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Demographics, Psychographics, Socialgraphics—Uniting Divided Customer Profiles

July 2, 2012 By Patrick Surry
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According to technology research firm IDC, the Big Data market is expected to grow from $3.2 billion in 2010 to $16.9 billion in 2015. Consumers are willingly providing companies with boatloads of personal information. Even with all the data in the world, marketers are still frustrating customers with irrelevant communications. There is a quid pro quo here: In return for giving up information, consumers expect the data to be used appropriately and intelligently. In order to tailor one-to-one messages, huge amounts of data need to be analyzed and applied to deliver accurate information and offers.

Just 10 years ago, sending customer communications was based on trial and error. Mass mailings were regularly sent in hopes that someone would positively respond, starting with a “wing and a prayer” approach and learning as you go. This type of communication evolved and moved toward a more one-on-one communication, in some cases addressing the customer by name in the email or mailing.

Even though some companies have mastered their data, too many are still failing on tailored messages for their customers. Marketing is no longer about one-way communication; it’s about creating and maintaining two-way, mutually beneficial relationships. With the availability of advanced predictive analytics solutions, marketers no longer have to guess. Choosing a list can be calculated and determined by who out of all the customers will positively respond to a particular piece of communication.

A Perfect Pairing
Traditionally, customer data is analyzed by looking at demographics and creating buckets of customers that have the common location, age and gender. Creating lists isn’t a new concept, but over the years, list building and the type of information analyzed have evolved. With so much data being compiled daily and with social media information being added to the mix, it’s hard for businesses to understand how to boil down and create extensive profiles and lists.

Demographics have long been used to create lists, though this can no longer be the sole means of gathering data and parsing customers. It takes more. Looking at the psychographics of a customer will provide companies with a more complete view. Psychographics look at more than just a location, age or gender; they look at variables such as attitudes, personality, lifestyles, interests and values.

For example, knowing that a mom of two children younger than five drives a minivan, shops at a local discount store once a week and likes to use coupons regularly can help a marketer target said mom with the most relevant offers and weekly discounts. What’s more is that there may be several more customers who fall in the same category. Placing these customers in the same list, it is easy to target them based upon the psychographics. Establishing behavior traits like this that suggest an individual target will respond positively to your next campaign can help select candidates who might be very different when viewed based upon demographics.

While psychographics provide a better view of a customer, a new level of data has been introduced, which incorporates social media data—sometimes referred to as socialgraphics—and helps give marketers an even more comprehensive view of the customer. This type of data captures attitudes, characteristics, behavior and motivations of customers online. Since the data from social networks consists of fields, which users grant permission for brands to use, customers have a higher expectation that communications will be tailored to them.

Social data truly brings customer data to the next level and, when paired with demographics and psychographics, marketers have a more complete view of a customer and can build lists that draw on all three to indentify targets who are highly likely to be interested in the offering in question.

The fact that customers can be different in so many ways and yet similar in one critical aspect makes list-building a very complicated process. But understanding how psychographics, social data and demographics play into customer data that is already collected will help tremendously. For instance, if you take a representative set of existing customers, overlay that with the external data attributes and then use profiling and predictive modeling to understand how the overlaid attributes are correlated to characteristics of your very best customers. The learnings can then be transferred across to non-customers or prospects, to make sure that the efforts are focused on those potential best customers—instead, for example, of acquiring a set of new customers that who easy to sign up but will not have a high lifetime value. By using intuitive solutions to access customer data, organizations can achieve increased productivity, faster decision-making and greater campaign profitability.

List-building and selecting the right customers to send communications to no longer has to be a guessing game. Marketers can determine what piece of communication should go to each customer and what each communication should say. By using psychographic information coupled with demographic and social data, companies can save time, resources and headaches and ultimately strengthen lifetime customer relationships.

Patrick Surry, Ph.D., is global solutions owner of customer analytics and interaction at Stamford, Conn.-based marketing software provider Pitney Bowes Software. He can be reached at patrick.surry@pb.com.


 

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