How to Create a Look in Looker

Creating a “Look” is one of the first things you’ll do in Looker, and it’s a foundational skill for anyone wanting to get answers from their data. A Look is essentially a saved report - a single chart or data table that answers a specific question. This guide will walk you through the entire process step-by-step, from starting your analysis to visualizing and saving your results.

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What is a "Look" in Looker, Exactly?

Before building one, it's helpful to understand what a Look is and isn't. Think of a Look as a single, focused piece of insight. It’s not a full dashboard with multiple charts, but rather the individual building block you might use to create a dashboard.

If a dashboard gives you a panoramic view of your business's health - like the instrument cluster in your car showing speed, fuel, engine temperature, and RPMs - a Look is just the speedometer. It’s one specific measurement used to answer one specific question, such as:

• How many new users signed up last week?
• What were our total sales by product category last month?
• Which marketing campaigns had the best click-through rate this quarter?

Looks are incredibly versatile. You can use them for quick, one-off analyses, save them to refer back to later, add them to dashboards, or even schedule them to be emailed to your team on a regular basis.

First, You Need to Understand What an "Explore" Is

In Looker, you don't start with raw data tables. Instead, you start from a query starting point called an "Explore." An Explore is a curated dataset that your data team has already set up for business users. It's designed to be a user-friendly and logical starting point for asking questions about a specific area of the business.

Don't worry, you don't need to be a developer to use them. You just need to know which one to pick. Common examples of Explores include:

• Orders: Used for analyzing anything related to sales, like revenue, order counts, and product performance.
• Users: Used for understanding customer data, such as sign-ups, demographics, and user activity.
• Website Analytics: Used for exploring website traffic data like sessions, page views, and traffic sources.

Think of choosing an Explore like picking the right tab in a large company spreadsheet. Once you know you want to analyze sales data, you start with the "Orders" Explore.

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Step-by-Step Guide to Creating Your First Look

Let’s walk through the process of creating a Look. For this example, imagine we work for an e-commerce company and we want to see our sales totals for each product category over the last 90 days.

Step 1: Choose Your Explore

First, navigate to the "Explore" section from the main Looker menu. You'll see a list of available Explores. Since our question is about sales and product categories, the "Orders" Explore is the perfect starting point. Click on it to open the Explore interface.

Step 2: Understand Dimensions vs. Measures

When you open an Explore, you’ll see a list of fields in the left-hand sidebar organized into collapsible groups. These fields are your building blocks and they fall into two main categories: dimensions and measures.

• Dimensions are the columns you want to group your data by. They are categorical or descriptive fields. Think of them as the "what," "who," "where," or "when." In our example, Product Category and Order Date would be dimensions.
• Measures are the numbers you want to calculate or aggregate. They are the numerical values that you can perform math on (sum, average, count, etc.). For our example, Total Sale Price would be a measure.

Dimensions are typically color-coded blue, while measures are orange, making them easy to tell apart.

Step 3: Build Your Report's Data Structure

Select Your Dimensions

First, we need to know what we are grouping our results by. Since we want to see sales by product category, we need to find the "Product Category" dimension. You can scroll through the field list or use the search bar to find it. Once you find it, click on it, and it will be added to your query.

Select Your Measures

Next, find the "Total Sale Price" measure. Search for it in the sidebar search bar and add it.

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Step 4: Run the Query

Now that you’ve selected your dimension and measure, click the "Run" button at the top right of the screen. Looker will process your query and return the results in a data table.

Now we have all order totals, grouped by the category of what was purchased, but this table will include all sales from the company's entire history! That isn't very useful, so in the next step, we'll narrow our query down further with some filters.

Step 5: Filter by Your Desired Data Range

You can see the unfiltered result now you've run your query. First, we have the Order Count and Order Total Sales. These numbers are currently for the entirety of this company's time in business.

To only see sales from the last 90 days, you should add a time limit as our third and final filter, so only results within that timeframe will return. First, we will need to find the "Created Date" in our sidebar and add that in as our third filter.

Once you select that, you get a menu with different "types" of filtering that you probably are already familiar with. You can set specific dates, like from March 1 to March 31, but instead, we want to set it up as "relative," so it's always pulling the past 90 days from the current date. To do that, set your timeframe from that dropdown list to "In the Past," with '90' on the left side of the day, with "days" on the right. Make sure the default filter setting is set to "complete days." Finally, re-run our results.

Visualizing Your Data

Now that we have the right data, let’s make it easier to understand. A data table is functional, but a chart often tells a much clearer story.

At the top of the data section, click on the “Visualization” tab. Looker will often guess an appropriate chart type, but you can easily change it. You’ll see icons representing different visualization options. Here are a few common ones and when to use them:

• Table: The default view. Best for seeing precise numbers or a lot of detail across many dimensions.
• Column/Bar Chart: Perfect for comparing values across different categories. This is a great choice for our "Sales by Product Category" report.
• Line Chart: Ideal for showing trends over a continuous period, like daily website traffic over a month.
• Pie Chart: Use to show the proportion of parts to a whole (e.g., percentage of sales from each region). Use these sparingly, as they can be hard to read with more than a few categories.
• Map: Great for visualizing geographical data, like users by country or sales by state.

For our example, a Bar Chart is a great fit. Select it, and Looker instantly transforms your table into a visual chart. You can customize it further by clicking the “Edit” gear icon next to the visualization options to adjust colors, labels, axes names, and more.

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Saving and Sharing Your Look

You've built a query, filtered it down, and created a great visualization. The final step is to save it so you don't have to rebuild it every time. This is what officially turns your exploration into a "Look."

Saving Your Look

1. Click the gear icon in the top right corner of the screen.
2. From the dropdown menu, select "Save..."
3. Choose "As a new Look."
4. A dialog box will pop up. This is where you finalize the details:
5. Click "Save."

Congratulations, you’ve just created your first Look!

Sharing Your Look

Now that it's saved, sharing it is easy. Open your Look and click the gear icon again. You'll see options to:

• Share a short URL: This copies a link you can send to other Looker users.
• Download: Export the data or visualization as a CSV, Excel file, PNG image, and more. This is perfect for use in presentations or other documents.
• Send or Schedule: You can send the Look once to a specific email address, or schedule it to be automatically delivered on a recurring basis (e.g., every Monday morning).
• Add to Dashboard: Add your new look onto a dashboard you manage.

Final Thoughts

Creating a Look in Looker is your entry point to data exploration and analysis within the Business Intelligence Toolset. By starting with the right Explore, selecting dimensions and measures, filtering your data, and choosing a clear visualization, you can answer specific business questions quickly and effectively. Knowing how to save and share these insights is what will enable your team to start making more repeatable, data-centered decisions.

While powerful, tools like Looker involve a learning curve around concepts like Explores, dimensions, and the manual step-by-step process of building reports. At Graphed, we’ve created a way for users to skip that complexity entirely. By connecting your marketing and sales data sources just once, you can have our AI data analyst build real-time reports and dashboards for you simply by describing what you want to see in natural language. Instead of clicking through menus to build your "Sales by Category" chart, you can just ask, and get an answer in seconds.