How can you identify the actions that influence users to be successful during the onboarding process?

Your goal is to get users to witness the promise of your app, and in order to get there, they need to go through a series of mandatory steps (the onboarding steps). However, that is not the only activity that they will complete during the onboarding process.

To go from one step to another, they will need to perform specific actions, such as: start filling forms or navigate through the application. Any action that the users complete will have an impact in helping them finish the onboarding process, or dropping off of the onboarding process.

Identifying the onboarding step with the highest drop off is not enough if you want to increase the onboarding rate. A good strategy is to analyse the actions that users perform after this step in order to identity what are the actions (if there are) that are specific to users who drop off the onboarding process. 

For this reason, we have developed a report on the actions users take between each onboarding step.

How does this report help you?

The goal of this report is to identify the actions that influence users to successfully finish the onboarding process, or to drop off of the onboarding process.

First, let's look at the way this report is analyzing data. (link report)

For any period that we select, InnerTrends will analyze the cohort for all of the accounts created during this period, and it will report on all of the activity that these users performed between any of the selected onboarding steps, regardless of whether or not that activity happened during the selected period.

That means that if a user created an account on the last day of the selected period and they had activity during the onboarding process after that day, that activity is going to be reported.

The longer of a period you select, the more statistically significant data you will be.

How to interpret the data and what decisions to make

There are three high points of interest when we analyze this data.

1. The first point of interest is represented by all of the actions that are performed much more by the users that are successful in getting to the next step of the onboarding process, but are not performed by the people who drop off of the onboarding process.

We refer to these actions as being specific to users that reach the next step. These actions could influence people in their decision to continue, or it could be the other way around: users performed them because they already made the decision to continue. This means we have a correlation and not causation.

To determine causation you need to look at these actions in the context of your app and ask yourself this: are they actions that people have to perform in order to get to the next step or are they actions that simply prove to be helpful for people in order to get to the next step? The second category is more likely to imply causation.

Highlighting these actions with in-product guides will help more users understand the benefits they might be losing if they don’t perform them.

2. The second category of actions that we want to analyze are the actions that are specific to people that drop off of the onboarding process. Just like in the previous example, it could simply be correlation or causation (doing these actions was a consequence of the fact that users have already decided to drop off).

Drill down the users that performed one of these actions and dropped off, and analyze their activity in order to see why that happened. You might discover an error, or scenario that was not covered by your onboarding flow.

A great way to decrease the impact of these actions is to add guidance to them in order to help users get back on the right track. Users that perform one of these actions after reaching that onboarding step should be prompted with a message trying to guide them on the right track.

3. The third category of actions that we want to analyze are the actions that have no impact or are not specific to neither successful users nor the users who drop off.

If, within this list, you identify actions that were designed to have a positive impact on the onboarding process, you need to redesign them.

Optimization strategies

  • If you identify actions that you did not expect to have a positive or negative influence on your users, we suggest that you drill down all of the users that interacted with that action, and look at all of their activities in order to see how they got to it.
  • Look at all of the actions that have had a positive impact on getting users to the next step of the onboarding process in order to come up with ideas of what content you can send them through email.
  • Last but not least, write in-product guides that use the actions that have had a positive influence on users in order to increase your chances of converting them.

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