Quantitative customer analysis approaches such as data mining and predictive modeling are valuable for companies with existing products in relatively stable markets, says Wharton marketing professor George Day. However, he thinks companies seeking new growth in rapidly evolving markets may not have the requisite data to discern relevant patterns.

“Even when quantitative data is most preferred you still need the qualitative [approach] to interpret what’s going on, to give it depth,” says Day. “You can’t hand an ad copywriter behavioral data and expect him to do a lot. He needs a more refined, colorful, multi-dimensional picture of the target customer.”

The greater challenge companies face is actually leveraging or operationalizing customer insights. Whirlpool and Procter & Gamble, for instance, are using customer information to build “concept banks” that drive new product development. The companies even mix and match their findings -- such as consumer reactions to certain product attributes -- to develop new concepts. The companies then convene in-house brainstorming sessions to translate those concepts into products. “You still have to get from the data to a creative insight," says Day. "Someone has to have an intuition, a sense that this is worth pursuing.”