How to Create a Revenue Dashboard in Looker

Building a revenue dashboard in Looker gives you a powerful, centralized view of your company's financial health, helping you spot trends and make smarter decisions. This guide will walk you through the essential steps, from planning your metrics to assembling and customizing your final dashboard.

First, Why Build a Revenue Dashboard?

A revenue dashboard isn’t just a collection of charts, it’s a living document that tells you the story of your business's performance. It centralizes your most critical financial metrics so you can stop jumping between platforms like Stripe, Salesforce, and your spreadsheet reports. With a well-built dashboard, you can answer important questions at a glance:

• Are we hitting our monthly or quarterly revenue targets?

• Which products or services are driving the most revenue?

• How are our key metrics like Monthly Recurring Revenue (MRR) and Average Revenue Per User (ARPU) trending over time?

• Is customer churn affecting our bottom line?

Answering these questions quickly and accurately is the first step toward building a more data-driven strategy. Looker is a powerful business intelligence tool for this, but getting it right requires some careful planning.

Step 1: Plan Your Dashboard Before You Build

Jumping straight into Looker without a plan is a common mistake. Before you build a single chart, take a moment to outline what you actually need to see. This planning phase will save you hours of rebuilding and rearranging later on.

Define Your Key Revenue Metrics

Start by identifying the Key Performance Indicators (KPIs) that matter most to your business. This depends entirely on your business model (e-commerce, SaaS, agency, etc.). Here are some crucial metrics to consider:

• Total Revenue: The most basic top-line number. You'll want to see this over various time frames (daily, weekly, monthly).

• Monthly Recurring Revenue (MRR): Essential for any subscription-based business. You'll also want to track New MRR, Expansion MRR, and Churn MRR.

• Average Revenue Per User (ARPU): Helps you understand the value of an average customer.

• Customer Lifetime Value (CLV): Predicts the total revenue a business can expect from a single customer account.

• Revenue by Source/Channel: Shows you which marketing channels (e.g., Organic Search, Paid Ads, Social Media) are driving paying customers.

• Revenue by Product/Service: Pinpoints your most and least profitable offerings.

Identify Your Data Sources

Where does your revenue data actually live? Tally up every platform that holds a piece of the puzzle. Common sources include:

• Transactional data from payment processors like Stripe or PayPal.

• Sales data from your CRM like Salesforce or HubSpot.

• E-commerce orders from platforms like Shopify or WooCommerce.

• Financial data from accounting software like QuickBooks or Xero.

• A centralized SQL database or data warehouse (e.g., BigQuery, Snowflake, Redshift).

Looker will need to connect to these sources to pull the data. Knowing this upfront helps you work with your data team to ensure the right connections are in place.

Consider Your Audience

Finally, who is this dashboard for? Different teams need different levels of detail.

• For the CEO/Leadership: A high-level overview with top-line KPIs like Total Revenue, MRR, and overall growth trends.

• For the Sales Team: A more granular view showing revenue by sales rep, deal conversion rates, and pipeline value.

• For a Marketer: A dashboard connecting campaign spend to revenue, showing ROI by channel and cost per acquisition.

Tailoring the dashboard to its audience makes it infinitely more useful.

Step 2: Connect Your Data and Prepare Your Model in Looker

This is typically the most technical part of the process and often requires help from a data analyst or developer who understands Looker's modeling layer, LookML.

For your revenue dashboard to work, Looker needs to be connected to the database where your data lives. Once connected, a developer uses LookML to create a "model" of your data. Think of LookML as a translation layer - it tells Looker what your data means in plain business terms. For example, a developer would write LookML code to:

• Define Dimensions: These are the "attributes" you use to group or filter your data, like Order Date, Customer Name, or Product Category.

• Define Measures: These are the calculations you want to perform on your data, like Sum of Sales, Average Order Value, or a Count of Unique Customers.

Without this LookML model, you can't build anything in Looker. It’s what powers the user-friendly "Explore" interface where you will actually create your charts.

Step 3: Build Your Visualizations ("Looks")

Once the LookML model is ready, you can start building the individual charts and tables - called "Looks" or "Tiles" in Looker - for your dashboard. This is done inside an "Explore," which is a user-friendly environment for asking questions of your data.

Let's walk through building a simple tile: a line chart showing daily revenue for the last 30 days.

1. Navigate to an Explore: Your Looker admin will point you to the right Explore, which might be named something like "Orders" or "Revenue."

2. Select Dimensions and Measures: On the left-hand panel, you’ll see all the available dimensions and measures defined in your LookML model.

   • Find your date dimension (e.g., Order Date) and click it.

   • Find your revenue measure (e.g., Total Sale Price) and click it.

3. Run the Query: Click the Run button. Looker will now query your database and show you a raw data table with dates and corresponding revenue.

4. Apply Filters: You don't want all your revenue data – just the last 30 days. In the "Filters" section:

   • Select your Order Date dimension.

   • For the filter condition, choose "is in the past."

   • Enter "30" and select "days."

   • Click Run again to apply the filter.

5. Choose Your Visualization: In the "Visualization" tab, select the line chart icon. Looker will automatically plot your data, with dates on the X-axis and revenue on the Y-axis.

Your first tile is ready! Now, you just need to save it to your dashboard.

Step 4: Save & Assemble Your Dashboard

With your first visual ready, you can create a new dashboard and start populating it.

Create and Save to a New Dashboard

1. From your newly created line chart (your Look), click the gear icon in the top right corner and select Save.

2. A menu will pop up. Choose As a Look to give it a name (e.g., "Daily Revenue Last 30 Days"). Then, select where it should live, likely a shared folder.

3. Next, under Add to a dashboard, choose New Dashboard.

4. Give your dashboard a name like "Executive Revenue Dashboard" and click Save to Dashboard.

Your Look is now the first tile on your new dashboard! You can repeat this process for every KPI you planned in Step 1 – creating a bar chart for revenue by product, a single value visualization for your total MRR, a table for top customers, and so on – adding each one to this dashboard.

Arranging Your Tiles

In your new dashboard, click Edit dashboard in the top right. This puts you into edit mode, where you can:

• Drag-and-drop tiles to position them. A good practice is to put your most important, high-level KPIs at the top.

• Click and drag the corners of each tile to resize it. Give more space to critical charts and less to secondary metrics.

Add Dashboard-Level Filters

This is one of Looker's most powerful features. Instead of having separate filters on every tile, you can add universal filters that control the entire dashboard at once. A date filter is the most common one for a revenue dashboard.

1. While in edit mode, click Filters in the top toolbar, then Add Filter.

2. A configuration window will appear. Give it a title like "Date Range".

3. For the "Field to Filter on", select the main date dimension from your Explore (e.g., Order Date).

4. Go through each tile on your dashboard and make sure it's set to listen to this new date filter.

5. Click Save.

Now, any viewer can use this single filter at the top of the dashboard to change the time frame from "last 30 days" to "this quarter" or "this year," and all the tiles will update instantly.

Final Thoughts

Creating a Looker revenue dashboard transforms how you view your business's financial health, replacing manual reporting with a unified, real-time source of truth. By focusing on what matters - planning your KPIs, preparing your data model, and designing for clarity - you can build a tool that drives strategic decisions for your entire team.

While Looker is a powerful tool, it often requires a steep learning curve and help from a data team to manage the underlying LookML models. For marketing and sales teams who need revenue insights without technical overhead, we built Graphed to simplify the entire process. You connect data sources like Shopify or Stripe in a few clicks and just ask in plain language - "create a dashboard of my monthly recurring revenue vs. ad spend" - and get a real-time dashboard made for you in seconds.