Predictive Modeling - Methods and Uses

Aug, 11 2011

Predictive modeling is a set of statistical procedures designed to predict a set of outcomes based on measured variables, assumptions and inputs.  In a broader sense, it includes product recommendations, but for practical purposes, we’re limiting it here to responses to marketing actions.

Predictive modeling is used in marketing for 4 reasons

  1. Marketing spend effectiveness (How much to spend)
  2. Targeting (Who to target)
  3. Promotion differentiation (How to differentiate offers)
  4. Contact strategy (How to contact customers over time)
1. Marketing Spend Effectiveness
Marketing spend effectiveness (MSE) deals with optimally allocating marketing budget against activities and marketing vehicles.  In case of direct marketing, it deals with how many people we should contact given the cost and benefit (incremental or total).
Through predictive modeling, a response (or incremental response) is calculated and converted into expected margin.  Comparing this margin expectation at a customer level is compared against the cost of the marketing action.  The point when the benefit is equal to the cost,  is the point of optimal spend, where any additional spend returns less than the cost of the action
2. Targeting
Targeting deals with how to choose the people for marketing.  Predictive models create a score for each customer, which could be sorted and selected against.  Understanding where customers fall within the spectrum leads to offer differentiation
3. Promotion differentiation
Most often, mass campaigns cannibalize margin, due to the fact that we'll be giving away discount to people who would have bought anyway.  This is probably the most important statement. So much margin is lost from campaigns this way.  Predictive modeling allows marketers to target offers so the customers likely to buy anyway are not offered discounts as much as people who are not likely to buy.
4. Contact strategy
Predictive analytics allows contruction of contact strategies where customers are selected for campaigns that they are likely to response.  This is more important in cases where the cost of campaign is small but the opportunity cost is high.  Opportunity cost comes in two flavors.  First of all it is the cost of doing something else, second is losing the ability to market to the consumer, as in the case when consumer unsubscribes from email.