How to Make a Pareto Chart in Looker

A Pareto chart is one of the most effective ways to find the biggest opportunities for improvement in your business. Rooted in the Pareto Principle, or the 80/20 rule, it helps you visually separate the "vital few" problems from the "trivial many." This guide will walk you through, step-by-step, how to build a powerful and interactive Pareto chart directly in Looker Studio (formerly Google Data Studio).

What is a Pareto Chart and Why Should You Use It?

The Pareto chart combines a bar chart and a line graph to instantly show you where to focus your efforts for the greatest impact. It’s based on the idea that in many situations, roughly 80% of the effects come from 20% of the causes. For example:

• 80% of your company's sales might come from 20% of your customers.

• 80% of customer complaints might relate to 20% of your product's features.

• 80% of website traffic might be driven by 20% of your marketing channels.

A Pareto chart visualizes this principle with two key components:

1. The Bars: These represent individual categories (like reasons for product returns, sources of support tickets, or top-selling products). They are always arranged in descending order from left to right, so the biggest single cause is immediately obvious.

2. The Line: This represents the cumulative percentage of the total. It starts at the value of the first bar and curves upward, reaching 100% at the last bar.

By plotting both on the same visual, you can quickly see which handful of issues contribute to the majority of your problems or successes. It cuts through the noise and provides clear direction on where to allocate your limited resources.

Preparing Your Data

Before you jump into Looker Studio, good chart-making starts with good data. For a Pareto chart, your data needs to be structured simply. You need two things:

• A Dimension: This is the categorical data you want to analyze. Examples include "Product Name," "Marketing Channel," "Complaint Type," or "Reason for Return."

• A Metric: This is the numerical value associated with each category. It could be "Sales Revenue," "Number of Sessions," "Ticket Count," or "Number of Returns."

Your underlying data should look something like this in a Google Sheet or database table. For our example, we'll analyze the reasons for product returns:

If your data is transactional (e.g., one row for every single return), Looker Studio will handle the aggregation for you. Just make sure you have a column for the reason and that each row represents one return.

Step-by-Step: Building a Pareto Chart in Looker Studio

Once your data is ready, you can start building the chart. We'll use the product return data from our example.

Step 1: Connect Your Data Source

First, open a blank Looker Studio report. Click on Add data on the report canvas or navigate to Resource > Manage added data sources > Add A Data Source. Choose the connector that matches where your data lives, such as Google Sheets, BigQuery, or a MySQL database. Follow the prompts to authorize and select your specific table or sheet.

Step 2: Start with a Combo Chart

The perfect foundation for a Pareto chart is the Combo chart, as it’s designed to display both bars and a line. From the toolbar, go to Add a chart and select the icon for Combo chart. Place it on your report canvas.

Looker will often populate it with default dimensions and metrics, which we'll configure next.

Step 3: Configure Dimensions, Metrics, and Sorting

With the combo chart selected, look at the Setup panel on the right. Now, let’s configure it for our Pareto analysis.

1. Dimension: Drag your category field into the Dimension box. In our case, this is "Return Reason."

2. Metric 1 (The Bars): Add your numerical field to the Metric section. This is "Number of Returns." Looker will probably create a table with "Record Count" by default, so replace that with your metric. We will keep this as the Bar series.

3. Sort: This is the most crucial step for the bars. Under the chart's setup options, find the Sort section. Set the primary sort field to be "Number of Returns" and make sure the order is set to Descending. This arranges your bars from largest to smallest, which is the standard for a Pareto chart.

At an instant, you'll see a bar chart ordered from the most frequent return reason to the least frequent. You're halfway there!

Step 4: Create the Cumulative Percentage Line

Next, we need to add the cumulative running percentage. Looker Studio makes this relatively simple by using built-in running calculations.

1. Add the Same Metric Again: In the Setup panel, drag the same metric ("Number of Returns") into the metric section again. You should now have two identical metrics listed. We will turn this second metric into our cumulative line. By default, it will be displayed as a second series of bars - we'll fix that.

2. Apply a Running Calculation: Hover over the second "Number of Returns" metric you just added, and click the pen (edit) icon.

   • In the settings window that opens, find the Running calculation section. Select Running Sum from the dropdown menu. This will sum up the values cumulatively from left to right.

