Businesses need more than simply a successful revenue stream in order to ensure their long term success. They need to be able to set themselves up for a successful future – leveraging what they know in order to figure out what will be expected to occur in the future. They need tools for analysis that will help them drive their business practices in the right direction.
Within the business world, predictive analytics are becoming increasingly common. Predictive analytics is a combination of several analysis techniques designed to estimate future trends and take advantage of patterns that have occurred with both current and historical data. In a way, predictive analytics is a form of purchase forecasting – using the data on hand to make sound predictive judgments for things like purchasing habits, risk, etc.
Predictive Analytics and Customer Retention
Predictive analytics plays many different roles throughout the CRM process, but it’s most common current use is with customer retention. Normally a company targets a customer that is leaving the company only after that customer leaves. That makes it difficult to retain their loyalty, because the customer has often already decided it is time to move on to a competitor.
Companies that integrate predictive analytics into their CRM use measurements seek to catch those that are in the process of leaving the company early, before they have reached the point of no return. Businesses take historical data, such as purchase data, and look at trends in buying habits that have historically shown to be the signs that someone is likely to stop purchasing the company’s products. They then take action that will improve the customer’s loyalty in order to increase retention before the customer
Predictive Analytics and the Future of Company Performance
Predictive analytics can be used in every part of CRM – including the opportunity to lead to more purchases. Depending on the data used and the analysis techniques utilized, predictive analysis can be a valuable way to ensure that the business is on a long term path to success.
No predictive analysis is 100% accurate because no predictive tools can predict every possible factor that leads to a loss of customer retention, the potential to increase purchases, etc. Yet predictive analysis (when used correctly) is perhaps one of the key ingredients to success even in today’s tough economy, because it allows you to target the right people at the right time in order to keep your revenue going strong.