Retention & Recovery
Predict, Retain & Win-Back
Minimise customer subscription churn using predictive analytics, retry rules and automatic card updating
Automated and intelligent audience recycling technology, with minimal resource investment and success-based pricing
Retain and win-back using personalised marketing campaigns, leveraging voucher codes, discounts and offers
Automated reports to provide statistics and analysis on the effectiveness of personalised marketing campaigns over a specific time period
Customer Subscription Retention
The Retention & Recovery module provides a range of configurable features that minimises customer churn and boosts existing customer revenues. This includes:
Card Expiry Date Validation - validates the expiry date for the renewal cycle on a successful subscription renewal event
Automatic Account Updating - ensures the most current card information is used during authorisation attempts, preventing involuntary churn and optimising life time value
Early Pre-Renewal Authorisation - attempts the authorisation before the renewal date, offers the option to cancel or complete transaction and provides a window of opportunity to receive new card information from the subscriber
Retry Rules - configurable multi-layered time-based retry rules, which are configurable on an individual subscription or global basis
Customer Recovery & Win-Back Initiatives
Customer recovery is a fully managed authorisation recycling function. It initiates payment retries following a transaction-specific, optimised pattern. If the transaction attempts become exhausted a win-back campaign process can provide discounts to lapsed customers. The Recovery process includes:
Intelligent Authorisation Recycling - Subscriber profiling, determining the most likely retry sequence to yield an approval, which boosts approval rates, minimises attrition and maximises revenue
Win-Back Campaigns - Automatically request the customer to update their card information or leverage voucher codes, discounts and offers to drive win-back rates
Predictive Churn & Product Packaging
eSuite employs Machine Learning techniques which aids our clients by understanding consumer behaviours to generate highly accurate reports of consumers who are most at risk of cancelling their subscription.
Machine Learning is also employed to analyse the historical data of existing customers to understand at which stage of the journey they purchased and which product/service they are most likely to purchase based on previous behaviour and profiling.
See how we helped
Publishers are taking note of the changes to the industry as print plateaus, with 27% of publishers planning to invest most heavily in digital memberships and paywalls in 2017. Racing Post, the UK and...
This project enables Racing Post to make that next step towards truly innovative digital service strategies. Leveraging eSuite, Racing Post can better understand who our customers are and their usage habits, have the necessary tools to increase acquisition and most importantly reduce churn.