In many markets, user subscriptions run in cycles as the user commits to an operator – and a device – for a 24 month period. For many operators, the keeping track of the tail end of these customer cycles is one of their only churn prevention processes. The flaw with this model is that they are highly opportunistic – neither take in account the key moment when a user is truly looking for a new device, namely the moment when their current device no longer lives up to their expectations. This could be due to battery deterioration, insufficient storage, sluggishness or changes in user behavior. It is at this point – when the user feels the need to improve their current device experience – that they starts to see the advertising from the competition.
Using eBuilder’s Device Insights, a Nordic operator A/B tested segmentation based on device experience for their 2017 Black Friday campaign4. Using the operator’s self-service app as channel and engaging the users through on-device notifications nearly forty thousand unique users were targeted for the campaign.
The target segment was identified using Device Insights, and ranked the users device experience in parameters including battery performance, utilized storage capacity, device performance, and likely-next-device. All parameters were collected and analyzed over time using prescriptive analytics and machine learning. The peer group was represented by users with Android devices not matching the target segment criteria.
The device insight and segmentation allowed the operator to be more specific in their marketing, identifying potential issues as well as offering the user a device that matched his or her next-likely-device. The results indicate improvements across all steps in the sales funnel – from notification CTR through time spent exploring the full campaign website to sales conversion.