Customer Attrition in B2B: loyalty as a sales growth booster
Predictive analytics for customer retention plays a critical role to accelerate sales in Business-to-Business.
Building customer loyalty successfully and efficiently is what makes business-to-business companies thriving on the long-term. These market leaders actively engage in customer retention prediction. In the end, reliability lives from common purpose, and not from passive “wait and see”.
Furthermore, for companies that are focused on achieving stable and foreseeable sales growth, B2B loyalty programs are unavoidable. Nobody can reliably grow a customer base in the absence of customer retention predictions.
Customer churn and attrition are per definition the opposite of loyalty. Churn and loyalty correlate inversely. Moreover, commitment, trust, and satisfaction are critical variables corresponding to customer loyalty.
It is disheartening to see sales teams investing loads of energy on gaining new customers while neglecting their existing ones. Nonetheless, acquiring new customers costs several times more than building customer loyalty.
Let’s begin with that point.
Building customer loyalty cost less than acquiring new customers.
Acquiring a customer cost you five to seven times more than closing new businesses with your existing customers.
It is particularly critical, therefore, if you want to grow your revenues that you keep doing business with your current customers.
Successful B2B salesforces are more efficient than also-runs because they can retain and grow existing customers than just chasing after possible business with unknown customers. Predictive analytics for customer retention provides B2B salesforce with early signals of potential attrition.
Although many companies invest heavily in acquiring new customer, being able to predict when a customer might churn is a real superpower in B2B sales. Our analysis using more than 200 years’ worth of historical sales data showed that investments in predictive analytics for customer retention returns x10 to x12 what investments in new customer acquisition did, for manufacturing and industrial distributors in B2B.
Furthermore, successful loyalty programs are a self-feeding cycle. A 2017 study published in the International Journal of Research in Marketing found that as the proportion of members adopting loyalty programs increases, it also increases the probability of non-members taking them.
B2B loyalty programs enable stable and foreseeable sales growth
Being able to plan and grow your sales is a critical condition for success in business to business. Therefore, if you are looking for a higher return on sales, one of the best endeavours you can consider is to retain customers and avoid them from churning.
Building customer loyalty requires, therefore, two separate set of activities. First, successful sales teams employ churn prediction software. Once Key Account managers identify a customer with high attrition risk, they use targeted loyalty programs.
Why employing churn prediction software?
Because only with customer retention prediction, can you release your sales resources from tedious self-service business intelligence tasks. Moreover, only predictive sales analytics can tell you in advance which customers might churn. And acting in advance of actual attrition is critical to retaining the customer.
Once you have operationalized churn prediction, you can develop your dedicated B2B loyalty program. Building customer loyalty means treating your customers with loyalty, respect, and a right-sense of priority. A successful B2B loyalty program makes every customer feel special while employing a set of dedicated retention activities.
How does Churn Prediction with AI work?
Customer attrition is the hidden killer of your return on sales.
Customer attrition is one of the silent enemies of sales growth and return on sales (ROS). Loyalty takes years.
No business builds customer loyalty overnight.
Any good customer retention analytics software will be just the start for a successful B2B loyalty program.
To increase operating profit and return on sales, successful companies implement customer retention predictions and build customer loyalty using predictive analytics. Predictive Analytics helps to prioritize using machine learning algorithms trained with sales data. No other method can be faster, neither more accurate.
Unfortunately, many sales executives are still in the beginnings of this revolutionary technology. The ability to predict possible customer attrition in sales critically affects the productivity of B2B teams. Therefore, a strong sales team needs information to predict customer behaviour in general and churn in particular.
Remarkably, studies in customer loyalty have shown that both the firm pursuing a retention strategy and its customers are better off when the churn rate is lower. The financial benefits of a B2B loyalty program might come from both supplier and buyer rewarding mutual trust.
Customer Attrition in B2B: loyalty as a sales growth booster – Summary.
The prediction of successful customer retention plays a central role in the acceleration of sales grown — same about the application of statistics in B2B loyalty programs. Nowadays it is no longer only about the loyalty KPI you can measure, but about those, you can predict.
This ability to predict potential customer churn in sales has a significant impact on the productivity of B2B teams. Furthermore, it underpins dynamic and satisfactory business relationships under limited sales resources.
By deploying a range of dedicated and timely customer retention activities, a successful B2B loyalty program gives each customer the feeling of being unique. Smart selling on steroids.
Once a company have operationalized churn forecasting, it can use a dedicated B2B loyalty program properly. Building customer loyalty means treating customers with commitment as well, respect and fitting priority.
Rules of classic sales still apply. Satisfaction, commitment, trust and dedication are essential variables that relate to customer loyalty.
Free eBook for download: Churn analytics and prevention with predictive analytics
Managing and reducing customer attrition is an essential task of a sales manager. Sadly, sales executives often overlook customer churn in practice.
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