The Cost of Data

There really isn't much we can't find out about you as an individual consumer today. If I have your email address, I can reverse append your home address, tie that to your income range, more than likely your FICO score, marital status, presence of children, type of vehicle, home ownership, educational level, consumption patterns, memberships, affiliations and possibly even your shoe size.

As a consumer, I had to go through the realization that my data exists everywhere. There really isn't much a business couldn't find out about me if they really wanted to.

For years, marketers have been trying to aggregate as much about the consumer as possible, some self-disclosed and some appended. But in most cases, the cost to do this in scale and at the individual level has been the barrier. If you went to your vice president of marketing and said, 'I'd like to append my customer file with five fields of data,' he or she would ask the obvious question: 'What is the return on this investment and how often will we need to do this append?'" It's rarely a one-time activity.

Marketers try to build online engagement elements like preference centers. I've become less enthusiastic about these and the value they bring a business. Aside from subscription management -- which newsletter I want to get -- many are woefully underutilized by marketers, rarely supported with marketing efforts and become a waste of time for the business. How many of you have developed a preference center, to find out that only 5% of your customer or subscriber base actually engaged with it -- and less than half of those actually kept the information updated?

Now let's add a new dimension to this view. We'll apply behavioral and attitudinal data to the mix, plus what we know you do on the Web and some level of context to why you may be browsing the site, signing up for those newsletters and purchasing. The task becomes increasingly complex and expensive to house all this at an individual level.

There are going to be some spectacular things happening in the Consumer Research/Data CRM space over the next 10 years that will freak out consumers, completely disrupt businesses and cause you to rethink how you scale marketing efforts. Audience profiling is becoming a real-time effort. Why is this important? You spend a lot of money to reach and acquire new customers (for sales or publishing purposes) and rarely are you validating the people you are targeting with any third-party source.

What if you could acquire more females on ESPN's site than Oprah's site? Are you getting the inventory you actually pay for? Or did they sell off the "women" inventory in your target range? On the surface, it's a no-brainer: Target the site, and you'll get what you paid for. But the Web has become a funny place, and behavioral targeting is a tricky thing to optimize.

From a retention marketing side, we continually try to build a profile of a consumer, but again, besides empirical transactional information, we have no means of validating who we are targeting, not without great cost. Moreover, many businesses don't need this much insight into a consumer at an individual level. At the risk of repeating myself, the game is about "actionable data," not "aggregation of data." These are two different business models.

If you are a publisher, data has value; but for a marketer it must meet a cost/value standard. Most wouldn't know what to do with attitudinal data and much less the bandwidth to action on Web behavioral data.

I'm rather excited by all the movement around social marketing and social public relations, since it will ultimately prove my point. Marketers will be drowning in information about who the customers are, their activities, preferences and influence. Some data, but not all, will be valuable. Some will be actionable; some will be monetizable. Your ability to work with third-party data services to access this data around specific efforts seamlessly and cost-efficiently will be the evolution. You just need to decide what data is most valuable to building and optimizing your programs.

The data solutions are evolving; the research services are becoming more affordable and accessible. Your operation will need to encompass this insight and ability to action in order to survive.

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