How to Make a Time Series Plot in Google Analytics

Spotting a trend on your website is the first step to understanding what's really working. A time series plot is one of the simplest yet most powerful tools for doing exactly that, turning a boring table of numbers into a clear visual story. This guide will walk you through exactly how to create and customize these essential charts right inside Google Analytics 4.

Graphed

Build AI Agents for Marketing

Build virtual employees that run your go to market. Connect your data sources, deploy autonomous agents, and grow your company.

Build Your First Agent

What is a Time Series Plot? (And Why You Should Care)

A time series plot is simply a line chart that shows a specific metric changing over a period of time. The horizontal x-axis represents time (days, weeks, months), and the vertical y-axis represents the metric you're measuring (users, sessions, revenue, conversions).

Think of it as the heartbeat monitor for your website or business. Instead of just knowing you had 10,000 users last month, a time series plot shows you the daily ebb and flow. It helps you ask better questions:

• Why did our traffic spike last Tuesday?
• Did that new blog post lead to more user sign-ups?
• Is our website traffic consistently lower on weekends?
• How did our Black Friday campaign traffic compare to last year?

This visual context is the key to moving from just collecting data to actually using it to make smarter decisions about your marketing, content, and sales strategies.

Finding Time Series Plots in GA4's Standard Reports

The good news is that you don't always have to build a time series plot from scratch. Google Analytics 4 is filled with them. In fact, most of the standard reports feature one right at the top. For instance, navigate to Reports > Acquisition > Traffic acquisition. The line chart you see at the very top is a time series plot showing you Users, Sessions, or another key metric over your selected date range.

You can hover over any point on the line to see the specific numbers for that day. You can also click the dropdown menu at the top left of the chart to switch between different metrics like Users, Sessions, and New users. These built-in charts are great for a quick overview, but the real power comes from creating your own custom views in the "Explore" section.

AI Agents for Marketing

Crash Course

Graphed

Free PDF · the crash course

AI Agents for Marketing Crash Course

Learn how to deploy AI marketing agents across your go-to-market — the best tools, prompts, and workflows to turn your data into autonomous execution without writing code.

Download the PDF

How to Build a Custom Time Series Plot in GA4 Explorations

When you need to analyze a specific metric that isn't in a standard report or compare two different metrics on the same timeline, a custom Exploration report is the way to go. This gives you complete freedom to build the exact chart you need.

Here's how to do it, step-by-step.

Step 1: Navigate to the Explore Hub

In the left-hand navigation menu of GA4, click on the "Explore" icon. This will take you to the Explorations hub, where you can start a new analysis or see your saved reports.

Step 2: Start a "Blank" Exploration

At the top of the hub, you'll see a template gallery. Click on the "Blank" template to start with a fresh canvas. This gives you the most control.

Step 3: Name Your Report and Choose the Chart Type

First, give your exploration a descriptive name at the top left, like "Weekly User Traffic by Device." Now, look at the "Tab Settings" column. Under the "Technique" dropdown, select "Line chart." This tells GA4 what kind of visualization you want to build.

Step 4: Import Your Dimensions and Metrics

The column on the far left is labeled "Variables." This is your palette - you need to add the "paint" before you can start "painting." In GA4's language, this means importing the Dimensions and Metrics you plan to use.

• Dimensions are the attributes of your data. For a time series plot, your primary dimension will always be time-based. Click the "+" icon next to "DIMENSIONS," search for, and select time attributes like Date, Week, or Month. Import them all so you can easily switch between views.
• Metrics are the quantitative measurements - the numbers you want to plot. Click the "+" icon next to "METRICS," search for, and select what you want to measure. Good starters include Active users, Sessions, Conversions, and Total revenue.

After selecting your desired items, click the blue "Import" button in the upper right. They will now appear in your Variables panel, ready to be used.

Step 5: Assemble Your Time Series Plot

Now the fun part. You're going to build the chart by dragging your imported Dimensions and Metrics into the "Tab Settings" column.

