The reason we collect data is to answer questions.  For marketers, those questions are usually about customer buying behavior — who is ready to buy, what they are likely to buy, which customers might defect. But marketing data is in trouble.

Lately, with Google snatching customer information wirelessly with drive-by mapping cars and companies surreptitiously tracking customer behavior on their websites, more questions are being raised by data than are being answered by data.  The war between the data hounds and privacy advocates is heating up.

The two biggest questions are “What data can we use?” and “What data should we use?” If the answers to these questions are not in sync, the industry is in for even more trouble and the data wars will intensify.  Here’s our take on the battle.

What data can we use?

Data comes in all sizes and shapes. Customer data can be demographic: zip, gender, age, or income level. That kind of data can often be collected without any input or knowledge from or by the customer. Third party data aggregators such as credit bureaus know a lot about you and they sell that information freely to companies who want your business. Should they?

Information gleaned from surveys and focus groups is more openly collected and less passive than demographic data.  At least the targeted customers know they are supplying the data. There are two problems with using this kind of data for marketing. First, only a small segment of customers respond to surveys; there is no way to know how the rest of the population thinks, so personalized marketing is not possible for the non-responders. Second, and this is not obvious but well documented, there is no correlation between responses to customer satisfaction surveys and the respondent’s future buying behavior. People say one thing and do another.

More accurate, more personalized, and definitely more toxic to defenders of privacy is the data captured in web clicks. Most people are wary of being followed around the internet. Many have no idea how pervasive this tracking is, and would be even angrier if they knew. Bowing to governmental pressures, browser manufacturers are making it easier to turn off tracking code and we may have a ‘do not track’ law in the near future. Consumers ask, “Whose data is this, anyway? Isn’t it mine, not yours?” This is the type of data most likely to bring the wrath of the privacy advocates onto companies that use it.

However, data associated with the sale of a product or service is willingly contributed, most personalized, and clearly belongs to the company that sold the product. Buyers willingly give up their billing address when they tender a credit card. In a B2B sale, the buyer’s contact information is almost always known. Similarly, buyers hand over their contact data in a B2C transaction over the web, from a catalog, or through a call center. Retailers with loyalty programs also capture transaction data that can be associated with the customer making the transaction.

Companies already have this kind of data sitting in their computer systems. Because this data is so personal, companies have an obligation not to share it or sell it without permission from the customers who volunteered it. Unfortunately companies often don’t know how to analyze it or use it for their own marketing.

What data should we use?

Happily for companies that know how to leverage it, the most useful data — from transactions — is also the data least likely to raise the ire of privacy advocates and least likely to have its origins questioned by a company’s customers. This data is a priceless corporate asset. It exists for all of a company’s customers, without the need to ask for it or pay for it. Even better, transaction data is the most predictive of future buying behavior, so it is the best type to use for marketing campaigns.

The challenge for companies is to make effective use of the goldmine sitting in their data files. “We’re drowning in data and starving for insight” is a common complaint. Even rarer than insight is the ability to deploy campaigns using the results of transaction data analysis. Yet that is precisely what a company must do to win the data wars

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