks at the same, consistent data.

  • Real-Time Performance Tracking: Dashboards connect to live data, so you always know how you’re pacing against quota and other KPIs.

  • Visual Insight: It’s easier to spot trends, opportunities, and outliers in a bar chart or a funnel than in a wall of numbers in a spreadsheet.

  • Team Accountability and Motivation: When performance is visible, it fosters a culture of accountability and healthy competition. Reps know exactly where they stand at all times.

Getting Your Data Ready for Looker

Looker doesn't store your data, it queries it wherever it lives. This means the first, and most important, step is to get your data into a database or data warehouse that Looker can connect to. Standard choices include Google BigQuery, Snowflake, Amazon Redshift, and PostgreSQL.

Typically, this involves a process called ETL (Extract, Transform, Load):

  • Extract: Pulling data from its source (e.g., Salesforce API).

  • Transform: Cleaning, structuring, and formatting the data so it's consistent.

  • Load: Placing the cleaned data into your data warehouse.

You can use ETL tools like Fivetran or Stitch to automate this process. Without clean, centralized data, your dashboard won’t be accurate or reliable.

Understanding Looker's Core Building Blocks

Looker has a few key concepts you'll need to grasp. While powerful, this foundation is what creates its infamous learning curve.

What is LookML?

LookML (Looker Modeling Language) is the heart of Looker. It's code that describes the dimensions, aggregates, calculations, and data relationships in your database. A developer or data analyst on your team will write a LookML project that acts as the semantic layer - a translation layer - between your complex database and your business users.

  • Dimensions: These are the fields you use to group or filter your data, like "Sales Rep Name," "Region," "Deal Stage," or "Date."

  • Measures: These are the numerical values you want to aggregate, like a count, sum, or average. Examples include "Total Sales Revenue," "Number of Won Deals," or "Average Deal Size."

Once the LookML model is built, anyone on your team can self-serve reports without ever having to write SQL.

Explores, Looks, and Dashboards

On top of the LookML model, you build the things users actually see:

  • Explores: These are the predefined starting points for your analysis. An analyst might create a "Deals Explore" that brings together all the relevant fields about your sales deals. A user can select that Explore to start building a report.

  • Looks: A "Look" is a single saved report — a saved table or a single visualization, like a single bar chart.

  • Dashboards: A "Dashboard" is a collection of Looks (or “Tiles”) organized onto one page to give you a comprehensive overview of a particular topic, like your sales performance.

How to Build Your Sales Dashboard in Looker, Step-by-Step

Assuming your data is connected and a basic LookML model exists, you’re ready to build your dashboard. Here’s a practical guide using common sales metrics.

Step 1: Define Your Key Sales KPIs

First, decide what you need to track. Don't try to visualize everything at once. Start with a few critical metrics that drive your business. Good starters for a sales dashboard include:

  • Sales Revenue: Total revenue generated, often tracked against a target.

  • Quota Attainment: What percentage of the sales goal has been met by a rep or the team?

  • Average Deal Size: The average revenue from a won deal.

  • Sales Cycle Length: How long it takes on average to close a deal from first contact.

  • Deal Velocity: How quickly deals are moving through the pipeline.

  • Win Rate: The percentage of total opportunities that are won.

  • Sales Funnel / Pipeline: A view of all open opportunities broken down by stage.

Step 2: Create a New Dashboard

From your Looker homepage or the folder where you want to save your work, create a new dashboard. Give it a clear name like "Q3 Sales Performance" or "Sales Team Dashboard."

Step 3: Add Your First Tile (Visualization)

Dashboards are empty canvases. You build them by adding “Tiles” one by one. To create your first Tile, you’ll start from an Explore.

Let's build a chart showing Revenue by Sales Rep:

  1. Click "Add" or "Edit dashboard" and choose to create a new tile.

  2. Select a relevant “Explore,” such as “SFDC Opportunities” or “Deals.”

  3. In the Explore interface, you’ll see your fields on the left:

    • Under Dimensions, find and click "Sales Rep Name."

