12/04/2022
DID YOU KNOW… It takes just 5 factors to predict when your customers will leave you.
And if you can predict which customers are likely to leave your business you can start taking action before it’s too late.
Through your own data, you can easily group different types of reasons why your customer leaves you. Thereby you can target specific actions to their dissatisfaction and prevent them from leaving.
We often spend much more time and money on attracting new customers than ensuring to keep the ones we already have. Maybe it should be the other way around…
A customer you have had for 1 year vs. 1 month is much more loyal and therefore much more robust concerning any dissatisfactions. And therefore, a customer that is worth more.
Based on 1st party data and just 5 factors we can make a strong prediction on when your customers will leave you.
Factors impacting churn:
• Interactions with support
• Changes in basket size
• Billing - Frequency / credit card expired
• Distribution errors
• Lifetime
Predicting churn through these simple phases:
Data: Utilize your 1st party data – easy access and probably data which you are already working on
Modelling: Use a transparent machine learning model - understand which factors affect churn
Testing: A/B test - easy to measure
Implementing: Complete the first three phases, then the implementation is simple
If you would like to learn more about key insights on predicting churn reach out to
Jesper Dam Nielsen, Tommi Grønkjær Christiansen, Kristian Vejborg, Jeppe Thierry Alken at Predictify,
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