TLDR: Without adoption, there is no retention.

Of all the factors that lead to retention and upsell in subscription businesses like SaaS, adoption is surely the most critical factor.

If you’re going to improve adoption, you have to start with measurement. Here are the five measures you should track.

For each user, the 3 F’s:

Features

You need know which of your product’s features are being used by each user.

Your measurement should focus on the most important features of your product. This number usually ranges between 10-20 distinct features. If you’re measuring more than 20 usage event types, you’re probably measuring things that introduce “noise” into your data; esoteric features that aren’t used by most users.

Frequency

For each feature, you want to know “how much” or “how often” that feature is used. This is defined as the number (count) of times each feature is used by each user each day.

Form factors

Many products have multiple form factors. A form factor is a mode in which a user will interact with your product such as a web application, PC app, tablet app, smartphone app, customer account portal, etc. And many analyses have suggested that adopting two or more form factors is a predictor of user stickiness. Therefore, you will need to identify which form factors are being used to access your product features, by user.

Across all users: Active Users & Active User Rate

Now that you can measure each user’s adoption, it’s time to measure the overall population of users with “active users” and “active user rate” as the metrics.

Tracking all of your users helps you understand the effects of product changes on your user base. It can also hold clues for changes in the composition of your user base and whether they adopt differently. For example, if you recently started selling globally, this metric might reveal issues in catering to the needs of users outside of your home country.

Active User count

A popular way to define an Active User is someone who has performed at least one action in your product in a given time period such as a month. The metric name would be Monthly Active Users or “MAU”. You can also look at Daily Active Users (DAU) and Weekly Active Users (WAU) if those metrics are more suitable.

To calculate these metrics, take a defined time period (such as this month, this week or a specific day) and determine the count of users who are active in that period.

I don’t recommend using rolling averages such as “last 30 days” because it make your trended analyses much more complicated.

Active User rate

To track your overall rate of adoption, take a defined time period (such as this month, this week or a specific day) and determine the percent of users who are active in that period. Most people start with monthly intervals. The Active User Rate math looks like this:

MAU / Total Number of Users

Just like the Active Users metric, I don’t recommend using rolling averages such as “last 30 days” because it makes your trended analyses much more complicated.

Useful analyses

These five metrics can be used in powerful ways. We’ll blog more in the future on this topic, but here are some initial ideas:

Trended analyses

• Is our active user rate increasing or decreasing over time?

Segmentation analyses

• For inactive users, how is their adoption different across the 3 F’s?

Account analyses

• Within an account (defined as either a household or a business entity comprised of multiple users) what percent of users are active?

Unpacking the drivers of adoption requires measurement. The building block is user-level measurement across the 3 F’s. If you’re not doing this yet, now is a great time to start!