1. Set the X-axis: Click and drag your time dimension (e.g., Date) from the Variables panel and drop it onto the "X-axis" box in Tab Settings. This sets the timeline for your chart.
2. Set the Y-axis: Click and drag the metric you want to measure (e.g., Active users) and drop it into the "Y-axis" box.

That's it! As soon as you drop the metric in, GA4 will instantly generate a time series plot showing your active users for each day in the default period (usually the last 28 days).

Graphed

Build AI Agents for Marketing

Build virtual employees that run your go to market. Connect your data sources, deploy autonomous agents, and grow your company.

Build Your First Agent

Level-Up: Advanced Time Series Analysis Techniques

With the basic plot created, you can now dig deeper to uncover more interesting insights.

Compare Two Different Metrics on the Same Chart

Let's say you see a massive spike in traffic. The next logical question is, "Did that traffic actually lead to more sales?" You can answer this by adding a second metric to your plot.

Simply drag another metric, like Total revenue, from your Variables panel and drop it into the "Y-axis" box as well. GA4 will add a second line to the chart with its own axis on the right-hand side, letting you visually correlate traffic with revenue.

Use a Breakdown Dimension for Richer Detail

Imagine your user trend is flat over the last quarter. Is it flat across the board, or are some channels growing while others are declining? A "Breakdown" answers this perfectly.

Import a dimension like Device category or Session default channel group. Then, drag it from the Variables panel and drop it into the "Breakdown" box under Tab Settings. Your single line will instantly split into multiple colored lines - one for each category (e.g., separate lines for Desktop, Mobile, and Tablet).

This is incredibly powerful. You might discover that while your overall traffic is flat, your mobile traffic is actually growing steadily while your desktop traffic is declining - an insight that would be invisible in a single-line plot.

Tips for Effective Time Series Analysis

Creating the plot is just half the battle. Interpreting it correctly is what drives results.

Tip 1: Choose the Right Time Increment

The time dimension you use for your X-axis matters.

• Use Date for granular, day-by-day analysis when monitoring a recent campaign launch or looking for short-term issues.
• Use Week to smooth out daily fluctuations and see the underlying trend more clearly. This is often the most useful view for weekly and monthly reporting.
• Use Month for a high-level, long-term view of your performance over quarters or years.

AI Agents for Marketing

Crash Course

Graphed

Free PDF · the crash course

AI Agents for Marketing Crash Course

Learn how to deploy AI marketing agents across your go-to-market — the best tools, prompts, and workflows to turn your data into autonomous execution without writing code.

Download the PDF

Tip 2: Context is Everything - Compare Periods

Knowing that you had 1,000 users this week is good. Knowing that it's 20% more than you had last week is an insight. In the top left of the Exploration, under the report name, you can click the date range. A calendar will appear where you can enable the "Compare" toggle. This lets you plot this year vs. last year, or this month vs. a previous period, all on the same chart. This adds critical context to your data.

Tip 3: Look for Patterns and Seasonality

Look beyond single spikes or dips. Do you consistently see a dip in sales mid-month? Does your traffic always spike during the first week of a quarter? Recognizing these recurring patterns can help you anticipate user behavior and plan your marketing and inventory accordingly.

Tip 4: Correlate Data with Real-World Events

A numbers chart can't tell you the "why" on its own. Keep a simple calendar or log of your key business activities. When you see a huge traffic spike on your chart, check your log. "Oh, that's the day we were featured in that newsletter." When you see a sudden drop? "Right, that's when the site had a temporary outage." A data point without context is just noise, a data point with context is an answer.

Final Thoughts

Time series plots are fundamental to understanding business performance. By moving beyond GA4's standard reports and creating your own custom line charts in an "Explore" report, you gain complete control to turn raw data into a clear story about your website's trends, patterns, and growth.

Creating these views in GA4 is powerful, but often the full story involves data from other platforms. For example, plotting ad spend from Facebook Ads alongside revenue data. This is why we created Graphed. We wanted a seamless way to combine our analytics, sales, and marketing data into a single, unified view. Instead of painstakingly building reports, we can now just ask for what we want - like "Show me a line chart of Facebook Ads spend versus Shopify revenue over the last quarter, broken down by campaign" - and get a live, shareable dashboard in seconds.