Banking & Financial
Providing the financial sector with the state-of-the-art predictive tools and enhanced analytics required for effective customer segmentation, targeting, acquisition and retention.
Westpac needed deeper insight into their credit card customers so they could boost card holder profits and reduce churn.
Datamine developed a customer ‘Love score’ so Westpac could measure its customer’s passion for the Westpac brand.
The Love model leveraged Westpac’s existing market research Net Promoter Scores (NPS) which Datamine then correlated with customer’s credit card behavioural data, demographics and hotpoints redemption rates – delivering a love/commitment score for every Westpac customer.
The love score initiative expanded Westpac’s market research sample results and enabled the bank to segment their credit card customers based on a card holder’s level of ‘love’ for Westpac. This enhanced the existing ‘current and potential profitability’ models and enabled Westpac to target marketing communications accordingly.
With a product offering that included credit cards, store cards and insurance products, the financial services division of a nationwide retailer wanted to better understand the characteristics of its customers, their location, demographics and profitability - with a specific interest in who was leaving and joining on a monthly basis.
Datamine created socio-demographic and behavioural profiles of cardholders and created several categories to distinguish groups of customers with similar characteristics and behaviours.
Datamine provided a suite of management reporting options - providing a window into customer dynamics and profiling the characteristics of clients who were both leaving and joining.
The monthly reports also enabled finance team to monitor the change in delinquency levels and balance transfers in and out of the cardholder base.
Analysis found that 50% of profit was generated by only 15% of customers, signalling a very high value group that needed to be identified and looked after.
Datamine were able to show that although the retailer's card spend had increased year on year, the customer base was actually shrinking, due to churn and minimal acquisition.
Motivated by the initial findings, the group further tasked Datamine with delivering solutions by which it could assess whether its lost customers were high or low value, and that could also accurately predict likely credit card ‘churners’. These reports have provided the company with actionable customer insights leading to more accurately targeted marketing and communications initiatives and an increased return on investment.
A large banking group wanted to understand more about its existing Business Banking customers - and how these businesses fitted within the overall SME market. These insights would then be used to help the bank develop its growth strategies and direct future marketing campaigns.
More specifically, the bank wanted to identify opportunities for cross-selling to its existing customers, and accurately define geographic and industry areas with the most potential for acquiring new business.
Datamine analysed the bank’s existing market share by region, business size and industry to identify areas where there was potential to acquire more SME customers.
The project also explored the product portfolio of current customers and identified gaps that indicated a cross-sell opportunity for the bank. Additionally, the analysis identified a particular product that was of high value, but which to date had received low uptake – presenting the bank with evidence of an area of great potential for cross-sell marketing that would likely to deliver significant returns.
This project has enabled the bank to accurately identify growth opportunities and better target its marketing and communications initiatives towards geographical and industry areas with the greatest potential for profitable clients.
Interestingly, marketers at the bank had already formulated an image of the ‘ideal SME customer’ which they requested be taken into account when carrying out the analysis. While the project was able to prove some of the assumptions that made up this profile were correct, some were also debunked – delivering a strong fact-based research platform for the bank’s future strategy planning.