How to Create a Retail Dashboard in Looker

Creating a retail dashboard in Looker turns your raw sales and inventory data into actionable insights that can drive your business forward. A well-designed dashboard shows you what's working, what isn't, and where you should focus your attention. This guide will walk you through the key metrics to track and provide a step-by-step process for building your own powerful retail dashboard in Looker.

Start with a Plan: Key Metrics for Your Retail Dashboard

Before you build anything, you need to decide what you want to measure. A dashboard is only as good as the Key Performance Indicators (KPIs) it tracks. Too many metrics create noise, while too few leave you with blind spots. Organize your dashboard around the core pillars of your retail business: sales, inventory, and customers.

Sales Performance KPIs

These metrics give you a high-level view of your business's financial health and sales efficiency.

Total Revenue: The most fundamental metric. Track it daily, weekly, and monthly to understand your overall growth trajectory.
Average Transaction Value (ATV): Calculated as Total Revenue / Number of Transactions, this KPI helps you understand how much customers typically spend in a single purchase.
Units Per Transaction (UPT): Similar to ATV, this measures the average number of items sold per transaction. It's a great indicator of cross-selling and upselling success.
Sales by Product Category/SKU: Identify your best-selling items and categories that are underperforming. This insight is crucial for product placement, marketing, and inventory decisions.
Conversion Rate: For e-commerce businesses, this is the percentage of website visitors who make a purchase. It's a direct measure of your website's effectiveness.
Sales Growth: Compare your current performance to past periods (e.g., month-over-month or year-over-year) to see trends and measure progress against goals.

Inventory Management KPIs

Effective inventory management is the lifeblood of a retail business. Too much stock ties up cash, while too little leads to missed sales opportunities.

Inventory Turnover Rate: Measures how many times you've sold and replaced your entire inventory over a specific period. A higher turnover rate is generally better, indicating strong sales or efficient buying.
Sell-Through Rate: Calculated as a percentage (Units Sold / Units Received), this shows how much of a product you’ve sold versus how much you ordered. It's especially useful for seasonal items or specific promotions.
Stock-to-Sales Ratio: This compares the amount of inventory you have on hand to the number of sales you're making. It helps you avoid overstocking and understocking.
Top Products by Units Sold: While sales revenue shows what makes you the most money, units sold shows what moves the fastest. This can inform your reordering strategy for high-volume, lower-margin items.

Customer & Marketing KPIs

Understand who your customers are and how they find you to build loyalty and drive repeat business.

New vs. Returning Customers: A healthy business has a good mix of both. This metric helps you understand customer loyalty and the reach of your acquisition efforts.
Customer Lifetime Value (CLV): Predicts the net profit attributed to the entire future relationship with a customer. It tells you how much a customer is 'worth' to your business over time.
Customer Acquisition Cost (CAC): The total cost of sales and marketing to acquire a new customer. You want your CLV to be significantly higher than your CAC.

Gathering Your Data: Required Sources

To populate your dashboard, Looker needs access to your data. Unlike some BI tools, Looker doesn't store your data itself. Instead, it connects to a data warehouse where you've consolidated your information. Common data sources you'll want to pipe into your warehouse include:

Point of Sale (POS) Systems: Tools like Square, Shopify POS, or Lightspeed provide raw transaction, product, and sales data.
E-commerce Platforms: Shopify, BigCommerce, or Magento are rich sources for online sales, customer behavior, and order data.
Web Analytics Platforms: Google Analytics provides e-commerce data like conversion rates, traffic sources, and on-site user behavior.
Advertising Platforms: Connect Google Ads and Facebook Ads to measure Return on Ad Spend (ROAS) and link campaign performance directly to an increase in sales.

How to Build Your Retail Dashboard in Looker: A Step-by-Step Guide

Once you have your plan and your data is consolidated in a warehouse (like BigQuery, Snowflake, or Redshift), you're ready to start building in Looker.

Step 1: Connect Looker to Your Data Warehouse

The first step is establishing the connection between Looker and your database. In the Admin section of Looker, navigate to "Connections" and "Add Connection." You'll need credentials for your database, including the host, port, and username/password. Once configured, Looker will be able to query your data directly.

Step 2: Define Your Business Logic with LookML

This is what makes Looker unique and powerful. LookML is a modeling language where you define your data's dimensions (the "what," like "Product Name" or "Order Date") and measures (the "how much," like "Total Revenue" or "Average Transaction Value").

