Heaptalk, Jakarta — When we create a product, it must be user-oriented. In other words, it can solve the user problem so that it can give the impression of an “AHA” moment for the user. Thus, the user can decide to use the application, starting from installing, becoming an active user, and making transactions.
These events are what we actually expect as the product owner. But in reality, users are very likely to get an ‘exception scenario’, where instead of what we expect, they can become active users and make transactions to generate revenue; instead, the user moves out of our product by being inactive or uninstalling.
It is what we can define as ‘Churn’. And the ratio of how much the user “moves out” can be identified as “Churn rate”. How can we identify and reduce our product’s churn rate to have the potential revenue from the customer journey we provide on the products?
In the webinar session about ‘Churn rate’ initiated by MoEngage with the theme #Growth Master Class on Wednesday, February 24, 2021, several product practitioners such as Alodokter, Fabelio, and Julo gave tips about this churn rate handling. Here are the lessons learned that we can learn.
Why is churn rate analytics so important?
Depending on the industry, varying stats and case studies show that the acquisition phase is 7-13% costlier than customer retention. However, customer retention can encourage the Net Promoter Score, where it is the metric to measure loyal customers. And if the Net Promotor Score increases by 5%, it can increase the profit by 90%.
When a brand or product can reduce its churn rate by several points, it has a pretty useful impact in achieving the goals that products want. It could be generating revenue, or increasing user downloads, and increasing the number of active users.
Churn rate analysis can also provide useful insights to be used as a reference by the product development team to improve the product quality by fixing some “potential causes,” which are the factors of why users eventually “move out”.
How to identify
According to Arian Vivaldi, Alodokter’s Head of Marketing, the way to identify the churn rate is to map the events we want. For example, when the user first goes onboarding our product, we define what the user needs to do afterward? Do explore features, read articles, update account profiles, and so on. Please note, this is relative in some business industries.
Next, we match the percentage of users from the first event to the last event. How many percent survive. Then, the number of users who do not complete until the end process we want is called the churn rate.
We can also identify the churn as a group of users who are no longer active for several periods or have uninstalled. The product owner can assist the metrics to measure this with deep learning from cohorts analytics.
How to control churn
Arie Wisnu Pradono, Chief of Marketing Officer Fabelio, explained the strategy to control churn. We can use metrics that are relevant to our business model. For example, Fabelio uses the customer Lifetime Value (LTV) parameter because it fits well with the B2C eCommerce business model.
Then use analysis from cohorts to identify user groups based on their preferences so that you can see the characteristics of each user. From the product side, you can practically control the campaign’s pattern, where users who have bought the sofa are unlikely to be offered a sofa anymore.
What is the magic wand?
The magic wand here is an effort from the product side to perfect the customer journey, oriented towards the customer’s expectations.
According to Mikhal Anindita, Julo’s Head of Marketing, products must deliver the customer journey as applicable as possible. The trick is, with understanding the customer whether is there a pain point? If the pain point has been identified, consider to continue improving the product and maintaining engagement through good communication with the user.
And based on the best practices that she has been through so far, if the customer manages to find the AHA moments, they are less likely to churn.
How to swing back the moved out customer
We often meet users who have visited but never engage again or fall into the ‘sleep’ user category. In the product point of view, we can do it by delivering messages as personal as possible by talking to a specific group of people. The channel can use touchpoints such as WhatsApp, Website, Socmed, Push Notification, etc.
For the case study of Alodokter, they use a flow funnel campaign by MoEngage to set the trigger and conditional rules for receiving the notification. They also employ A/B Test & Optimize with different message approaches & timing to bring the users back, including delivering the benefit, feature insights, article, and free-offer campaign.
Also, you consider using engagement based on user interest. Use campaign flow where users receive the notification based on conditional events. In Alodkter cases, it is likely to contribute an incremental increase in Daily Active User & Monthly Active User, that contribute up to 15% to overall event performance.
