Collecting data and handling purchase signals is straightforward, context is another matter entirely.
In his book, The Circle, Dave Eggers frightened all of us with his story of the AI-powered surveillance that went on to become a Hollywood movie adaptation starring Tom Hanks and Emma Watson. These tales are always scary because science fiction has conditioned us to expect machines to overrule us in every aspect of our lives – even marketing.
There is logic in this belief. Machines have already replaced some aspects of marketing and made it more efficient. We’ve seen how online algorithms implemented by Google ads have simplified the process of gauging purchase intent and predict when potential buyers are ready to make the purchase. Machines do very well with handling purchase signals, but they aren’t quite as adept at understanding the context that surrounds the buyer’s perceptions and motivations.
Context helps create meaningful brand experiences
Context helps you understand buyer motivations. For example, a consumer might be searching online for signs of a failing storage drive or searching for bargain deals for lightweight PCs, and this will point Google to the signal that this consumer is in the market for a new computer. The question now is what kind of computer will Google show in their ads?
Google might have further information about the consumer such as where he works (let’s say a tech company), where he lives (let’s use a creative hub such as Austin Texas) and these pieces of information will point to a Mac. But what kind of Mac? If Google digs deeper and sees that the consumer often searches for good rates when traveling on business, Google will decide to present travel-friendly options in the ads.
While a new MacBook will sound great to most people, you have to factor in brand preferences when marketing stuff to them. Not everyone is an Apple guy. Some people are loyal to other brands, and this crucial piece of information is perhaps the most important when presenting ads. If this is overlooked, none of the purchase signal matters and the ad will eventually be a waste of time. If advertising algorithms can’t even display the best ads, how can we expect AI technology to run a full marketing campaign successfully?
Where the Challenge lies. More context
Machines processing and interpreting data and signals are still essential, but there needs to be a way to inject more context about buyer’s brand loyalties and whether or not they can be swayed one direction or the other. These machines also need to be equipped with a means of defining what experiences ought to be created to reach consumers that are willing to listen to your message.
Machines are quite capable of providing data that can aid marketers in reaching prospects that are already in the market. They can also provide steer micro-decisions to the most efficient way of running campaigns. What they lack is an ability to create highly personalized brand experiences that will hold the attention of consumers.
To effectively market products to consumers, there needs to be an understanding of their current state of mind and past experiences with your brand. This is why marketers still do a better job of developing meaningful experiences that lure prospects further down the funnel and a step further from just awareness to actual consideration.
Artificial Intelligence is the future
At the most basic level, context is just another form in which data can be represented, and a future where machines are capable of understanding customer motivations and perceptions is not far off.
Let’s say you decide to launch a new campaign that reassures your customers of your commitment to them. Utilizing a model that takes a deep dive into online behaviors via browsing history, searches, and social media interests, artificial intelligence will probably be able to tell you which customers are more likely to leave and thus require more attention.
Ultimately it will still fall to a human being to answer the question of what experiences need to be created to effectively reach the customer about to jump ship.
There are so many things to consider especially when it comes to privacy and data gathering. With Facebook alone, if likes and dislikes, time and place of interaction with content and friends’ interests were made public, then suddenly machines will have that extra ammunition of context to work with.
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