A short exercise on predicting or recommending where AI will take marketing in the next two years.
Connected heavily with augmented reality, and more generally with mobile, we’re already using audio fingerprinting, a branch of weak AI, to permit fuzzy identification of audio content. This has been around for a long time in the form of apps like Shazam and Soundhound, connecting music heard over the radio or tv with identification, lyrics, and the ability to purchase – but I’m seeing ever-growing applications to migrate from this relatively passive approach to one where recognition is used to improve the conversion rate of all sorts of traditional advertising by giving the audience a shortcut to engagement by detecting brand messaging in their environment and providing a simple way to answer the call to action.
Thanks to market research, social media, public databases, and so on, we have more information about audiences than ever. The tendency is to think that the always-on future of screens is an opportunity to fill the public’s visual field with ever-present marketing messages. AI lets us avoid that misstep by using our these massive datasets to anticipate who will respond and when, by building models of interest and response, and being helpful rather than intrusive.
2018 will see a spike in apps for mobile, and the year following in digital eyewear, that are able to confidently identify products in the user’s environment. Experimental and novelty AR has previously been based in recognition of specific targets, but Apple’s MLKit sent the message that AR recognition is all about machine learning. With this tool, we can connect marketing efforts to lifestyle like never before, being a consumers assistant instead of just another ad to close.
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