How to Make a Line Graph in Looker with AI
Making a line graph to track your key metrics over time is a fundamental reporting task, but it can often feel tedious in tools like Looker Studio. This guide will walk you through creating line graphs in Looker, first the traditional way, and then by using its emerging AI features to do the heavy lifting for you.
Why Use a Line Graph?
Before jumping into the "how," it's helpful to quickly recap the "why." Line graphs are the best way to visualize a trend or see how a particular metric has changed over a set period. They connect individual data points, making it easy to spot patterns, growth, and anomalies at a glance.
You should use a line graph when you want to answer questions like:
How has our website traffic grown month-over-month?
What were our daily sales during the Black Friday campaign?
Is our social media follower count increasing or decreasing over the last quarter?
How did a specific marketing campaign impact user sign-ups over a two-week period?
Essentially, if your question involves the words "over time," "daily," "weekly," "monthly," or any other time-based period, a line graph is almost always the right choice. They tell a story that static numbers on a spreadsheet never could.
The Traditional Way: Manually Creating a Line Graph in Looker Studio
If you're familiar with Looker Studio (formerly Google Data Studio), you're probably used to the manual drag-and-drop method. While powerful, it requires you to know exactly what dimensions and metrics you need. Here's how that process works.
Step 1: Get Everything Set Up
First, make sure you've connected your data source. This might be Google Analytics, a Google Sheet, your Google Ads account, or another platform. Inside a new Looker Studio report, you'll need to choose from your available data sources to bring that information into your workspace.
Once your data is connected, click Add a chart from the toolbar and select one of the "Time series" chart options. This is what Looker Studio calls a line graph.
Step 2: Configure Your Dimensions and Metrics
This is where things can get confusing if you're not a data expert. Once you place the empty chart on your report canvas, a configuration panel will appear on the right side of the screen. You'll need to tell Looker what data to show.
Dimension (the "When"): This is your time element. You need to drag a date field into the "Dimension" box. This could be Date, Week, or Month. This sets up the X-axis (the horizontal line) of your graph.
Metric (the "What"): This is the number you want to track. You'll drag a numerical field like Sessions, Revenue, Users, or Conversions into the "Metric" box. This populates the Y-axis (the vertical line).
If you want to compare two metrics - for example, sessions vs. pageviews - you can drag a second field into the "Metric" box. Looker will automatically draw a second line on the graph for you.
Step 3: Style and Customize Your Graph
After your data is configured, you'll likely want to clean up the graph's appearance. Click over to the Style tab in the configuration panel. Here, you can:
Change the colors of your lines.
Add or remove data points.
Toggle a trendline on or off to see the general direction of your data.
Adjust axis titles, gridlines, and labels to make the chart easier to read.
This process is effective, but it involves several clicks and a clear understanding of your data structure. If you pick the wrong dimension or metric, your chart won't make sense, leading to frustrating trial and error.
The New Way: Using Generative AI in Looker Studio
Google is integrating generative AI into its Cloud products, including Looker, to simplify the report-building process. Instead of manually dragging and dropping fields, you can now describe the chart you want in plain English, and Looker's AI will attempt to build it for you.
How an AI-powered Prompt Works
Let's recreate the same traffic graph, but this time with a simple prompt. In modern versions of Looker equipped with GenAI, you might find a prompt-based chart builder or a feature called "Help me create". Rather than searching through menus, you can just type what you want to see.
A good prompt is direct and specific. For example:
"Create a time series chart showing daily sessions from our Google Analytics data for the last 30 days."
Let's break down why this prompt is effective:
"Create a time series chart...": You're telling the AI exactly what kind of visualization you want.
"...showing daily sessions...": You're specifying both the metric (sessions) and the time interval (daily).
"...from our Google Analytics data...": You're pointing it to the correct data source.
"...for the last 30 days.": You're defining the time period.
The AI will interpret this command, automatically select Date as the dimension and Sessions as the metric, apply a 30-day filter, and generate the line graph you asked for without you needing to touch the configuration panel.
Refining Your Chart with Follow-Up Questions
The conversation doesn't have to stop there. Once the initial chart is created, you can refine it with follow-up prompts.
"Now add a second line to show users."
"Change the color of the 'sessions' line to blue."
"Can you add a moving average trendline?"
This conversational approach turns a multi-step configuration process into a simple back-and-forth. It’s faster, more intuitive, and lowers the technical barrier, allowing anyone on your team to start visualizing data and finding insights without needing to become a Looker expert.
Essential Tips for Effective Line Graphs
Whether you build it manually or with AI, a few design principles will make your line graph much more effective.
1. Don't Overcrowd the Chart:It's tempting to track ten different metrics on one graph, but this usually results in a messy, unreadable chart often called a "spaghetti graph." Stick to a maximum of three or four different lines. If you need to compare more, consider creating a second chart.
2. Label Everything Clearly:Your graph should be understandable without additional explanation. Give it a descriptive title (e.g., "Daily Website Traffic - Past 90 Days"), and make sure the X-axis (Date) and Y-axis (Sessions) are clearly labeled.
3. Use Color Wisely:Use distinct, contrasting colors for each line. Be mindful that some team members may have color vision deficiencies, so relying on color alone is a bad idea. Using different line styles (solid vs. dashed) can also help.
4. Provide Context:A line graph shows the "what," but it seldom shows the "why." If you see a massive spike in traffic, use Looker's text box tool to add an annotation explaining it. For example: "Spike due to viral blog post" or "Dip due to site maintenance." Context turns data into a story.
5. Choose the Right Interval:The time interval you choose (daily, weekly, monthly) changes the story. Daily data is good for granular analysis of short-term campaigns, but it can look noisy. Weekly or monthly data smooths out those daily fluctuations and makes it easier to spot longer-term trends.
Final Thoughts
Leveraging AI to build charts in Looker Studio transforms a technical chore into a straightforward, conversational process. It streamlines your workflow, empowering you to move from a question to an answer in seconds instead of navigating complex menus. You can focus less on wrestling with the tool and more on what the data is actually telling you.
While features like this are making BI tools easier to use, we believe building reports should be even simpler. That's why we created a platform where connecting data sources like Google Analytics, Shopify, and Facebook Ads is turnkey, and building entire dashboards is as easy as asking a question. With Graphed you simply describe the report you need, and our AI data analyst builds a live, interactive dashboard for you, saving you the headache of learning a traditional BI platform at all.