In this article, you'll learn...
- Five key considerations for predictive modeling
- How predictive modeling can boost your marketing efforts
- What to look for in a predictive modeling partner
We're entering a new Age of Marketing Precision (think AMP) brought on by ever-increasing computing capacity. One result of that amped-up computing power is the ability to process complex sets of data faster, and outputs that more precisely predict the relationship between marketing inputs and human behavior.
In short, new modeling techniques can bring brand managers closer to achieving the dream of "push this button, get that result!"
Ad Age recently reported that Procter & Gamble has spent $15-$20 million for modeling that will give the company a real-time read on its marketing mix return on investment (ROI) so it can make faster adjustments and focus on communications tactics that produce results.
Not every marketer has that kind of budgets, and different kinds of affordable predictive models exist for different marketing needs, such as strategy development, product-concept optimization, product-line optimization, and media mix modeling, to name a few.
If you're thinking about jumping on the predictive modeling bandwagon, here are five points to consider.
1. Good model outputs depend on good inputs
Or, as the saying goes: Garbage in, garbage out. A company that specializes in predictive modeling can guide you on the types of inputs needed for a good model, and will supplement your own knowledge of category, competitors, and relevant brand attributes. Look for a modeling partner that understands business and can help you think through the model inputs that will lead to a robust and powerful model.
2. Try to be complete