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8 Best Practices for Collecting Data from Social Networks

June 30, 2010 By Heather Fletcher
Stick it in a histogram or plop it in a pie chart, data units mined from social networking sites often can be more difficult to categorize than the usual demographic information direct marketers collect in their data mining expeditions.

That might be due to the fact that the psychographic data on those networks involves a bit more finesse to understand than simpler facts such as Prospect A lives on Avenue Q. Sometimes, social networkers might even be maintaining fake profiles—without a smidgen of factual information about themselves, warns Jeff Williams, data analytics team director at Wayne, Pa.-based direct marketing agency DMW Direct.

Keeping that minefield for data mining in mind, social networking sites are still replete with veins of consumer-insight gold. Marketers should extract that treasure, but carefully, say DMW's Williams, Rich Grosskettler, interactive services director and Katrina Zubey, data analyst; as well as Dylan T. Boyd, vice president of sales and strategy for Portland, Ore.-based e-mail marketing firm eROI; and Kent Lewis, president of Portland-based search engine marketing agency Anvil Media.

The quintet provides direct marketers with eight best practices for collecting data from social networks.

1. Respect social networkers' privacy, even if their profiles are publicly visible. Opt in or double opt in is always best, says Lewis, "So people know what they're getting into. So, for example, if I wanted to harvest my Facebook or LinkedIn or Twitter profiles to gain customer insights, I would want to have some sort of disclaimer about how I'm going to be using the data somewhere."

Williams says social networkers are often so honest in their profiles because they have an expectation of a certain level of privacy. While the information disclosure benefits marketers, he suggests marketers mainly interact with people they know or use information without names and identifying features to create pictures of their ideal customers.
 
2. Use the data to create prospect profiles. Williams suggests that marketers collect aggregated, anonymized data to understand what consumers like or dislike about a particular product or service. Then an offline campaign, employing a list from a data solutions firm with good penetration at the individual level, can help marketers leverage what they learn online where they formulate "strategies and get an idea of what the typical person looks like and where they are, psychologically speaking," he explains.

While the most obvious source of this social media graph data may be Facebook, Lewis points out that YouTube viewers and video uploaders can find plenty of data by simply clicking on the "views" button and expanding it. For instance, for a video that he uploaded in 2006, "Big Gun Recoil—Test Firing Middle East Version," its more than 267,000 views came from 25- to 44-year-old men from the United States. (Lewis adds that more information is available about the people who commented and were YouTube subscribers. Many video commenters also include Twitter in conversations.)
 

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