Did you know that up to 60% of your new users interact with your app only once? These are all the users who create an account but never finish the on-boarding process.
And yet, how many of you use the number of sign-ups in your reports and stats, and not the number of on-boarded users?
In what follows we will show you how not focusing on on-boarded users can lead to misleading conclusions that can affect your business.
So… how relevant is it to base your reports only on sign-ups?
Truth being told – you’re probably falling in a trap.
What we witnessed in most cases is that the on-boarded users growth trend is stable even when the sign-ups trend fluctuates a lot. These stats can greatly influence your perception on the current status of your business.
Some of the reports highly affected by this issue are:
- Retention Rate
- Upgrade Conversion Rate
- User Lifetime
- Cost of Acquisition
Let’s see how these reports are influenced by your choice of using one number or the other.
Example #1: Retention report for sign-ups vs. for on-boarded users
This is how the retention report looks like for the sign-ups.
The graph shows a huge 90% drop in users a week after creating an account. These users never visit your app again. Let’s face it – a first week retention rate of 10% is not what you’ve wished for.
And this is how the the same report looks like for the on-boarded users.
If you decide to look at things from a different perspective, and take into account only the people who finished the on-boarding, you will find out that 20% of them came back to your app.
600 users vs. 300 is not so bad after all.
Now… which report is relevant? How will you interpret the data?
If you take into account the first results, this means you have a retention problem and you should start a campaign to increase your first week retention. But the second report points out that retention is not really the issue here. The real problem is getting people to finish the on-boarding process, which would require an on-boarding optimization campaign, not a retention campaign.
Example #2: Upgrade conversion rate for sign-ups vs. for on-boarded users
Typically you report how many of your trial users become paying customers.
The example that we are going to show below is taken from a company with 32612 new users out of which 353 became paying customers.
This 1% conversion rate from sign-ups to upgrade was way below their expectations and targets. Just looking at these numbers, there was no way to know where to start optimizing their conversion rate.
When they used the on-boarded users for their conversion report, they discovered a 2 % conversion rate from on-boarding to payment – twice as big as the figure above.
They came up with 2 actions plans from the graph above:
- Increasing the on-boarding rate which would have a huge impact on the number of paying customers.
- Targeting all the customers who paid but did not finish the on-boarding process, as they would be the first ones to cancel their subscriptions.
Now they had a clear action path on how to increase the number of paying customers up to 5 times.
Example #3: User Lifetime for sign-ups vs. for on-boarded users
The User Lifetime Value is defined as follows:
User lifetime = 1 / Churn
Now, the churn rate can be reported for sign-ups or for on-boarded users. Most companies report user churns for sign-ups.
But let me show you how these 2 figures influence your results and your perception on how your business is doing.
For the sake of the example, let’s assume that you have 1000 sign-ups on day #1 and after 4 months 340 active users.
If you use the number of sign-ups for the calculus, you will get a churn rate of 16.5% and a user lifetime of 6 months.
This is how we reached these numbers:
1000 sign-ups – 340 on-boarded users after 4 months = 660 churned users in 4 months.
660 churned users / 4 months = 165 churned users / month.
Sign-up Churn Rate = 165 churned users / 1000 sign-ups = 16.5%
User lifetime = 1 / 0.165 = 6 months.
Now let’s look at the same example from an on-boarded user’s perspective.
Stats show that 600 users churn the very first day. That means that over the course of the following 4 months, for the 400 remaining users the average churn rate / month will be 5% and the user lifetime of 20 months.
This is how we reached these numbers:
1000 sign-ups – 600 churned users on the first day = 400 on-boarded users left on the first day.
The rest of the 600 churned users are irrelevant to your report now.You will focus only on the 400 remaining users.
At the end of the 4 months you still have 340 on-boarded users.
This means that 400 remaining users – 340 on-boarded users = 60 churned users in 4 months.
60 churned users / 4 months = 20 churned users / months.
On-boarded Churn Rate = 20 churned users / 400 initially on-boarded users = 5%
User lifetime = 1 / 5% = 20 months
That means the on-boarded user life time is at least 1.6 years – versus 6 months when reported to all signups. Quite a difference!
This is an oversimplified example, since it does not include all the variables when calculating churn, such as:
- Previous users
- Reactivated users
Still, it helps us make our point: your marketing campaigns and customer acquisition efforts can determine significant fluctuations in the number of created accounts. Many times, the fluctuations are not found when it comes to the number of on-boarded users. Here is a random example from one of our customers:
Reporting churn to sign-ups is prone to these fluctuations, while reporting the number of on-boarded users will offer you a much more accurate and reliable view on your business.
Example #4: Cost of acquisition for sign-ups vs. for on-boarded users
Let’s take the example of a company whose CLV / client is $1100. In order to optimize costs, the company sets a target of $1000 for each new client.
Their conversion rate for the free trial users turning into paid customers is 10%. This means that, in order to generate a new client who will pay $1000 for the period using this product, the company needs to generate 10 free trials for which they can pay up to $100 / user.
The company hires an advertising agency and sets the acquisition target to a maximum cost of $100 for each new trial.
After three months of advertising campaign, the company crunches the numbers. The results are not as expected. The sales targets generated from the advertising campaign are not reached although the metrics reported by the agency are within limits: less than $100 for a free trial.
On a more detailed analysis, the company realizes that conversion rate for the free trial users turning into paid customers is much lower than 10%. Digging even deeper, the company notices that there are far more free trials that abandon the product in the first few days after sign-up, compared to the free trials generated by other marketing channels.
The users’ decision to create an account depends on the promise made on the landing page and on the banners. Create false expectations, and they will leave.
This is exactly what happened. The advertising company started to over-promise in order to reach its target, so many users left before onboarding. While the agency reached its target, the company did not.
Using the number of on-boarded users and not the sign-ups in your analyses and decisions will ensure a higher quality of the generated leads and will help you eliminate the problems from the scenario above.
The security this method offers in unparalleled. You will be able to raise the stakes much higher, and count on a more efficient outcome.
For a 25% conversion rate from onboarded users to paying clients , the company can raise the budget to $250 for each onboarded user. It will also ensure much more chances for the final revenue targets to be reached.
Hope you found our insights useful and will be able to apply them in your company.
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