Demand for predictive analytics tools has risen dramatically in the past few years. Although the tools have been around for decades, more and more companies are grasping the reality that predictive analytics is a competitive necessity.
Predictive modeling is utilized to support numerous small business initiatives. On the other hand, the current growth in demand can result from the need to remain competitive in today's market by maximizing the life span of an organization's most valuable clients.
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Customer retention is essential, particularly when considering it is considerably more expensive to get new customers than it is to keep present ones.
When version scores are put on the customer database, a much more proactive retention approach can be gained. If a company knows ahead that a client is very likely to flip to some other supplier, the intervention could be taken to keep that client.
According to a recent article from CRM magazine, the yield on investment (ROI) could be important for businesses using predictive analytics to leverage client retention plans.
A sizable British telecommunications company, Orange U.K., kept an extra 4 percent of the most valuable clients every month by employing predictive modeling scores to ascertain customer flight hazard.
This equates to a nearly $40 million annual gross operating profit. The us-based firm, 1-800-Flowers, fostered customer retention by 10% throughout the downturn. This equated to an extra $40 million in earnings.
Common Applications of Predictive Analytics comprise:
- Economy sizing and segmentation
- Prioritizing and targeting customer acquisition campaigns
- Identifying cross-sell opportunities
- Identifying loyalty dangers