Marketing Profitability Gets a Boost With New Analytics Tools
In a time of slim profit margins, every advantage counts when trying to boost marketing profitability. In an effort to improve profits, one credit card provider realized that they needed to adjust the manner in which they identified active customers. Their goal was to focus marketing efforts on those individuals who were most likely to spend more money. The solution they sought more accurately identified this specific customer segment, helping save time and money and improve their profit margins.
Response patterns across customer categories
The card provider decided to test their existing profitability models to see if improvement could be identified. These models were tested against Equifax Advanced Decisioning Attributes, the most current set of foundational attributes from Equifax, and were augmented with Equifax Dimensions™, which identifies a consumer’s credit activity over the previous 24 months.
Their team constructed four new versions of the models to evaluate key customer categories, including customers more likely to respond to an offer, customers more likely to respond to an offer and spend more than the average customer in the next six months, those more likely to get a new bank card in the next six months, and those most likely to both get a new bank card in the next six months and respond to offers.
A tale of two models
The comparative analysis was conducted using the Kolmogorov-Smirnov (KS) statistic, which measures the distance between the total percentage of consumers in the “good” target categories and “bad” target categories – response to offer, spend, propensity to open a new bankcard and combinations of those (per the company’s marketing campaigns). The higher the KS score, the better the model performs at differentiating high-spend customers from the low-spend group.
Comparative analysis showed lift in the KS scores of each measured category.
Comparative analysis results
In this exercise, the provider evaluated KS points for the top percentiles in each category, then calculated the “lift,” or improvement, in the KS score of each category over the category scores in the previous model.
The results? Adding Equifax Dimensions™ to Equifax Advanced Decisioning Attributes helped increase the accuracy of identifying customers most likely to respond to an offer by 18 percent incrementally and improved lift across every category measured. Because Equifax Dimensions™ is based on a customer’s actual credit behavior history, it can help provide the truest form of marketing predictability — a powerful tool for businesses pursuing improved marketing profitability. Of course, results may vary across different tests.
Marketing action items based on results
Armed with this information, the credit card company gained solid data to act upon in streamlining and focusing marketing activity to help increase acquisition and boost marketing profitability. They can better prioritize and segment their customer base for marketing initiatives and can also choose to extend or increase credit limits to high-spend customers.
This extremely focused approach not only helps lower marketing costs, but it also helps improve the effectiveness of marketing campaigns, which ultimately may boost profits for the company. The conclusion? More precisely targeted marketing can help yield improved marketing profitability.
Image source: Equifax, Flickr
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