One of the biggest buzzes of 2015 turned out to be the ever-maturing rise of Artificial Intelligence, Machine Learning and Bayesian Networks. It’s always been there, it’s not a new paradigm, but we really saw it starting to become a more explicit component of technical grade projects for banks and insurance companies.
There has also been a huge amount of interest in its future uses to enhance and improve consumers’ lives in areas such as help and support. If every company used or created their own version of Siri or Cortana, we’d see pocket assistants able to solve so many common consumer issues. The implications are huge.
But what about the implications for digital marketing? With ever-evolving technology and the need for better connected thinking and omni-channel communication, it’s going to become imperative for any contemporary business to use a more reactive, intelligent set of systems for communicating with customers. Customers are also becoming more demanding, more selective regarding who they give their attention to and more easily agitated by poor comms. Smart communication is not just good for business but crucial to win hearts and minds.
Artificial Intelligence Marketing (AIM) is a form of direct marketing leveraging database marketing techniques and AI which makes the reasoning part of the outbound communication to be performed by computer algorithm instead of humans. AIM predominantly gives digital marketing teams a set of techniques that enable incredibly powerful behavioural targeting. It also gives us the ability to suddenly start joining up often-disparate departments within an organisation.
The basic AIM principle is based on the 'perception-reasoning-action' cycle you find in cognitive science. In a marketing context this cycle is adapted into the Collect, Reason and Act cycle;
• Collect - All the activities, which aims to capture customer or prospect data from across all their omni-channel actions. Whether taken online or offline these sources of data are then saved into customer or prospect databases.
• Reason - This is the part where data is transformed into information and eventually intelligence or insight; artificial intelligence and machine learning in particular have a key role to play.
• Act - With the intelligence gathered from the reason step above you can then act. In a marketing context, act means some sort of communication that would attempt to influence a prospect or customer purchase decision using an incentive driven message.
Let’s look an example of Collect-Reason-Act in motion: Welcome to the bank of the future that knows what conversations a customer has had in a branch or directly with a member of staff (yes, people exist in the future!) Using the information collected during that conversation they are able to pipe the intelligence to a central, single view of the customer that the call-centre staff are also able to use so they can have a more intelligent conversation should the need arise.
Similarly, that single-view-of-customer data can be piped into the communications database so any outbound messages and push notifications can include the context of the customers’ needs, fears, worries or actions.
Artificial intelligence has a role to play at every stage. Ultimately it’s an unsupervised additional member of staff that can take the decision and act accordingly to the information it receives at the collect stage - but on a vast, almost unlimited scale.
Many online users and advocacy groups are of course concerned about privacy issues surrounding targeting of this nature. This is an area that the behavioural targeting industry is trying to minimize through education, advocacy and product constraints to keep all information non-personally identifiable or to use opt-in and permission from end-users (permission marketing).
But we can’t ignore the fact that beyond the economic implications of automation, it also provides all industries with a much quicker, more scalable model for marketing and managing customer relationships. In the bank example above, the customer could be receiving targeted messages helping them benefit from the branch conversation within minutes of walking out of the building.
It doesn’t have to be creepy or intrusive if it’s done sensibly either. It could provide consumers with a much greater quality of communication by better diagnosing their needs and personalising every message to a level of accuracy that makes marketing the conversational style we crave from our relationships.
By Pete Trainor, founder & director of Nexus, the Human Centred Design company.
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