Predictive analytics can improve the effectiveness of CRM models
FREMONT, CA: Customer relationship management (CRM) is increasingly getting complex for businesses. Evolving customer expectations, the presence of competitors, and technological advancements are some of the key factors that make CRM even more challenging. According to a report, between one and two-third of all CRM projects fail mainly because the CRM solutions are used even after they become irrelevant due to emerging trends or technological innovations. This challenge can be effectively solved with the help of predictive analytics.
Predictive analytics leverages predictive sales software in CRM to achieve measurable profitable growth within a timeframe. Several firms are also coupling their predictive analytics software with disruptive technologies such as artificial intelligence (AI) to reduce operational costs and enhance revenues. Some of the companies are also utilizing the insights from predictive analytics to redesign their existing CRM with better features.
The implementation of predictive analytics shortens the length of the sales cycle. Alternatively, the incorporation of an entirely new CRM is both costly and is associated with longer sales cycles. Advanced analytics models augment human judgment with seller feedback and aids in the CRM model’s retraining. Such analytics capabilities enable the sales executives to prioritize and plan their sales approach. Further, predictive sales software offers a higher return on investment (ROI).
Predictive analytics uses data mining, machine learning (ML), and AI to make predictions concerning sales leads, customers, and products. Companies can leverage such insights to score leads, understand risks, analyze pricing, and cross-selling. Thus, successful companies are using predictive analytics to boost their customer relations instead of restructuring the CRM models from scratch. Successful implementation of a predictive analytics solution provides firms with a wide range of business insights, which include market dynamics, customer behavior, as well as emerging trends.
The seemingly irrational nature of customer behavior and expectations can be addressed with the help of predictive analytics. After all, firms that manage to address their customer needs will ride the market wave.