How to Predict Customer Churn in B2B with AI
For businesses selling ad-hoc, it's hard for companies to predict customer churn. That is in contrast to as-a-Service subscription-based businesses for whom identifying at-risk customers is more accessible right from the initial sign-up.
SaaS businesses benefit from constantly updated, deep, live client usage statistics in the free trial and beyond when they become subscribers. They build AI-based churn prediction models on historical data tracking how often clients log in and what features they use.
Read more
How to Define and Reduce Customer Churn in B2B Sales
Customer churn in B2B refers to a portion of subscribers or contract customers who change suppliers during a certain period of time. In B2B practice, some churn goes unnoticed for a long time or is only detected when it is already too late.
Have you ever wondered how you can reduce the likelihood of churn and target B2B loyalty programmes?
Read more
Retain Customers with Artificial Intelligence - Churn Prediction
Reduce customer churn and attrition with Qymatix Predictive Sales Software.
How to Win Back Lost Customers in B2B
Joachim Meyn has many years of experience in B2B sales and customer management. In this article, he shares his impressions on the topic of "customer recovery".
First of all, losing customers is an entirely normal process. Therefore, one of the reasons to conduct systematic new customer acquisition is to replace these departing customers.
However, you should remember that it is about 10 to 11 times more expensive to acquire a new customer than to retain an existing one. It is therefore advisable to devote a certain amount of effort and resources to customer retention. But what happens when it is already too late?
Define and reduce customer attrition in the subscription industry
What is customer attrition in the subscription industry?
What is an average churn rate? B2B companies can expect an average annual customer churn rate of around 11%, a recent study found.
This cancellation rate fluctuates between countries and industries. Customer attrition can represent a 24 % average in office supplies, 16 % in the insurance industry and 13 % in banking.
Predictive Analytics to Understand Customer Behavior in the B2B Sector
For some B2B companies, predicting customer behavior is like guesswork. Managers sit together and try to make predictions about upcoming sales, future pricing or appropriate customer loyalty measures.
Often these forecasts are based on sales reports, sales representative’s own gut feeling and, Excel analyses created with a lot of frustration. Don't get us wrong, the gut feeling of an experienced sales team can very often be right, especially when it comes to customers they have had a lot of contact with. But what about all the other customers?
Predictive Sales Forecasting: Answers to 5 Questions of Salespeople
Why should we use predictive sales forecasts in sales? This article is aimed at anyone thinking of using AI for more efficient sales planning and sales management.
Every Saturday morning, Mr. Meier visits the magazine store around the corner to buy the weekend edition of his favourite newspaper. This has been going on for half a year now. The saleswoman knows Mr. Meier by now, and because he stops by every Saturday, she always addresses him with the same question as soon as he enters her store: "Good afternoon, Mr. Meier! The weekend edition, as usual?"
For Mr. Meier, buying his newspaper on the weekend has become a ritual. It's a pattern that repeats itself every week. The saleswoman has recognized this pattern and addresses Mr. Meier about it, almost automatically.
Are you a sales manager with Big Data? Here are three Predictive Analytics examples for B2B
With predictive analytics, big data becomes a big opportunity for B2B sales managers. This significant opportunity requires, however, a profound understanding of the sales situation, coupled with an understanding of big data mining models available.
How to define customer churn in B2B?
B2B Churn Rate: Definition and Calculation.
Business-to-Business (B2B) companies depend on building and developing long-term relationships with their customers to be financially successful.
However, over time, some customers will stop buying or will defect to the competition. Sales managers define this situation as “churn” or “customer attrition”. Managing and reducing customer churn is one of the most important, yet sometimes overlooked job of the sales leader.
Read more
Predictive Analytics & Controlling - How to use it in B2B Sales
How the sales analytics tools you use impact your sales controlling.
Controlling sales in B2B is increasingly becoming a high-tech game. Since selling cycles in business-to-business are getting longer and sales is getting more expensive, controlling need to look further into the future.
Machine learning, a well-known example of weak artificial intelligence, represents a fantastic opportunity for improvement in B2B sales controlling and business intelligence. It enriches the world of sales analytics with a substantial competitive advantage.