The Martech Report 22/23

Martech is more important than ever, and despite a more challenging economic situation in 2022, martech budgets are continuing to grow. The global market for Martech and Salestech is estimated to be worth $508.9bn.

As our latest State of Martech report finds organisations face a number of challenges around marketing technology. The biggest one is finding the skills and talent needed to drive martech initiatives.


How to Design an AI Marketing Strategy

In August 2019, an American Marketing Association survey revealed that the implementation of AI had jumped 27% in the previous year and a half.

Following that, a 2020 Deloitte global survey of early AI adopters showed that three of the top five AI objectives were marketing-oriented.

These three objectives were, in no particular order, enhancing existing products and services, creating new products and services, and enhancing relationships with customers.

What I'm getting at here is that AI is very much at the forefront of marketing's future, so it stands to reason that you should get your foot in the door before it's too late and you're just playing some sort of catch-up game.

So how do you go abut dipping your little toesies into the AI waters? How do you design your very own AI Marketing strategy. Well, somewhat surprisingly...

Don't start with AI

You're going to want to walk before you can run and boy oh boy, you're gonna want to crawl before you can walk.

In this regard, crawling would be akin to using simple rule-based applications, such as customer-facing task-automation programmes. These apps are useful for guiding customer service agents through their engagements with clients.

Now you can think about machine learning

Good new-fashioned machine learning, eh?

Once a company has a decent platform of very basic AI/automation tools and a whole smorgasbord of delicious data on the customers and market, then they can start getting machine learning involved.

An example of perfectly-implemented machine learning would be that of clothing retailer Stitch Fix. Their clothing-selection AI helps its stylists curate offers for customers based on their self-proclaimed styles, the items they previously kept or returned, and their feedback.

To work properly, AI and machine learning apps need a shedload of excellent data, so marketers should turn their attentions to the likes of internal transactions, outside suppliers, and even potential acquisitions.

Time to get some sexy AI-powered marketing

Now you can fully automate a number of tasks and take pesky humans out of the equation entirely... but only for the menial tasks that humans can't really be expected to do.

These tasks involve the repetitive, high-speed decisions - such as those required for programmatic ad buying - where humans can't really keep up and the results of which are almost instantaneous.

AI also extends to suggestion to clients or staff, such as a streaming service insisting that you really, really need to watch The Kissing Booth 3 (whatever that is) or a DXP suggesting a strategy to a marketing executive.

Generally speaking, human-made decisions will probably always be required for certain tasks, so you can't - for now - setup an AI system in your company and let everything run itself.


Sadly, life isn't like that episode of the Simpsons where Homer has one of those table top dunking bird tools running the power plant's Nuclear Safety Console from home. That's real AI.