The phrase ‘hype cycle’ could have been invented for the mobile marketing industry. Typically, a new tech’s day in the sun lasts anything from six – 12 months, before the next big thing comes along. Think about Native, Wearables, Programmatic, Augmented Reality and Virtual Reality. All came, all are still very much around, but each has been superseded by the next. And if VR was last year’s big thing, AI (Artificial Intelligence) is this year’s, infiltrating an increasing number of aspects of our daily lives.

In the home, there’s Amazon Echo, the personal assistant which responds to your voice to tell you how your commute is looking, what the weather’s doing, or what’s happening in the news. Whether Echo qualifies as AI in its current guise, however, is a moot point. Ask it something it doesn’t know the answer to and, in my experience to date, it will remain ignorant of the answer, no matter how many times you ask it.

AI chatbots
On a more mundane level, brands are turning to AI-powered chatbots to improve the customer service experience. There are many examples, but as ever, Domino’s is leading the charge, enabling customers to order a pizza via Facebook Messenger using its “enhanced ordering assistant bot”, Dom.

Unilever tea brand PG Tips also went down the chatbot route for Comic Relief day in the UK in March, enabling consumers to donate to the charity and hear jokes from a bot version of its Monkey brand mascot.

Twitter has also got in on the act, enabling brands on the platform to steer the conversation when a consumer starts to send a direct message to them. DM @Tesco on Twitter, for example, and before you’ve written a single character, the retailer hits you with a message thanking you for getting in touch, and presenting you with a list of things you may be contacting them about, from ‘Tesco Clubcard’ to ‘In Store Stock Query’. Talking to an agent is one of the options.

Whichever one you select, you get an instant response explaining what you need to do next. To my mind, it’s one of the least glamorous, and at the same time, most impressive, applications of AI in the brand world.

Last year, ad agency McCann Erickson hired a new creative director, but this one doesn’t do long lunches or knock up scamps with marker pens. Its name is AI-CD and it’s a piece of software that creates ads by analysing thousands of previous TV commercials, in order to, in the agency’s words: “creatively direct the optimal commercial for any given product or message.”

Netflix adopted a similar approach when creating its hit series, House of Cards. As McCann Japan creative planner Shun Matsuzaka explained to Alex Spencer in his recent piece on AI: “All the films and drama series provided by Netflix are tagged. The database is connected to behavioural data, which they had been accumulating over six years. As a result, Netflix became confident that they had a full grasp of the user preference. Therefore, rather than purchasing external content, they thought that they would be able to create better content themselves.

“House of Cards was produced based on an algorithm which concluded, using this database, that a political show starring Kevin Spacey and directed by David Fincher would be a major hit. Even though it was their first original series, Netflix invested $100m – they were that confident – and the show went on to win multiple Emmy awards.”

Personalised search
And the AI launches keep on coming. Sentient Technologies recently launched an AI-powered personalised product search platform for mobile. Sentient Aware for Mobile personalises individual recommendations on-the-fly based on shoppers’ interactions.

It evaluates a shopper’s taps, swipes, and scrolls in an app or mobile site in real time. These actions are interpreted as signals of varying significance and preference for certain styles in the catalogue, and are translated into certain vector values matching products in the catalogue.

The AI then matches these values against hundreds or thousands of vector values in a dimensional “feature space” that represent each product in a retailer’s catalogue. The closer a shopper gets to what they like, the stronger those signals get. These signals then allow the AI to narrow down to precisely the product features and vectors that the shopper wants in just a handful of taps and swipes. The AI can also pick up on nuances and a user’s unspoken preferences in case shoppers want to explore a different path.

And just yesterday, location-based advertising firm Blis unveiled Blis Futures, which it claims is the industry’s first AI-powered mobile advertising solution.

“Using proprietary deep learning technology, Blis Futures is an AI-powered, predictive location modelling solution,” the company says. “It identifies consumers most likely to visit specific locations, then provides advertisers a guarantee they will only be charged per consumer visit.”

And so ‘cost per visit’ takes its place in the digital advertising vernacular, alongside cost per click/download/completed view et al. Stella Artois is the first brand to run a campaign using the tech, with the aim of driving drive customers into pubs, increasing engagement and inciting them to buy.

Is AI for me?
The key question, of course, is whether, as a brand, you should be piling into AI. At the risk of stating the obvious, the answer, as ever, is not to get fixated with the tech, but to look at your own business problems and see if, in its many guises, AI might offer a solution.

If your call centre is overrun with enquiries, most of which fall into a few easily-definable categories, then a chatbot may well do something to improve the customer experience, and reduce your costs at the same time.

If you have an inordinate amount of campaign or customer data at your disposal, then an algorithm that can crunch it to deliver trustable insight into what your customers might want from you next is obviously worth exploring.

But please, don’t just obsess over the latest piece of cool tech and jump on the AI bandwagon, only to jump off it again when you find it was no good for your brand. There’s a reason why, in most cases, the products and technologies that find themselves in the hype cycle don’t tend to stay there for very long.