Churn prediction refers to two main concepts in marketing analytics. The first is predictive modelling to estimate the likelihood that a customer may churn. The second is done through time-series forecasting and regression analysis to project the future churn rate for a group of customers defined through segmentation analysis.
It is well known that it is far costlier to acquire new customers than to accommodate your existing ones. For the best results it is recommended that data is pooled from several sources. For example customer purchase history, call center transcripts, social media, location data, etc.
Quanovo can provide you will a prediction system that has been created firstly by analysing the data you already have and then by incorporating new data as it is created. This model can then be used in whatever way your business would find most useful. For example, it is possible to create a web service that can alert your business if a customer is showing high levels of potential churn, thereby allowing you to take the appropriate preventative steps. Using the model in this way can help you transition from being reactive based to proactive based with your customer strategy.
Often it is the case that being able to predict the likelihood of a customer churning can be of great value to increasing the efficiency of marketing campaigns. Maximising the return on investment by offering discounts or other incentives only to customers that have a higher potential to churn.
Not only can your business save money but churn prediction can also improve your reputation as a company that does not simply spam its customers but rather as one that has built a relationship and understands its customers as individuals with specific needs.
Being able to forecast the churn rate for a specific customer segment or across your customer base can help identify areas of your business that are a major factor in churn rates. For example product pricing or product packaging.
Knowing in advance what your major causes of churn are can help you with strategic planning in your business. If you are thinking about introducing a new product or altering the your business practices then Churn Prediction can help model what their likely impacts will be for churn.
When subscribers jump from provider to provider in search of bargains. It is far costlier to acquire new customers than to accommodate existing ones.
What is the leading cause of your customers churning? Common causes include high prices, poor service, new competitors and outdated technology.
Use real time analytics to process current usage statistics and target customers that are heading towards churning.
Predictive analytics based on previous data and current patterns.
Make use of Sentiment Analysis to understand customer views.
Change is noticed earlier and so can be dealt with in a proactive manner.