Demographics, Psychographics, Socialgraphics—Uniting Divided Customer Profiles

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.

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