Entrant: FCB New Zealand Nominee: Mercury Awards: Nexus Gold - CRM & Data Management, Industry Bronze - Communications/Utilities
The energy sector is highly competitive, heavily focused on acquisition and playing hard at both ends of the funnel – big brand activity and pointy acquisition offers. While the short-term wins have an addictive appeal, it can be an expensive long-term strategy relying more and more on deep discounting and offers to lure customers in or keep them.
The result? 1 in 5 Kiwi households switching energy companies each year leading to annual churn sitting at 20%.
Tired of playing this blunt, expensive, commercially unsustainable game, Mercury switched it up. The hypothesis: if they could predict in advance when current customers were seriously considering switching, they could reduce churn rates.
Deploying an innovative predictive retention strategy, that combined data smarts, technology and personalisation, they were able to target “at-risk” high value customers with relevant messaging earlier than ever before by using over 17 data sources and their own Enterprise Application Network to identify signals of potential churn.
Proprietary banner optimisation technology combined with Mercury’s EAN platform then allowed them to create and serve multitudes of personalised digital and social display ads, tailored to audience segments at different stages of the customer journey.
Taking this segmented approach meant creative needed to adapt to the audience and context. So a carefully constructed messaging matrix of Brand, Retrospective Value and Future-Value Based Offers allowed Mercury to maximise retention, while minimizing the category-standard reliance on deep discounting.
The campaign was the epitome of CRM and data management, leveraging a wide range of 1st, 2nd, and 3rd party data and unifying technology platforms in order to enhance customer relationships and ultimately deliver business value.
It’s precision strategy ultimately delivered one of Mercury’s most successful retention campaigns ever, reducing churn and reducing the average cost of retention.