/ Statistical Modeling
Overview: Maximize objective
(i.e. response rates, incremental sales, marketing mix) using regression
analysis, target models, segmentation using cluster and factor analysis,
forecasting and tracking using predictive models, significance testing.
Using Regression Modeling
rates for acquisitions and renewals, increase sales to target audiences,
and optimize marketing mix. Example: built models for several of
HachetteFilipacchi magazine titles identifying subscribers most likely to
renew. In this case, models were coupled with an innovative mail timing solution
and mail selection strategy.
More about response
preference, affinity points programs redeemers, likely program defectors,
product switchers & migrators within program, the timing of market entry,
and heavy users. Example: built a GM Card redeemer model identifying the
likelihood each customer would redeem their rewards and how soon for millions
Using Cluster and Factor Analysis
types such as defectors, in market buyers, ethnic groups, military/college
buyers, employees, owners/loyalty, competitors/conquest, and unique segmentation
schemes using multivariate analysis. Example: Segmented GMs hourly,
salaried and retired employees into research defined attitude and
energy dimensions for inclusion in their Ambassador Program, designed
to encourage and empower employees to sell cars.
about segmentation (PowerPoint).
including seasonality and other patterns using previous months or years of
data and assumptions about future trends. Results are tracked and compared
to forecasts. Example: dynamic, interactive sales and revenue forecasts for
the GM Card.
between results that are directionally different and those that are