Today I had a sense of déjà vu as I read about ad-tech startup GumGum’s new social image analytics platform, Mantii, in another industry publication.
According to the article, 85 percent of posts containing a logo include either no text at all or no text relevant to the brand. Mantii looks for all or part of brand logos contained in social media posts, whether they mention the brands or not. I thought of something I’d once read that said when a McDonald’s customer complains, “The coffee was too hot” on social media, the brand often won’t know because the location and store name are not mentioned explicitly.
At the Metropolitan Museum of Art last year I observed that only one of six people who posted to Instagram or Twitter while at the Temple of Dendur actually mentioned the name “Dendur.” A good portion of the posts were almost entirely image-based.
In fact, I came to believe that an over-reliance on textual keyword monitoring tools was actually producing the very opposite of what they were intended for. By “oversampling” for specific keywords and patterns that were obvious, brands were blind to potentially more important signals being routinely overlooked because they could not “see” them, nor could the monitoring platforms.
It turns out that eliminating “data gaps” seems to be the logical next step for many platforms, including Google Analytics, which recently announced vastly improved attribution of customer search responses with TV airings data though tight(er) integration with Rentrak TV Essentials. According to Google, “When a TV or radio ad creates an I-want-to-know, I-want-to-go, or an I-want-to-buy moment in the mind of a consumer, many pursue it online. Immediately – and on whatever screen they have handy.” That was harder to track in Web Analytics – until now.
But it doesn’t stop there. The AirPR Analyst platform, a Google Analytics partner, reports that it can attribute the return on investment (ROI) of brand PR by tracking how many potential customers came to a brand’s website from specific press hits. Then there’s the “data gap” created by website events that are too often untracked by web analytics because they were never enabled in the first place.
For example, Google Analytics has had “event tracking” in place for several years, but many website owners don’t know how to track events on their website or maintain the website tracking they have in place, much less add new tracking to it. That’s where SkyGlu, another Google Analytics partner, comes to the rescue, as the platform can automate event tracking on websites, zoom in on visitor analytics and export and integrate Google Analytics with house databases or CRM.
Let’s not forget the current debate over “dark social” data, which is also not tracked by web and social analytics platforms, and which ways to begin closing that dark social data gap. While Facebook made changes recently to make attribution of dark social easier (being that Facebook is said to be its main source), there’s plenty more to go around.
Putting all of this information in content brings to mind situations beyond the scope or context of convergence analytics (or web analytics), such as the way we individually and collectively interpret the world. Just as many social and web analytics platforms are designed to detect certain “spectrums” of data while being blind to the rest, we only see, or listen to, certain aspects of information (strictly literal interpretations of The Bible or the US Constitution, to name two).
Perhaps it could be said that the limitations of analytics platforms reflect our own limitations. If that analogy holds true, there’s hope that just as convergence analytics is rapidly closing “data gaps” on websites, something similar can help close our own data and belief gaps.
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