Using a Data Deep Dive to Inform a Customer Referral Program
The insights revealed by this work are already shaping our thinking and actions for the refer-a-friend program. The Revium team deeply understood our goals, and without needing being prescriptive in the approach they were able to help us uncover insights in our own data. Particularly useful were a handful of 'ah-ha' moments that we are now implementing with a test and learn approach to make the program more effective.
Red Energy is a 100% Australian Energy Retailer owned by Snowy Hydro. Red Energy is a challenger brand with more than 1 million customers across VIC, NSW, QLD, SA and ACT.
Customers can see energy as a grudge purchase and acquisition and retention can be challenging. After all, it can be difficult to engage a customer in a positive way if they only think about their energy provider if something goes wrong (such as bill shock) or when they’re moving home (an already stressful time).
To help tackle this issue, Red Energy launched their Refer-A-Friend program in 2012. Revium was recently engaged to analyse the success of the program and to identify audience insights that will drive more effective business practises.
Revium conducted exploratory analysis across the Refer-a-Friend data set and delivered audience insights and recommendations to better improve the program for the brand.
The key challenge was to analyse the existing dataset of almost tens of thousands of customers with a common attribute over the last 3 years and develop insights on how to improve the program and generate more customers.
Red Energy engaged Revium to help better understand insights about the relative value of customers who engage in the refer-a-friend program. Red’s desire is to get more effective at timing, communications and offerings in the program.
Red Energy and Revium take data privacy and handling very seriously and both companies ensured all data was handled correctly and lawfully in order to adhere to Australian Data Privacy Principles.
Revium followed a 3-phased approach to improve the effectiveness of the RAF program leveraging a range of tools and techniques. These phases included;
Clean and map the data
This comes with all exploratory analysis and it is critical to ensure accurate reporting and audience insights.
Graphs were created to analyse and visualise the data so it was easy to digest and identify specific trends.
Revium identified audience insights from the customer base by answering all the specific questions. There was a well-rounded mix of insights that validated suspicions, and surprising insights that wouldn’t have been identified if the analysis wasn’t completed.
Action the insights
What is an insight without a ‘so what’? Revium recommended over 20 actionable insights to Red Energy to help improve the RAF program and drive more sales for the business.
Red Energy now has a clearer picture of the value of their refer-a-friend customers. Red better understands how they behave, how to market & communicate to people that use refer-a-friend, and how to improve the effectiveness of the program in the future.
Revium received very positive feedback from multiple stakeholders at multiple levels at Red Energy as this type of analysis pulls back the curtain on improving business effectiveness and is core to Red’s ongoing success in an increasingly complex, challenging and competitive industry.
Each node in the 2019 Red Energy Referral Network Visualisation reflects the distance between referrers.