HomeResourcesLove (and AI) will keep us together: how AI and machine learning can help to prevent lapse and churn

Love (and AI) will keep us together: how AI and machine learning can help to prevent lapse and churn

23rd June 2022 - 4 mins


By Lauren Heckman

, Content Marketing Manager

In business, customers lapse and churn all the time. But it’s important to understand the different circumstances a customer can lose connection with your business.

Nobody likes a break-up, but on the plus side there are some great break-up tunes to help make those moments a bit easier (we may have name-checked a few songs in this article).
Fortunately, AI and automation can help you prevent customers splitting up with your brand, so you wont need to reach for the break-up music playlist!
Broadly, we can separate customer break-ups into two categories:

  • those who intentionally walk away from the business
  • and those who get left behind

Both are important to identify and bring back into your customer lifecycle, as new customers are expensive to acquire.
Econsultancy studies place the cost of new customer acquisition at 7x more than customer retention. Loyal customers also spend 67% more than new ones!
But when you have thousands of customers, it’s an impossible task to track manually. Using AI and machine learning, particular behaviours can be tracked and used to make predictions about likely future behaviours.
Women in red waiting for taxi to leave home

Don’t leave me this way: predicting customers who churn

Some customers may walk away intentionally. Maybe they actively cancel a subscription or membership, or they simply opt out of any future marketing comms and start purchasing from another brand.
Once these customers leave it can be harder to win them back – especially if they’ve moved on to a competitor.
This means it’s essential to identify these customers quickly to prevent them reaching a point where departure from the customer lifecycle seems likely – or at least, a vulnerability.
If a customer’s purchasing history shows a marked slow down in frequency or amounts they buy, or those who used to make regular repeat orders of specific items and are purchasing less or have stopped, this could indicate they’re finding alternative products elsewhere – and you could be losing them to another brand.
AI and machine learning can learn from these behaviours and predict those customers who are showing a high likelihood to lapse, enabling you to trigger a suite of comms to re-engage the customer before its too late.
Women boarding train, saying goodbye

Never say goodbye: it’s all about the timing

For any re-engagement comms to be truly successful they need to be timed for each individual customer. This is where marketing automation supported by AI and machine learning really comes into its own.
Timing is everything – and AI enables you to tailor each campaign to each individual customer. A customer who has previously engaged with you frequently should be re-engaged quickly before its too late.
This is especially important in the case of loyal customers. AI and predictive analytics can identify any changes in their purchasing habits which enables you to act quicker and at the time most optimal to that individual customer vs an arbitrary time period that won’t reflect all customers.
A couple hugging and drinking red wine

Let’s stay together: AI in action

Sounds good in theory? Let’s look at it in practice. Growing online cosmetics retailer allbeauty wanted to try and retain a larger proportion of their value customer database.
With more than 150,000 customers, effective comms at this scale could only be achieved by automation supported by Redeye’s AI and predictive analytics, which can identify the customers most likely to churn in the next 90 days.
Applying the predictive churn model onto allbeauty’s customer database identified the customers who were likely to lapse, based on individual purchase behaviour.
This allowed for individually personalised reactivation campaigns to target and convert customers who might have otherwise lapsed.
This is where AI and automation are formidable tools for marketers: as the automation is triggered at an individual customer’s own moment of lapsing – rather than it being left to guesswork!
As a result RedEye helped allbeauty achieve a 414.6% increase in sales and a 518.7% increase in revenue from their lapsing segment, by simply letting their customer data, alongside AI-powered predictive analytics, decide when the re-activation campaign should be sent.

In conclusion: Never gonna give you up 🙂


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About the author

Lauren Heckman
Lauren Heckman Content Marketing Manager

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