Ramping up: the new user attention span

Once the technical onboarding is complete and your customers have connected their devices, your goal is to turn them into regular users within the next 30 days. After that, there's a high risk that they'll lose interest and churn.

And this comes with a question: at which point in the customer experience are you most confident that a user is here to stay?

There are three ways you can work this out:

1. The chasm
2. Usage pattern
3. Baseline value

Let's look at these one by one.

The chasm

To understand the chasm, you need to start with data.

The easiest way to set a goal for a shift from ramping-up to cruising is by looking at a graph of your users' first to last seen dates.

In the initial ramp-up stage, you should see a big dip followed by a longtail trail of churning users.

The end of your chasm is the point where the tip turns into the longtail trail. If you can push more users to this stage and beyond, you’ll find that a lot of them stay for longer.

Usage pattern

Daily, once a week, twice a month – knowing the ideal usage pattern of your product is essential.

If the usage is sporadic, the user clearly hasn't built a habit of using your device yet. Or they haven't seen enough value to use it as often as they should.

By helping more users reach the perfect usage pattern for your product, you can minimize churn and maximize lifetime value.

However, this approach doesn't work for every product. For devices that are sporadic by nature (gadgets) or a daily necessity (smart bulbs), usage patterns alone aren't enough to show that users are here to stay.

Baseline value

Baseline data is all about what your users do, rather than how they do it.

One option here is to identify the key features that show the real value of your product or app. And this should always be based on data – not just what your team feels is right because a lot of development time went into it.

Once you've identified those features, you could say that anyone who hasn't experienced them yet is still ramping up.

Another option is measure usage frequency against retention until you can say something like this: "People who use the product X times are 95% likely to stay with us for at least X years",