What is a Trendline in Excel?

Adding a trendline to an Excel chart is a quick way to see the underlying pattern in your data. It cuts through the day-to-day noise to show you the big picture, making it easier to spot trends, make forecasts, and understand your performance over time. This article will show you exactly how to add and interpret trendlines in Excel, including the different types available and how to choose the right one for your data.

What Exactly is a Trendline?

A trendline, also called a "line of best fit," is a visual tool that overlays your chart to show the general direction of your data points. Imagine you're plotting your monthly sales. Some months are great, and some are a little slower. The resulting chart might have a lot of peaks and valleys. A trendline smooths out those fluctuations and draws a single line to illustrate the overall trajectory. Is your sales trend generally increasing, decreasing, or staying flat?

In short, trendlines help you:

Identify trends: Instantly see if your key metrics are growing, declining, or holding steady over a period.
Make forecasts: Project future performance based on past data, giving you a reasonable estimate of what to expect.
Spot patterns: Recognize cycles or patterns that might not be obvious from looking at raw data points alone, such as seasonality.

How to Add a Trendline in Excel: The Step-by-Step Guide

Before you can add a trendline, you need a chart. Trendlines work best with chart types that show data over time or compare two numeric variables, like a line chart, scatter plot, or a bar/column chart.

Let's assume you have a simple two-column dataset, like dates and website sessions.

Step 1: Create Your Chart

Highlight the data you want to visualize.
Go to the Insert tab on the ribbon.
In the Charts group, choose a suitable chart. A Line or Scatter chart is usually best for showing trends. For our example, we'll pick a line chart.

Once you have your chart created, you're ready to add the trendline.

Step 2: Add the Trendline Element

Click anywhere on your chart to select it. You’ll see three small buttons appear on the top right side of the chart.
Click the "+" button, which stands for Chart Elements.
In the menu that appears, simply check the box next to Trendline. Excel will automatically add a default linear trendline to your chart.

That's it! You've added a trendline. But the real power comes from customizing it and choosing the best type for your specific data.

Choosing the Right Type of Trendline in Excel

Excel doesn't just offer a one-size-fits-all trendline. When you click the small arrow next to "Trendline" in the Chart Elements menu and select "More Options...", a "Format Trendline" pane will open on the right side of your screen. Here, you can select the best model for your data.

Linear

This is the default and most common option. A linear trendline is a straight line, best used when your data points are increasing or decreasing at a steady, consistent rate.

Best for: Data that follows a straight line.
Example: Tracking the growth of a subscription service that adds about 100 new customers every month. The growth is steady and consistent.

Exponential

An exponential trendline is a curved line used for data that rises or falls at an increasingly rapid rate. Think "J-curve" growth.

Best for: Values that grow or fall by a percentage over time.
Example: Early-stage "viral" user growth, where a small user base rapidly expands as each new user brings in several more. It's also great for modeling compound interest.

Logarithmic

This is essentially the opposite of an exponential trendline. It's a curved line best used for data that initially grows or declines very quickly and then starts to level off or plateau.

Best for: Data that experiences a burst of activity before stabilizing.
Example: The initial spike in website traffic after a big product launch that gradually settles into a more consistent daily number.

Polynomial

A polynomial trendline is a curved line best for data that fluctuates with peaks and valleys. Think of it as a rollercoaster. You can specify the "order" of the polynomial to determine the number of curves (bends) in the line. An order of 2 has one bend, an order of 3 has up to two, and so on.

Best for: Datasets with multiple highs and lows.
Example: Analyzing quarterly sales figures over several years that rise and fall with seasonal demand. A polynomial trendline can capture that cyclical pattern.

Power

A power trendline is another curved line used when the data is increasing at a specific rate. It's common in scientific and engineering measurements.

Best for: Datasets that compare measurements that increase at a specific rate, like the acceleration of an object over time.

Moving Average

This isn't a "best fit" line in the statistical sense. Instead, a Moving Average trendline smooths out sharp fluctuations in your data to make the underlying trend clearer. It works by averaging the data points over a specified period. For example, a 2-period moving average will average every two consecutive data points.

Best for: "Noisy" or highly volatile data where the daily or weekly fluctuations hide the bigger picture.
Example: Analyzing daily stock prices or daily website traffic. A 7-day moving average would smooth out the weekday vs. weekend volatility to show a clearer weekly trend.

Reading Your Trendline: R-Squared and Forecasting

In the "Format Trendline" pane, you’ll find a few checkboxes at the bottom that give you powerful information. The two most important are "Display Equation on chart" and "Display R-squared value on chart."

What is "R-squared"?

The R-squared value is a number between 0 and 1 that tells you how well your trendline actually fits your data. The closer the R-squared value is to 1, the more reliable the trendline is and the better it explains the relationship between your data points. A high R-squared (like 0.95) means the data points are very close to the line. A low value (like 0.20) means the data is scattered far from the line and the trend is weak or non-existent.

General rule of thumb: Look for an R-squared value of 0.80 or higher for a strong correlation. If your R-squared value is low for a linear trendline, try a different type (like polynomial) to see if you can get a better fit.

Making Predictions with Forecasting

One of the most practical uses of a trendline is forecasting. Excel makes this incredibly simple. In the "Format Trendline" pane, there's a Forecast section.

Forward: Enter the number of periods you want to project into the future. For example, if your chart shows 12 months of data, entering "3" here will extend the trendline three months into the future.
Backward: This does the same thing, but for past periods.

This allows you to create a visual forecast directly on your chart, giving you an evidence-based prediction for where your metrics are headed.

Some Practical Tips for Using Trendlines

Choose the Right Chart. Trendlines are most powerful on charts that show data over time (line, column) or relationships between variables (scatter). They don't make sense on pie charts or other categorical visualizations.
Don't Force a Trend Where There Isn't One. If your data points are scattered randomly and your R-squared value is extremely low no matter which trendline type you choose, it might mean there is no meaningful trend to analyze.
Forecasts Are an Estimate, Not a Guarantee. They are based entirely on historical data. A trendline can't predict a sudden market shift, a new competitor, or a game-changing marketing campaign. Use them as an educated guide, not a crystal ball.

Final Thoughts

Excel's trendline feature is a straightforward yet powerful tool for turning raw data points into a clear business story. By adding a single line to a chart, you can understand past performance, identify hidden patterns, and create a reasonable forecast for the future, all without writing complex formulas.

Of course, building these reports and manually refreshing your data in spreadsheets still takes time. At Graphed , we automate this process. We let you connect data from sources like Google Analytics, Shopify, and your ad platforms in just a few clicks. Instead of building charts and finding trends yourself, you can just ask questions in plain English, and our AI data analyst builds real-time dashboards for you instantly. Your trendlines and reports are always up-to-date, so you can spend less time wrangling spreadsheets and more time acting on insights.