Predictive Modelling identifies eligible ECO scheme prospects for leading UK insulation provider
A leading UK insulation specialist required a data-driven approach to identify potential customers that would qualify for free insulation under the ECO scheme. The ECO scheme, mandated by the UK government, aims to reduce energy consumption and support people living in fuel poverty by funding the installation of energy-saving measures in their homes. Identifying households that qualify was crucial to our client’s goal of expanding their service reach.
The challenge was to identify a multi-dimensional set of variables critical for identifying ECO scheme eligible households. These variables needed to include energy efficiency, income, property type and age, whether the households received benefits, and their family composition. Notably, households with elderly or young children were more likely to qualify. It was crucial to establish an effective and reliable methodology, and to provide enough data volume for both test and roll-out activity.
Our methodology combines actual property variables with modelled household information to gain an insight into both property attributes and consumer characteristics and behaviours. Data was carefully selected from our UK Household File which contains no personal data providing a GDPR compliant view of over 30 million UK residential households (owners and renters).
We collated the key data variables and incorporated them into our proprietary predictive model, which identified the most significant factors contributing to ECO scheme eligibility. By utilising a data-driven approach, we were able to provide our client with a comprehensive list of households ranked by their likelihood to convert.
Our data-focused strategy identified many ECO scheme-eligible homes that had not been targeted before. This not only grew our client’s customer base but also let them increase their services into areas not yet reached by their competitors.
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