The "make use of it or be prepared to lose it" element in the subscription market means that if your consumers don't engage with your services, you will ultimately lose that customer, the renewal and the revenue. The relationship between subscriptions and usage displays this aspect well. If a consumers usage reaches targets thresholds, the subscription revenues are retained at renewal. If usage climbs enough, subscription revenue growth can be generated by a new subscription tier or more seats. Similarly, customers with the most usage tend to expand their subscriptions to more complementary products.
If you flip the coin, if a consumer's usage dips under a certain threshold, the first thing that happens is tier churn, which reduces subscription income. Continuous dips in usage leads to service churn as the consumer chooses to use less of the service. Finally, consumer churn happens when usage drops so far down that no matter the of price the subscription it will not be justified.
Recording The Data and Utilising To Its Full Potential
Usage data is simply the data recorded about usage. Its volume, variety, and velocity make it difficult to harness. The volume of usage data includes billions of user events to be analysed for correlations and insights. The variety of usage data ranges from web events, mobile application events, call centre activity, and other customer interaction points and the velocity requires millions of new usage events being recorded and responded to every day. To complicate things more, usage data is generated and stored in systems that are separated from the subscription data, so attributing (i.e., linking) usage to the right rate plan, product, subscription, and customer can be tricky.
How Evolok Can Help You Get The Most Out of Your Data
As part of Evolok's services, our technology automates that integration of usage and subscription data. The result is predictive analytics utilised to drive revenue growth. The integration of the two sets of data allow correlations between usage and subscription retention, growth, and churn to be identified and quantified. Consequently, as usage data accumulates:
- Trial prospects can be segmented by those most likely to close
- At-risk customers can be identified early to prevent churn and retain revenue
- Renewals can be classified as cross-sells and up-sells to grow revenue
- Rate plan prices and packaging can be modified to optimise revenue
In other words, predictive analytics is made possible with Evolok and can be used to optimise subscription life cycles and customer lifetime value. By linking usage data to subscription data, you can quickly and easily identify the correlations on which trials are most likely to close, which customers are at risk, where the most up-sell potential exists, and what are the best cross-sell opportunities..
Predictive analytics derived from the combination of usage and subscription data allows a company to know what actionable pricing and customer management opportunities exist and align their resources to optimise revenue growth in the subscription market.