Revenue Churn, how to minimise it with Artificial Intelligence

The relationship between companies and consumers holds a central position in today’s market, which is increasingly marked by horizontal and two-way communication between users and product and/or service providers.

For this reason, modern companies must be able to set up a process that is capable of attracting and transforming consumers into customers in the first instance, and then capable of retaining them to the brand once they have been acquired.

The customer acquisition phase is not everything in fact, because it represents an impromptu action that can sometimes be done without even a thorough analysis on the part of the consumer. Loyalisation, on the other hand, is much more complex and, if conducted in the best possible way, allows the company to improve not only its revenue, but also its image in the market, positioning itself as a solid company capable of keeping its customers attached to it.

We have already talked about customer churn here. Here we try instead to focus on Revenue Churn, which is slightly different, but still very important to know and to analyse.

Revenue churn represents the amount of revenue lost in a given period. This does not necessarily mean that you are losing customers, but that you are not gaining from your customer base as much as before.
This can happen if customers switch to a subscription or a cheaper version of your product. While they continue to make purchases from your company, they spend less money than before.

This can happen for a number of reasons, such as new competitors providing services at a lower price, or difficulties customers have experienced along the onboarding process at your company. Or, along the constant process of customer loyalty to the brand, one is getting a few steps wrong, conveying the wrong image that pushes the consumers away from the company.

This stems, in most cases, from a wrong analysis of customers, which does not take into account the complexity of their needs and requirements. In order to remedy this shortcoming, companies must rely on innovative and technological solutions capable of analysing their customer base in depth, providing a comprehensive overall picture of the situation that allows them to put in place strategies capable of limiting the haemorrhaging of customers and revenues. In other words, we are talking about Artificial Intelligence.

But how can you implement artificial intelligence within your company?

With BigProfiles, which provides its customers with an easy and intuitive artificial intelligence platform capable of analysing huge amounts of data in a very short time, suitable for both experts in the field and those with no knowledge of coding.

Thanks to it, the data scientist team, together with operations and marketing, will be able to predict the behaviour of customers within their CRM and set up models accordingly, in order to map out the best possible strategy to achieve their retention, acquisition, cross-selling or debt collection goals.

Would you like to learn more about how to implement BigProfiles within your company and start harnessing the power of Artificial Intelligence?

Fill out the form below and request a free demonstration with one of our consultants!