Predictive analytics can help marketers upsell and cross-sell products to customers. But the key word in that sentence is “customers.”
So says Stephen H. Yu, vice president of data strategies at Papillion, Neb.-based data provider Infogroup.
Different divisions handling different channels or various departments in charge of various products can cause problems for customers if companies decide to organize data based on those guidelines alone when creating predictive models. So instead, Yu suggests, “Companies should go through a paradigm shift towards 'customer-centric' marketing. Even the best-designed databases and models will turn out to be ineffective if marketers use such tools with 'division-centric' minds. That is how one customer ends up getting confusing offers in [a] short timeframe from the same company.”
This is just one bit of advice about how marketers can best use predictive analytics to identify cross-sell and upsell opportunities. More suggestions come from Yu and:
- Ozgur Dogan, vice president and general manager of the Data Solutions Group at Columbia, Md.-based marketing agency Merkle;
- Jeff Hassemer, vice president of product strategy at New York-based marketing services provider Experian Marketing Services;
- Paul McConville, senior vice president of sales and marketing at Vienna, Va.-based data provider TARGUSinfo;
- Stephanie Miller, vice president of email and digital services at Indianapolis-based marketing software provider Aprimo, a Teradata company;
- Barbara Nelson, a product manager of analytic and segmentation products for Little Rock, Ark.-based data solutions firm Acxiom Corporation;
- Wilson Raj, global product marketing principal for customer intelligence at Cary, N.C.-based business analytics software and services provider SAS; and
- Jesse Roberts, senior data strategist at Costa Mesa, Calif.-based marketing agency Rauxa.
1. Rethink the data to include. Miller's comment that “CRM is the new black” is only slightly tongue-in-cheek. Customer relationship management efforts in channels such as social media are yielding many insights that she says should be included in data-gathering efforts for predictive models.