Title: How to Use Predictive Analytics for Better Marketing Performance
Headings: How to Use Predictive Analytics for Better Marketing Performance
How to Use Predictive Analytics for Better Marketing Performance
What Is Predictive Marketing Analytics?
Dive Deeper:
8 Use Cases for Predictive Marketing Analytics
1) Detailed Lead Scoring
2) Lead Segmentation for Campaign Nurturing
3) Targeted Content Distribution
4) Lifetime Value Prediction
5) Churn Rate Prediction
6) Upselling and Cross-Selling Readiness
7) Understanding Product Fit
8) Optimization of Marketing Campaigns
Dive Deeper:
Predictive Marketing Analytics Measurement
1) Customer Acquisition Cost (CAC)
2) Marketing Percentage of CAC
3) Ratio of CLV and CAC (CLV:CAC)
4) Time to Earn Back CAC
5) Marketing Originated Customer Percentage
6) Marketing Influenced Customer Percentage
Dive Deeper:
Implementing Predictive Marketing Analytics for Optimized Business Decisions
Conclusion

Content: 5) Churn Rate Prediction
Churn rate is the rate of attrition, which is the percentage of subscribers or users who stop their subscriptions within a certain period. To grow, a business must have a higher growth rate than churn rate. With predictive analytics, you can identify the warning signs that alert you to the loss of a customer and allow you to provide the necessary follow-up or nurturing before it’s too late. 6) Upselling and Cross-Selling Readiness
Using the available data about customer buying behavior, businesses can upsell, cross-sell or combine both to increase profit. For example, if you know that 30% of customers who buy product A from you come back to buy product B within six months, you can then market product B to customers shortly after they buy product A to speed up that process and capture those who might not have otherwise considered purchasing product B.
7) Understanding Product Fit
Equipped with historical purchase, behavior and leads data, businesses can better understand exactly what customers’ needs and wants are. This may translate to developing future products to further meet those needs or improving upon existing products that aren’t meeting their sales targets. 8) Optimization of Marketing Campaigns
With predictive analytics, businesses can better plan, develop, strategize and implement future marketing campaigns. The more you know up front, the more successful your targeting and messaging will be. By applying predictive analytics in organizations, risks can be significantly reduced because decisions will be made based on data, not merely unproven assumptions that rely on instincts and some educated guesses. Many successful e-commerce ventures adopt predictive analytics in their marketing efforts and, of course, it should be no surprise that Amazon is the king of using data to target and remarket to customers with great success.