Trend Lines

Crazy peaks and valleys in your graphs got you down? Fear no more! πŸ“ˆ

Baremetrics avatar
Written by Baremetrics
Updated over a week ago

What are Trend Lines?

Trend lines are a way to average your data. This allows you to ignore the random dips and spikes in your metrics and get to the core of what the data is trying to tell you.

Trend lines are most useful for long date ranges.

Enabling Trend Lines:

Click on the Trend Lines icon at the top right and choose which one you'd like to use.

What types of questions can I answer with Trend Lines?

  • Is my churn trending downward?

  • Does my MRR follow an exponential growth pattern?

  • Am I succeeding in increasing my Average Revenue per Customer?

But what does it all mean?!?!

All these terms are likely to excite the data nerds among us, and scare a few others. Not to worry! Here's a breakdown of what it all means.


Linear draws a straight line through your data and completely ignores peaks and valleys. If you're looking at a metric that is mostly up-and-to-the-right (such as MRR, hopefully) Linear is a great choice.


Similar to linear except it will follow a curve. Great for data that changes rapidly and then settles, like say a rapidly growing MRR that plateaus or slows.


Another one with lots of syllables! This trendline is great for following data with lots of peaks and valleys. Polynomial trendlines may have a maximum of 2 curves. Churn and LTV are two metrics that Polynomial trendlines can work well with.


These trendlines change at a specific rate. This works well with any up-and-to-the-right type data, like say MRR.


This is for data that rises or falls at an exponential rate. Only a handful of businesses grow at an exponential rate–a great example is a company like Slack.

Moving Average

For each data point, we look at it, and the two other data points next to it, and average them. This is great for data that ebbs and flows quite regularly, and often has erratic data points. Churn, LTV and ARPU often work great with this method.

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