Electronics Retailer Uncovers Insights to Optimise Pricing and Profitability of Extended Warranty Subscriptions

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Case Study
Electronics Retailer Uncovers Insights to Optimise Pricing and Profitability of Extended Warranty Subscriptions

Industry: Retail

Challenge: Optimising Pricing and Profitability of Extended Warranty Subscription

Solution: Predictive analytics, financial modelling, dashboard, reporting

Technology: MY SQL, Power BI, Excel

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Situation and Challenge

Our retail client sells extended warranty subscription as an add-on service contract to customers which provides coverage for certain types of damages or defects that may occur after the expiration of the original warranty.
 
The problem is that there is a great deal of variation in the profitability of a warranty subscription as the level of claims on subscriptions is one of the key factors in determining the profitability of such products.
 
The challenge for our client is to fully assess the level of claims and associated costs in order to set optimal subscription prices and understand the customer lifetime value as key drivers of profitability.

Insight and Action​

Our client’s previous analyses were of a highly aggregated nature, leaving limited insight into channel and category performance. This led to inaccurate forecasting, mispricing of products and an inability to identify the underlying drivers of revenue, cost and profitability.

In response, we engaged stakeholders from IT, Finance and Commercial teams to source and analyse five years of transactional data across all channels and territories. We then implemented probabilistic bottom-up aggregation model to assign a probability distribution to each customer cohort, segmenting based on customer value dimensions such as product category, channel, type of warranty, tenure, etc.

This new model enabled us to accurately forecast the lifetime value of undiscounted revenue and cost based on churn and claims propensities among customer cohorts. The data was segmented into over 25 value dimensions, unlocking greater understanding and unexpected insights into lifetime value and profits earned from warranty types and product categories. 

Results and Impact

We developed a real-time Power BI dashboard to deliver comprehensive insights into product performance, empowering the finance and commercial departments with granular data visibility to quickly recognise base trends and respond to any potential adverse outcomes. 

Our analysis further demonstrated that the sales channel has a much more pronounced influence on profitability than initially expected. We found that one channel was consistently loss-making due to higher marketing costs and greater claims frequencies.

Interestingly, we found that 85% of core revenue was generated by just 14 products, which is less than 30% of the entire category range. The year-on-year margin increased by 1%, however, there were large margin fluctuations across categories due to multiple factors.

We identified new pricing opportunities with margin differentials that reflected channel profitability and achieved a 45% improvement in forecasting accuracy. 

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