Visma Software is part of the Visma Group of Companies, which has 900,000 customers spanning 12 countries and services in five distinct business areas.
The objectives of this project were on two different levels.
First of all, we wanted to analyse and predict the probability of both churn and buying.
Secondly, we wanted to get to know the factors, processes and variables that influence churn & buying probability the most so that we could influence event outcomes effectively, either by preventing churn or accelerating buying.
According to a Harvard Business School report, a five per cent increase in customer retention rates results in a 25 to 95 per cent increase in profits.
Visma marketing team wanted to identify customer behaviour before churn and enhance their own activities to prevent it.
The team wanted to be more precise about creating offers and identify the need for training, webinars or other services to keep customers loyal and even increase purchases.
Churn is one of the most demanding predictive analysis operations from a data requirement point of view when it comes to marketing.
Our machine learning-fuelled analysis revealed that the metrics most significant for churn prevention are:
- Interactions with content produced by the marketing team
- Power user detection and engagement
- Support engagement
- Partner preferences