Predicting Customer Churn

Understand your churn

Sometimes customers leave your service and therefore are seen to have churned. For SaaS companies in particular, churn is the among the few key drivers of business success or failure. This may not be as obvious as a closed account, however, with E-commerce companies having large volumes of ‘zombie’ accounts in their databases. Many organisations track the retention of different cohorts to better analyse growth activities and business success metrics. Yet, among the most difficult questions that still faces customer centric organisations are the questions surrounding the ‘why’. Why did the customer leave? Was this inevitable? Could we have predicted it? And therefore prevented it?

When the cost of acquiring a new customer is often estimated to be up to ten times that of retaining an existing customer, these difficult questions are worth putting under the microscope.

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Prevent your churn

Utilising advanced machine learning and statistical modelling, we assist you to analyse and be better able to answer these difficult questions. By analysing your customers’ behaviour in detail, we help you to;

  • Understand and visualise important metrics such as customer retention, lifetime value and cohort analysis. To enable proper self-service reporting, setting up proper data infrastructure may be needed.
  • Utilise predictive analytics to identify the most at-risk customers so you can step in and retain them.
  • Understand the driving forces behind customer retention and churn so that you can interact with their customers in a way that maximises satisfaction and reduces the risk of losing them.