AI in Marketing: Where Does the Value Come From

AI in Marketing: Where Does the Value Come From

AI creates value by enabling us to do what we already do today, only better. In this post, we’ll look at how AI can help marketing excel across the different stages of the customer lifecycle:

  • It enables us to attract more and better customers
  • It ensures we don’t miss opportunities to grow customer value;
  • And it helps us retain the customers who are worth keeping.


Acquisition marketing is often highly inefficient: we market to the many but sign up relatively few. AI adds precision and efficiency; we can be much more focused, spending less money and effort to achieve more.

Though we have much less data about potential customers compared to actual ones AI algorithms can learn, for example, the most promising sources of customers, and what will best persuade prospects from each source to sign up. It can identify the best profile (based on publicly available data) to target in a particular channel and select prospect-matched offers to maximise interest and conversion.

AI can also analyse the journey a prospect takes, from initially seeing our information, through exploration of our website and on to initial purchase. Intelligent systems can spot early in that journey that a prospect is the right “shape” to become a customer and trigger proactive guidance that steers them quickly to conversion. Smart systems can also identify paths which lead to prospects “dropping off” the website – abandoning their search (or even baskets), or simply jumping to external pages as they get distracted or lose interest.


Once customers are on board, they generate copious data that can be used to understand how best to handle them as individuals. As well as any demographic information they declare, patterns become visible in their behaviour – how they buy our products, and in some cases how they use them. AI learns to recognise the signals that a customer is ready to buy more. That might be by identifying replenishment cycles – how frequently each customer repurchases more of the same product (or a similar one).  Or, from “basket analysis” of purchases, knowing which additional associated products are likely to appeal. Share of wallet analyses can provide clues that our customers are spending money elsewhere and suggest which offers might help us take additional share. And when a new product is launched, AI can recognise – based on past behaviour and predicted preferences – which customers it will appeal to, and how best to pitch it to them.

Value growth also comes from up-selling: recognising when a customer is ripe to upgrade to a premium product. AI can identify the profiles of those with the potential to spend more, or spot those whose behaviour is changing with a similar trajectory to those who previously went through the upgrade process.


The natural response to losing customers is… panic! Customers are leaving! We need to staunch the flow!!

It’s easy to find ourselves spending money and marketing effort on desperate attempts to “save” anyone who might be at risk of leaving. But with its deep insights and ability to predict, AI can ask, for every potential leaver: Are they really at risk? Are they worth keeping (not just from past or current spend, but based on predicted lifetime value)? Can they be persuaded to stay? And if so, what offer would be most effective in turning them around? Based on that level of knowledge, AI can coolly assess all our potential leavers, and decide what actions to take, towards which customers, that will use our retention spend most effectively and produce the best possible results.

 As we’ve seen, there are wins to be made in each lifecycle stage. Where AI can help you get really smart, though, is joining up insights about customers and applying them acrossthe phases of the lifecycle. For example, AI can learn the profile of customers showing highest growth and apply that in your acquisition marketing – so you don’t just acquire more customers, you acquire customers with greater value potential. And if customer loyalty is found to be strongly associated with particular products purchased, offering those products to more customers might reduce potential future loyalty issues.

We all know the key to value is to maximise customer engagement throughout the customer lifecycle. AI lets us take the right actions, at the right time, for each customer, and that enables us to get the maximum value out of our customer base as a whole.

Author: Colin Shearer





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