The Everest before Digital Advertising
Facebook, Google and probably Amazon store,everything you do in the digital domain. But any marketer who believes that true ad relevance is ever achievable should take a hard look at how the sites and apps they use classify them as individuals.
Here is what a report from the Pew Research Center has to say about the process by which companies figure out what site users might be interested:“It is clear the process of algorithmically assessing users and their interests involves a lot of informed guesswork about the meaning of a user’s activities and how those activities add up to elements of a user’s identity.”
The report details the results of a survey focused on Facebook’s categorization ofindividual’s interests as represented by their “Your Ad Preferences” page. Not surprisingly, 74 percent of Facebook users did not even know the page existed but when directed to it 51 percent stated they were not comfortable with how the site categorises them, and 27 percent thought the categorization inaccurate.
For instance, the fact that I clicked on the advert or message by a University online does not mean that I am automatically a good target for MBA programme organized by the institution. Kantar studies show total consideration should be given to the clickers total personal information which can be sourced before targeting the prospect. Therefore, it would be more meaningful to know the target before shooting the marketing communication darts.
Most of the categories are less than ‘informed guesswork’ and mere literal interpretation. This problem of incorrect inference applies to all the data collected, including the behavioural data gathered from your mobile telephone and other sources. Most of the categories are less than ‘informed guesswork’ and are mere literal interpretation.
Take for example, the fact that I liked a page about Manchester United (my son’s club) do not make me a Man United fan. What the system may not know is that I visited the website to harvest a few talking points to ensure a I have a meaningful discussion with my son who is a dedicated follower of the Manchester Club. This problem of incorrect inference applies to all the data collected, including the behavioural data gathered from ones mobile. If we do not know the potential client well how do we serve him better?
Recently a colleague gave this hypothetical example of how geolocation can go astray, “According to my mobile’s location data I am a regular at the gym. I spend half an hour there twice a week, and therefore see many, many ads for protein powder targeted at gym regulars. But my gym could be right next door to a donut shop, and I could in fact be stuffing my face with donuts twice a week.”
I have no doubt that behind the scenes Facebook, Google, Amazon and other stakeholders can create a far more detailed and accurate profile of my behaviour and interests. The data is all there to be used. If an advertiser really wants to serve me relevant ads they should be taking all this information into account. But how many really do? From what I see, most simply take the basic classification and run with it.
But what do you think? Is true ad relevance ever achievable? Please share your thoughts. Michael Umogun / Michael.Umogun@kantarmillwardbrown.com / 08023117969