For retailers and distributors, keeping customers happy and engaged is more critical than ever. But did you know that 6 out of 10 mid-market firms lack the tools to predict churn or identify upsell/cross-sell opportunities?

Our latest article dives into how AI/ML is revolutionizing customer retention. Learn how to leverage these technologies to:

• Predict and prevent churn with advanced analytics.

• Identify personalized upsell/cross-sell opportunities.

• Tailor marketing campaigns for maximum impact.

• Build stronger customer relationships through personalization at scale.

Read the full article to discover how to build an insights-driven retention strategy that maximizes customer lifetime value and drives sustainable growth for your company.

RFM Analysis is a powerful tool for businesses seeking insights into customer behavior and segmenting them based on purchasing habits. By calculating RFM scores and creating segments, companies can identify valuable customer groups and target them with personalized sales and marketing campaigns. RFM Analysis is not limited to the retail industry or the marketing domain. It can be applied to most industries and functional domains that touch the customer, including pricing, supply chain, A/R, product management, and customer service. Additionally, RFM Analysis can benefit nonprofit organizations by understanding donor behavior to optimize fundraising initiatives.

In part 2 of our RFM Analysis article, we'll dive deeper into how we can calculate RFM scores, visualize customer performance by RFM segment and discuss sales and marketing implications.