Marketers are all far too aware of how their job scope and responsibilities have grown and evolved over the last few years.

We are no longer responsible for simply interacting with consumers across one or two touchpoints, and that’s because consumers don’t engage with just one or two touchpoints anymore — they engage across a plethora of different channels in a variety of ways, owning their own journey.

Unique

Consumers also have unique preferences, hobbies, habits and interests, and so this should be reflected in the way brands communicate with them. This never used to be possible with the likes of newspaper adverts or direct mailers, where the same message was sent en masse to huge audience groups, but we have recently begun to realise how technology can be used to deliver the level of personalisation that is now expected by consumers.

The benefits of effective personalisation are clear: consumers are far more likely to engage with something if it is written in a way they are familiar with, or mentions something they have an active interest in. This, in turn, can lead to more meaningful and long-lasting relationships with customers, who feel more like they are talking to someone who is helping them, rather than annoying them.

The challenge, however, lies in being able to deliver this level of personalisation across all channels, whether it be e-mail, social media, call center, display advertising or smartphone push notifications. Getting this right involves taking huge amounts of customer data and orchestrating in intelligent ways, and this can be a real challenge, not least because each channel has its own set of unique rules and requirements.

In a bid to deliver effective, hyper-personalised communications across every single channel while simultaneously simplifying the process, marketers are turning to artificial intelligence (AI) as the solution. Based around sophisticated algorithms and machine learning methods, AI technology is already a part of our everyday lives — it powers everything from the voice assistants in our smartphones to Facebook’s facial recognition feature —and this is now expanding rapidly into the marketing sector.

Because of the number of factors and variables at play, AI is able to perform a much better job at converting all of the vital customer data held by companies into actionable customer insights. In fact, machine learning algorithms work better with more data: the more information a company holds, the more complex techniques (i.e. deep learning) they can use to influence their customer journeys, which results in better outcomes. The algorithms can also be used to pick up on complex trends and patterns that might have otherwise gone unnoticed by the human eye, which can lead to an extremely valuable additional layer of personalisation that can further drive engagement and customer loyalty.

AI has certainly proved its worth in these respects. Many companies are now making use of data management solutions — be they DMPs, CDPs or otherwise, but most are limited in how to integrate AI with these solutions.

Specifically, with many data management solutions, AI still relies on separate products and human input to structure and standardise the data it uses. Marketers cannot simply plug raw data into an AI-generated algorithm and expect it to do all the hard work — there are numerous behind-the-scenes processes that must also be factored into the final result, most of which are the responsibilities of data scientists. In order to deliver full personalisation – AI driven customer journeys – it is critical to choose a platform where AI is integrated vs. separate.

The future

Looking towards the future of personalisation, AI will definitely have a huge role to play, but it will be utilised in more sophisticated and innovative ways. Take chatbots, for example: powered by AI, these could take a consumers’ personal interests into account before relaying the most relevant results for a specific question.

An article on the Marketing Society website explains further: “Imagine you are trying to lose weight, for example. You access weight loss tips or diet information online. And you monitor your progress on your internet-connected scales. Then Alexa says: ‘Are you sure about that?’ when, frustrated by a difficult day at work and craving a boost, you ask her to order you a box of donuts or pizza.”

Marketing success in today’s environment is largely defined by the level of personalisation they can achieve in their communications at every touchpoint on the customer journey. Consumers nowadays are far more savvy and aware of common marketing tactics, and so they will be far more likely to engage with a brand that talks to them like someone that knows them, not like they’re just another customer on a list. AI technology has proved successful in making this an achievable goal for marketers, and its role will continue to evolve in the coming years.