    • Under Measures, find and click "Total Revenue."

  4. Click "Run" at the top right. This will generate a data table with reps and their revenue totals.

  5. To turn this into a chart, click the "Visualization" tab. Choose a "Bar" chart.

  6. Customize the tile with a clear title like "Revenue by Sales Rep (This Quarter)."

  7. Click "Save" to add the tile to your dashboard.

Repeat this process for other visualizations, such as a line chart showing revenue over time or a pie chart illustrating deal sources.

Step 4: Use Single Value Tiles for KPIs

For top-level numbers like "Total Revenue This Quarter," a simple number is often more effective than a full chart. Use the "Single Value" visualization type in the visualization options to create big, bold KPI call-outs at the top of your dashboard.

Step 5: Build a Sales Funnel

Sales funnels are incredibly valuable and easy to create if your data is structured correctly. In your deal data, you likely have a dimension called "Deal Stage."

  1. Create a new tile using your Deals Explore.

  2. Select the "Deal Stage" dimension and a count of your deals (e.g., a "Deal Count" measure).

  3. Run your query.

  4. In the visualization options, select a "Funnel" chart type. Looker will represent the stages visually, showing you where prospects drop off.

Step 6: Add Interactive Filters

A static dashboard isn't very helpful. The real power comes from interactivity. In the Looker dashboard editor, add filters for common dimensions like:

  • Date Range: Let users choose "This Quarter," "Last 30 Days," or a custom range.

  • Sales Rep: Allow managers to filter the entire dashboard to view a single rep's performance.

  • Region or Territory: Give a high-level view that can be drilled down into specifics.

Once you’ve linked these filters to the corresponding fields in your tiles, a user can change the date filter at the top of the dashboard, and all the charts and KPIs will update instantly.

Supercharging Your Looker Dashboard with AI

Building dashboards manually is powerful but can be slow. This is where AI assistants, like Gemini in Looker, radically change the workflow.

Instead of manually clicking through Explores, selecting dimensions and measures, and configuring charts, you can now use natural language to tell Looker what you want.

From Clicks to Conversation

Inside Looker, you can open an AI assistant and simply type your request in plain English. For example:

  • "Show me total sales revenue by region this quarter as a bar chart"

  • "Compare the average deal size for Sarah and David over the last 6 months"

  • "What are my top 10 open deals by value?"

The AI will interpret your request, query the underlying LookML model, and generate the visualization for you. From there, you can refine it or add it directly to your dashboard. This dramatically speeds up the process of building reports and empowers non-technical users to explore data themselves without needing to navigate complex menus.

Finding the "Why" with AI

Beyond chart creation, AI can help you find answers faster. If you see a sudden dip in your sales for the week, instead of an analyst spending hours digging through data to find the cause, you can simply ask the dashboard:

“Why did our sales revenue drop last week?”

Looker’s AI can analyze the underlying data to identify contributing factors, such as a key account pushing a deal to next quarter or a drop in a specific region’s performance. It automates the deep-dive analysis that used to be a completely manual task.

Final Thoughts

Building a sales dashboard in Looker is an investment that pays off by creating a truly data-driven sales culture. By centralizing your CRM data and defining your key metrics, you can move from reactive reporting in spreadsheets to proactive decision-making based on live, visual insights that the whole team can use.

While Looker is a fantastic tool for data experts, the AI-powered features highlight a major shift in business intelligence: moving away from complex BI interfaces toward natural language. At Graphed, we’ve built our entire platform around this idea. Instead of navigating the learning curve of LookML, you can securely connect data sources like Salesforce and Google Analytics in minutes, then simply talk directly with your data. You can ask Graphed something like, “Create a sales dashboard showing our pipeline, win rate by rep, and total revenue this quarter,” and the AI builds it for you in seconds. It’s the instant, real-time reporting you need without the technical overhead.