Discover how Cumulative LTV analysis can help you maximize the success of your application with an in-app subscription model. Learn how to track this powerful metric and how it can help you optimize your app performance.
The Cumulative LTV (lifetime value) metric displays dynamic revenue growth for different user segments. The formula depends on the calculation metric you select: ARPU (Average Revenue Per User), ARPPU (Average Revenue Per Paying User), or ARPAS (Average Revenue Per Activated Subscriber):
Cumulative LTV = ARPU/ARPPU/ARPAS * Lifetime
Almost everyone knows that Cumulative LTV measurement is important to subscription businesses. However, we want to emphasize how you can improve your product and marketing strategy:
Let’s take a look at how this chart works in Apphud.
This is a list with recommendations on how to use the Cumulative LTV chart in Apphud in full force:
ARPU/ARPPU/ARPAS. We calculate these metrics using proceeds.
30, 180, 365 days or your custom range is up to 999 days!
country, user gender, or age, and even search ad campaigns to identify the best customer segments.
If you have different subscription types: weekly, monthly, and annual, we recommend analyzing the longest cohort period - 999 days, it allows you to see the big picture.
For a long term of more than 2 years, the annual subscription may remain in the lead due to renewals and a higher price. However, the situation is different for shorter terms, and monthly or weekly paying users can be a larger part of your revenue.
Understanding the most profitable subscription plans is a way to choose a better pricing strategy and improve app performance. That's why Apphud offers the possibility of long-term LTV analysis with a custom range of up to 999 days.
Another practical piece of advice with Cumulative LTV analysis is to generate user acquisition hypotheses from the data you have through continuous segmentation and estimation. Acquire new customers and significantly increase your revenue.
Cumulative LTV metric analysis helps subscription businesses grow by providing insights into customer spending trends, enabling them to make informed decisions about how to acquire and retain customers and decrease the churn rate. It can also help identify areas for improvement in order to increase customer lifetime value and optimize pricing strategies. It can also be used to measure the effectiveness of marketing campaigns and track user engagement over time.
At Apphud, we recognize the significance of subscription analytics for app revenue growth. Hence, we prioritize data precision. Our platform supplies you with the most accurate app revenue data to provide you with growth hypotheses. Sign up for Apphud today!