For the past couple weeks, I’ve seen various places broadcasting this article to me that Facebook has missed the boat.
What if they are really missing the boat?
I've been following Marty Weintraub of AimClear's brilliant thoughts on Psychographic targeting for a while and have recently begun wondering why there is no pass-through data from Facebook to websites, back to Facebook and other places, improving the conversion process every time.
In other words, why doesn't Facebook provide pass-through analytics to websites that tell site owners what type of visitor is visiting their site? What other types of things do they like? Are they male or female? What's their age range? Liberal or conservative? Single, engaged, married? The list goes as deep as the data on Facebook.
Who Likes Sioux Falls and What Do You Do With That Information?
Facebook has all sorts of mineable data that's easily available to people who know where to look. For instance, Optimal Social tells me that people on Facebook who like Sioux Falls also like Minneapolis-Saint Paul, Des Moines, and North Dakota. Those make sense.
However, Optimal also tells me that people who like Sioux Falls also like LaCrosse, Wisconsin and #Plymouth. Despite the fact that Optimal leads me to the community page for Plymouth, England, I'm going to give Optimal the benefit of the doubt and assume that people who like Sioux Falls also like Plymouth, MN, which makes a little more sense.
Now, why are we seeing LaCrosse and Plymouth show up? Do Sioux Falls people like LaCrosse for a specific reason? Perhaps the better question is, would people from LaCrosse and Plymouth like Sioux Falls? Would they be looking to move here? Vacation here? Do business here? A trial-run ad campaign targeted to LaCrosse and Plymouth to attract people to Sioux Falls could make sense from this data.
Facebook has an outstanding opportunity at this point. If they were to come up with their own analytics platform, and tie in user actions with user demographics, website owners would now be armed not only with what people do on the site but the persona of who they are.
How Could a Large Business Use This Type of Analytics Platform Data?
In the case of a large business (with a larger sampling of mineable data), Target for instance, the web analytics team at Target could see that 90% of people who like Target are female. Optimal pulls Facebook's data and tells us this is, indeed, the case.
However, how many of those people that actually visit Target's website are female? Target could then see a certain percentage of people who visit like The Children's Place, Bath and Body Works, and Cheesecake Factory, and the average age of these particular visitors is 32.
What if Facebook's analytics platform was able to provide conversion funnel data according to these user personas? It's obvious that those who like The Children's Place will be buying children's items, but what else do they tend to buy? Party Supplies? Lamps? Rugs? What about those who like the Children's Place who are in their 20s vs. in their 30s? Do those who like Bath and Body Works buy beauty supplies online or tend to buy in-store?
What about those who like the Cheescake Factory who are coming to Target's website? That gets a little trickier to attach a persona of those people just by guessing, but Facebook's data would show you exactly where that type of person is traveling in the conversion funnel. 90% of people who like Target are female, but what types of products are the guys looking at?
Improve The Funnel and Improve Conversions
Post-funnel analysis would show the marketer exactly what type of people buy certain products, arming them with better targeting data to use for their next campaign and logically seeing a large increase in conversions because they're targeting the right people.
Google seems to be on the road to this sort of analytics with Google+; the problem is that they're lacking information. Facebook has this information. For those of you wondering about privacy issues, Facebook could do the same thing it's currently doing with Custom Audience targeting and mask any user data that is passed through. If done right this could be a major win in Facebook's business offering arsenal.
