As AI continues to redefine the marketing landscape, the role of marketers is evolving just as rapidly. From automation to deep personalisation, AI is reshaping how brands connect with audiences in smarter, more impactful ways. To unpack how this transformation is unfolding, FutureWeek sat down with Juliette Aiken, Chief Marketing Officer at customer engagement platform Dotdigital.
In what ways is AI transforming how marketers work today?
AI is really far reaching in terms of channels. It can use data it collects from platforms to re-target audiences on social media and other advertising platforms. Since lots of brands have come online, the market has become really competitive, but it has also been easier for sophisticated types of martech to be adopted. As marketers are having to compete for attention, it comes down to doing more with less, or working smarter not harder. And that’s where AI can help. If you’re a marketer, a lot of your time is devoted to the campaign creation process. AI can then be used for small things which become time consuming, like formatting or editing emails. Our AI engine Winston AI, for example, will look at pools of data to determine what works to get people to engage with content in their inbox. That’s one aspect.
Then, there’s the more data-forward aspect of AI. Looking at data, our own AI agent Winston AI can inform marketers of someone’s predicted next purchase date, or the predicted customer lifetime of a consumer. This way, while marketers build cross channel customer journeys, they can make informed decisions based on what their audience likes. Winston also provides predictive recommendations. It understands audiences and finds lookalike profiles within data that can be retargeted with content and promotions that have worked elsewhere.
How does AI help marketers gain deeper insights into their audiences?
The beauty of AI is that it makes huge pools of data actionable. It helps us, as humans, understand vast amounts of data in a way we can use it to better understand an audience. For us, marketers can access analytics around re-target lists they have created. They can see what types of links the audiences are clicking on, and when audiences engaged with content. They can see if there are particular products that the audience is more engaged with, which they can then factor into the next campaign that will go out to them. There are those surface-level, aggregate insights that can be really valuable in the first instance.
Beyond that, AI plays a part in predictive product recommendations, or collaborative filtering. With collaborative filtering, marketers look at a particular individual and their behaviour. This includes knowing when they have browsed a website, what they have purchased and when. The model goes to find profiles similar to that person, so the recommendations can be more relevant. All of that gets wrapped into a predictive recommendation model, which can be surfaced to the end customer across email, web, and other channels.
Which groups or individuals are best positioned to benefit from AI in marketing?
I think AI can add a lot of value by fast-tracking menial tasks, and helping to develop young, new to mid-level marketers. I think it will help new marketers work more strategically, sooner in their careers. That bodes well for the marketing landscape as a whole.
In terms of personalisation, I think if AI is harnessed in the right way, it should ultimately benefit the end consumer so they are receiving more relevant content. We’re all thinking about relevancy – people want brands to be entertaining or helpful in terms of the content that is delivered. Relevancy is the key word, and I think AI can do a lot for the end consumer on that front.
Where might there be the most disruption in the marketing supply chain?
We work with a lot of brands, and we sell to, and prospect to, a lot of brands who are mid-market or small enterprises. What we increasingly see as we move upmarket is that we get invited to request for information (RFI) processes – brands go out to a selection of vendors with their goals and request proposals.
RFIs are complex because the questions that need to be answered with them span from what the platform does to what the company’s stance is on accessibility standards. Sometimes, there’s a legal and compliance aspect there, and there’s a lot of work that goes into managing what the answers should be. As a business, we’ve started testing out how AI can help us craft a repository we can tap into, so that we have a starting point we can tweak and personalise to the brands who reach out to us.
What do you see as the biggest challenge with adopting AI in marketing?
I think the challenge is with the idea that AI will take over and completely replace humans. The AI and human collaboration is really key. It’s not just key to making sure the output quality is good and authentic to the brand. But from a consumer perspective, consumers like to know that there has been human oversight with content produced or partially produced by AI. I think there’s still an assurance piece as well, that people want to know that they’re not just dealing with a machine, but that there is still that human touch.
What excites you most about the future of AI in marketing?
As a marketer, I am most excited about AI helping us get back to the most creative versions of ourselves. For example, we use CoPilot internally, and it almost becomes an extension of our ideation sessions and brainstorming capacity. We’re seeing really fun, interesting conversations come off the back of that. It also helps us reduce the workload of admin-heavy tasks that are always prone to human error. This means we can spend more time being not just strategic as marketers, but also creative, which ultimately feels like a full circle way for AI to come back and help us.
