From credit-worthy to target-worthy: How predictive scoring is being used in marketing

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Would you bother mailing a list of a million contacts if you knew that only 100,000 of those contacts were “worthy” of your campaign and very likely to respond?

Innovation is not necessarily the invention of something new, but the result of finding a new use for an existing product, service, methodology or practice. Take the use of predictive scoring in marketing.

Predictive scoring has helped credit lenders identify people who were most likely to behave optimally as account holders, i.e.: those who take out a loan and repay the minimum instalments within the given period of time period and were also based on demographics and payment behaviour. Every time you make payment on a loan or pay for a product or service in monthly instalments, you’re generating data that will be fed into a scorecard to determine your credit score, or credit-worthiness.

Think of it this way: Predictive scoring answers the question "Who is most likely to...?" based on the application of weighting to criteria that creditors created to show the results of a certain type of behaviour.

Innovative marketers are beginning to use this same methodology to determine their contacts’ “target-worthiness,” i.e.: who is most likely to respond or who is most likely to be a profitable customer? By using predictive scoring and scorecards, Marketers are now able to reduce target list sizes from millions to only thousands of “target-worthy” contacts.

By identifying variables within such data sources as demographic data, purchase behaviour and credit bureau data, predictive scoring and scorecards can be used to assign points to each variable and administer a score to the consumer that indicates their “target-worthiness” for your campaign. By applying scoring to your customer or prospect base you can:

• Increase the response rates with a more focused, targeted audience;
• Decrease the cost of customer acquisitions by targeting only the most desirable contact profiles;
• Reduce the weakening of your brand by decreasing the number of leads who are unlikely to be interested in your offering; and
• Segment offers by different needs, wants and responses to marketing messages; which lets you receive more relevant data and improve the rate at which people respond.

Industries that use predictive scoring today

Insurance

Principa has helped a South African insurer to take pre-emptive action on its existing customer base by using a number of behavioural characteristics that collectively anticipate human behaviour. As a result, the client is able to rely on statistical predictions to identify and rank their client base by propensity to miss payments or equally by potential to expand policy coverage. Equipped with this information, the client is now in a position to make an informed decision on growth and retention and as a result decide who should receive attention and to what degree. It all begins with a first generation model (or scorecard) built using historical data; fresh campaign performance data is then used to update the scorecard on an ongoing basis.

Hospitality

This industry uses intelligent analytic solutions to draw insights from their customers' purchasing behaviour to better understand their needs and preferences. This allows them to review their product mix (the 4 Ps: Product, Pricing, Promotions and Placement), and continually adjust to improve marketing ROI and overall profitability.

Hilton Hotel Worldwide uses geographic, demographic, psychographic (different personality traits, values, attitudes, interests, lifestyles) and benefit-oriented variables to divide its target market into segments or groups. In this way, the most attractive or suitable service and product campaigns are targeted very efficiently and effectively. With this marketing strategy, reports show that the revenue of Hilton Worldwide from 2009 to 2015 continued to increase and that they generated approximately 10.5 billion U.S. dollars in 2014 alone.

Transportation

This industry has used market segmentation to identify typical traveller behaviour and characteristics for many years. They used the normal socio-demographic variables (age, sex, education, income, marital status) to determine customers' preferences, but they found they also needed a way to reveal what motivates this behaviour. A prime example of how this works well is with Southwest Airlines. By focusing on predictive analytical marketing strategies Southwest Airlines improved their campaign ROI and now use predictive scoring to target their most desirable customer profiles. By collecting data using weighted scores, they found that not only do variables such as passengers’ educational levels affect their expectations and perceptions; but scores also differ by frequency of flight and flight purposes.

Predictive scoring can reduce your overall campaign cost by reducing your target list size to only those contacts you’ve deemed “target-worthy” and likely to respond.