   • Give this metric a more intuitive name, like "Cumulative Percentage," so you can easily identify it in the chart settings later.

3. Convert to Percent of Total: To turn the running sum into a percentage, go to the Style tab in the main right-hand panel. In the section for Series #2 (which corresponds to your second metric), scroll down to the bottom where you'll find the option "Show as," and select Line from the dropdown. This is a non-obvious step that makes this work correctly. This seems hidden but it is the easiest approach in Looker. Back in the setup menu for this metric, click edit on that duplicate "Number of Returns." Go to the Comparison calculation and change this to "Percent of total." This is the perfect setting.

Now your second metric is correctly calculating the running cumulative percentage. However, it's probably squashed at the bottom of the chart because it's being plotted on the same axis as the raw counts.

Step 5: Configure the Dual Axes

To fix the scaling issue, we need to assign our new cumulative percentage line to its own axis on the right side of the chart.

1. Navigate to the chart’s Style tab in the properties panel to the right.

2. Scroll down until you find the settings for each series (Series #1, Series #2). You might need to assign one for Bar and one for Line here but some combo-charts are setup with a default of bar then a line series automatically displayed as first a blue bar and then an orange line for example, bypassing some configuration efforts. Let's start with just bars.

3. Find the dropdown for Series #2 (your cumulative metric). Change its chart type from "Bar" to Line.

4. Right below that, you will see a dropdown for Axis. Switch it from Left to Right.

Instantly, your line graph will scale properly to its own axis, extending elegantly from the top of the first bar to the 100% mark on the top right of your chart.

Step 6: Final Styling and Formatting

Your Pareto chart is functionally complete, but a little styling makes it much easier to read.

• Label Axes: In the Style tab, under Axes, you can add titles.

  • Give the Left Y-Axis a custom title like "Count of Returns." This provides useful context to your boss and coworkers.

  • Give the Right Y-Axis a title like "Cumulative Percentage" using that same option field "Custom Axis Title." It's good reporting practice we'll use here and elsewhere.

• Format the Right Axis: By default, the right axis will show numbers like 0.2, 0.4, 0.8, etc. Select your line chart section you configured, and then back in the Setup for that chart find that same right-axis metric. Go to the main Setup panel, edit your cumulative percentage metric, and change its Type to Percent so that "0.8" becomes a much more readable "80%."

• Add the 80% Reference Line: This makes the crucial '80/20' point stand out. Navigate to the Style menu > scroll down to Reference Lines and click Add a reference line. Choose a constant value of "0.8" for 'value', give it a label saying "80% of issues" to emphasize just why you built this chart! Making your charts look good AND have a clear use can save the whole company a lot of grief. Don't overlook these last mile features.

How to Interpret Your Looker Studio Pareto Chart

Now for the fun part: turning this visual into actionable insight. Here's how to read it:

1. Identify the Biggest Bars: Look to the far left. The first two or three bars represent your biggest single problems. In our return reason example, "Wrong Size" and "Damaged Item" are clearly the primary drivers.

2. Use the 80% Line: Find the 80% mark on your Right Y-Axis. Trace a horizontal line over to where it meets your cumulative percentage line. Now, look down at the bars included to the left of that intersection point. These are the "vital few" causes that make up approximately 80% of the total problem.

3. Form an Action Plan: Based on our example, we can see that addressing only "Wrong Size," "Damaged Item," and "Changed Mind" would solve over 80% of all product returns. Instead of trying to fix six different problems at once, the team can focus its effort on refining size guides, improving product packaging, and perhaps clarifying product descriptions.

The Pareto chart's power is in its clarity. It channels your team's energy where it truly counts.

Final Thoughts

Building a Pareto chart in Looker Studio combines configuration of chart settings, metrics, and display styles, but the resulting visual is invaluable for data-driven prioritization. It transforms a simple list of problems into a clear roadmap for what to fix first, ensuring your efforts create the largest possible impact.

Going through these steps in traditional BI tools requires clicking through several menus. We built Graphed because we believe getting to that "aha" moment should be faster. Instead of manually adding metrics, creating running totals, and configuring dual axes, you can simply ask, "Create a Pareto chart of product returns by reason." Graphed instantly builds the same chart by connecting to your sources in real-time, handling all the complex setup in the background so you can spend less time configuring and more time acting on your newfound insights.