Evan Schuman's StorefrontBacktalk

Making this situation much more problematic is the absence of a reliable means for determining true influence. Asking people how they came to be interested in the product they are buying is fairly useless.

Most won’t bother to answer truthfully, and many more won’t actually know. Their kneejerk response might be, “I liked the colors/price/functionality,” which is almost certainly true. But they won’t add, “What got this on my radar at all was when my friend wrote about it on her Facebook page, which I found because she also tweeted about it.”

One reliable method of determining influence is to create very targeted campaigns on, let’s say, Twitter and see who shortly shows interest in it. But that marketing approach simply misses the point of social media. The influence referenced above in the kneejerk response example was exclusively based on the relationship the customer had with his/her friend. It’s a personal referral sale. Had it been a tweet or a Facebook post from a retailer or manufacturer, the influence would likely be far less. Regrettably, this stuff has to happen organically for it to have the huge impact on sales that it has.

RichRelevance’s chief marketing officer, Diane Kegley, concedes the challenge based on her own company’s report.

“It seems like some merchants have Twitter as part of their marketing value chain, but quantifying the return on that specific kind of behavior is problematic,” she said in an E-mail. “More generally, it highlights the need for merchants to correctly understand attribution. While we would like consumer behavior to be the result of simple cause-effect chains, we know—in no small measure from our own personalization algorithms—that it is, in fact, much more complex.”

Complex is just one small part of it. “Complex” suggests that a sophisticated enough algorithm could crunch the data and expose all of the social influence, while “impossible to quantify precisely” is probably closer to the sad truth. But the more solid part of this report—confirming that social site buyers (on those rare occasions when they can be identified)—makes clear that this problem must get figured out. The potential dollars here are huge.

“When we factor shopper intent into the equation, the fact that Twitter users generate higher [purchase values] makes sense. Twitter users—similar to Facebook users—are not generally researching or completing purchases. A Twitter user, however, might see a tweet from a friend or an ad from a retailer and get pulled into a retailer’s Web site. This spontaneity, combined with influence from word of mouth or an ad, can lead to a higher average order value.”