Think of it as creating a single source of truth for your business metrics. You write the code once, and then anyone on your team can analyze the data without needing to know SQL. For example, to define total revenue, your LookML might look something like this in a view file:

By defining your metrics here, you ensure that everyone who reports on "total revenue" is using the exact same calculation, which helps maintain data consistency across your organization.

Step 3: Create an "Explore" for Users

An "Explore" is the starting page for your users to begin their analysis. It's defined within your LookML model file and exposes the relevant views (e.g., orders, products, customers) and their relationships (joins). By creating a Retail Sales Explore, you give your team a curated set of data specifically for analyzing sales and inventory performance, making it much easier for them to answer their own questions.

Step 4: Build Your First Visualization (a "Look")

Now for the fun part. Go to your new Retail Sales "Explore" to build your first chart.

From the left-hand field picker, select the dimensions and measures you need. For example, to view sales over time, you'd choose a dimension like Order Date and a measure like Total Revenue.
Click "Run" to fetch the data.
In the "Visualization" tab, choose the chart type that best represents your data. A line chart is perfect for showing a trend like sales over time.
Customize the chart's appearance using the settings menu (gear icon). You can adjust colors, labels, axes, and more.
Once you're happy with it, click the gear icon in the top right and select "Save" > "As a new Look." Give it a descriptive name like "Monthly Sales Trend."

Repeat this process for all the KPIs you planned earlier. Create separate Looks for your top-selling products (bar chart), sell-through rate (gauge), and new vs. returning customers (pie chart).

Step 5: Assemble Your Looks into a Dashboard

A dashboard is simply a collection of these Looks arranged on a single page.

Navigate to the folder where you saved your Looks and click "New" > "Dashboard."
Give your dashboard a name like Retail Performance Overview.
Click "Add Tile" and choose "Looks" to select the visualizations you just created.
Arrange the tiles by dragging and resizing them. A common best practice is to place your most important, high-level KPIs (like Total Revenue) at the top in large single-value visualizations.
Follow with more detailed trend charts and tables below.

Step 6: Add Interactive Filters for Deeper Analysis

A static dashboard is useful, but an interactive one is far more powerful. Add filters to allow users to slice and dice the data themselves.

On your dashboard, click "Filters" > "Add Filter."
A common filter is a "Date Range" so users can view data for last week, last month, or a custom period.
You might also add filters for "Product Category" or "Store Location."
For each tile on the dashboard, you'll need to link it to the filter by selecting which LookML field it should filter on.

With filters, a marketing manager can analyze sales for a specific product category they're running a campaign for, while a store manager can view performance for just their location.

Step 7: Schedule and Share Your Dashboard

To make sure your dashboard drives action, get it in front of the right people. Use Looker's scheduling feature to automatically send a snapshot of the dashboard via email or Slack every Monday morning. You can set the filters for the scheduled delivery, ensuring that each stakeholder gets a report tailored to their specific needs without having to log in and set the filters themselves.

Best Practices for a High-Impact Dashboard

Know Your Audience: A dashboard for a CEO should be high-level and strategic, while one for an inventory planner should be granular and tactical. Tailor the content accordingly.
Prioritize Clarity Over Clutter: Resist the urge to include every possible metric. Stick to the handful of KPIs that drive the most important decisions. Use whitespace effectively to make the dashboard easy to read.
Add Context: Use text tiles to add titles, explain what a chart represents, or define how a specific KPI is calculated. This helps remove ambiguity and ensures everyone interprets the data correctly.

Final Thoughts

Building a retail dashboard in Looker centralizes all your performance metrics into one clear view, enabling you to make smarter, data-driven decisions that grow your business. By defining your data logic, creating intuitive visuals, and making the insights accessible, you empower your entire team to move beyond gut feelings and focus on what the numbers are telling you.

While Looker offers incredible power, the process of setting up a data warehouse and modeling data in LookML can be complex, especially for small teams without dedicated data engineers. We created Graphed to simplify this process entirely. By connecting directly to your tools like Shopify, Google Ads, and Facebook Ads, you can use natural language to build real-time dashboards in seconds. Just ask, "Show me my sales and ROAS by campaign for last month," and get a live, interactive dashboard built instantly, skipping the setup and coding entirely.