Tuesday 2¢: Is AI an Intelligent or Artificial Prediction for 2018?

With each new year comes a fresh set of reflections and predictions, and if you cast your browser around the online marketing press, pundits and analysts, it seems that Artificial Intelligence (AI) comes top of the list for 2018.

  1. chevron left iconTuesday 2¢: Is AI an Intelligent or Artificial Prediction for 2018?
Ian TruscottJanuary 2, 2018
  • Technology

Welcome to the Tuesday 2¢. It’s Tuesday, the weekend is a distant memory and it’s time to let off some steam and give our 2 cents on a hot industry topic. This week Ian Truscott confronts the hype surrounding Artificial Intelligence and its predicted role in marketing over the year to come.

Happy New Year! With each new year comes a fresh set of reflections and predictions, and if you cast your browser around the online marketing press, pundits and analysts, it seems that among the regular predictions of “big data” and “knowing your customer”, Artificial Intelligence (AI) comes top of the list for 2018. But, should AI sit at the forefront of our new year’s resolutions? Or, like so many predictions in this industry, is it just a bubble of hype which will be pricked by real world experience?

Back in August 2017, City AM reported that Gartner rated Artificial Intelligence and Machine Learning to be at “peak hype”. Hype which, I believe, is fuelled by the liberal sprinkling of the Artificial Intelligence fairy dust over a wide range of machine enabled marketing processes, from the simplest decision trees, personalization rules, algorithms that identify images, and automated text tagging, to the advanced natural language processing which enables you to have a conversation with a bot which would pass the Turing test.

However, there is a danger in this. In a stark warning to technology buyers, Ben Davis, editor of Econsultancy, recently expressed in this article in Marketing Week that:

Artificial intelligence is reaching the top of its ‘hype cycle’, but the term is often misused leaving marketers at risk of handing over cash for solutions that do nothing new and offer little value…

If you are familiar with the Gartner Hype Cycle, you’ll know that what follows this inflated peak is a steep dive into the trough of disillusionment before a technology crosses this chasm to being adopted as truly useful (on the ”Plateau of Productivity”). So, when taking Ben’s warning and this model into consideration, should we ignore AI for now and instead wait for the hype to blow over?

However, all is not so clear with where AI sits in the Hype Cycle, as it’s being applied to such a wide range of technologies and use cases which are not all at sitting at Hype Peak. So yes, the term “artificial intelligence” is over hyped, but with the right application it can be a sound productivity technology for today. I like the phrase that Ben Davis refers to in his article; perhaps for now we should think of AI and Machine Learning as “automation-plus”, an evolution of marketing technology and not the revolution the hype suggests.

So, if we decide that there is something in this AI thing, beyond the hype for 2018, where could we use it?

Making Sense of Big Customer Data

The AI conversation focuses around the other recent perennial prediction for recent years: Big Data. Machine Learning requires a lot of data in order to identify patterns which it can learn from. If your marketing automation database could fit onto a single spreadsheet, then there is probably not much information to go on. If AI technology can get its insight from a big data set which can be applied to your little one, however, then this could be useful. For example, I was chatting to an email and marketing automation vendor, and as a cloud solution they are using machine learning on the anonymized data set from all of their customers to deliver insights into optimizing email subject lines and potential open rates for individual clients – insights which couldn’t be taken from their own smaller data sets.

Making Sense of Big Content

Forrester analyst, Ryan Skinner, refers to this as Content Intelligence, to use these algorithms to make sense of big sets of content and to automatically understand the meaning of content so that it can be tagged and therefore delivered to a more relevant audience. I like this; in an industry that for a decade has been fixated on understanding the audience, it really is time that we understood our content so that we can deliver something of value to them (now that we know who they are).

Making Sense to Your Audience

The obvious example is personalization, not a new technology but the practice of getting relevant content in front of the right audience which is becoming more sophisticated and being described as AI. There is also a lot of chat about allowing the machines to create content, based on big data insights into what we interact with. This isn’t necessarily new, we already have algorithms which rate content for SEO, help with readability and grammar and I shudder at the idea of machine written articles (I don’t even like ghost writing), but AI can help create the small promotional bits around the content such as email subject lines and - this article from the Content Marketing Institute describes some good examples.

I have barely skated across the surface of this big subject, but hopefully I have answered the question of whether AI is an Intelligent or Artificial marketing prediction for 2018. The term is over hyped and over used, but underneath there is some real technology here as an iteration of what we’ve used before and is worth paying attention to this coming year.

Ian Truscott
Ian Truscott has a passion for creating ART (Awareness, Revenue and Trust) for B2B software companies as a marketing leader and is a censhare alumni. Wanting to connect a like minded community and share something useful, he founded Rockstar CMO, a monthly digital publication, and is currently helping B2B companies create ART at appropingo.

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