How AI and predictive analytics can increase customer lifetime value
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The document discusses how AI and predictive analytics can enhance customer lifetime value (LTV) by improving engagement and reducing churn rates. It highlights the effectiveness of predictive modeling in increasing sales and retention rates, with significant increases in conversions and revenue reported. Additionally, it anticipates a rise in the use of customer data platforms and the effectiveness of multichannel marketing strategies by 2020.
How AI and predictive analytics can increase customer lifetime value
- 1. How AI and Predictive Analytics Can Increase Customer Lifetime Value
- 2. Predictive Engagement Modelling 40% Fewer emails sent Revenue increased by 25% Retaining new and disengaged customers to secure their LTV While increasing top-line revenue Public 2
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- 4. People have different understanding of what AI is Strong understanding 18.9% Becoming more confident 18.9% Source: eMarketer 4
- 5. Artificial Intelligence AI involves machines that can perform tasks that are characteristic of human intelligence but on a greater scale Machine Learning A process for gathering information and analysing data to provide learnings for AI to be successful. Predictive Analytics A specific set of algorithms that provides the likelihood that something will happen in the future, eg likelihood to make a purchase. 5
- 6. Predictive modelling Customer ID & Cross-device tracking Orchestration Reporting & Analytics DataIntegration Personal & Demographic Onsite Behavioural Data Engagement Data Transactional Data Mobile & Device Data Data APP Data Lifestyle Data Email Direct Mail Paid Social SMS AdWords Web Push Store Multi-channel & Data Segmentation 6
- 7. Single to Multi-Buyer Predicting VIP’s Customer Churn Allow Marketers To Accurately Predict and Influence Lifetime Value Prospect Conversion Predicting Customer Lifetime Value 7
- 8. Single to Multi- purchaser Model Unsubscribe Model First Purchase Model Lapsing Model 27.5% INCREASE IN CONVERSION RATE 114.6% INCREASE IN SALES 8.8%AN 83.5% INCREASE IN SECOND PURCHASES (MONTH ON MONTH) INCREASE IN RETENTION 909.6% INCREASE IN TRANSACTIONS 31.05% DECREASE IN UNSUBSCRIBES 103.83% INCREASE IN REVENUE 8
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- 10. 54% IN CUSTOMER REDUCTION CHURN INCREASE ACTIVE SEGMENT FROM 29.5% TO RedEye Confidential SPEND PER CUSTOMER HAS INCREASED £194 65% OVERALL VIP SEGMENT SIZE INCREASE BY 3.2% 5.8% PROPORTION OF VIP’S 2018 3.1% 1.4% PROPORTION OF CHURN RATE 33.5%
- 11. LTV as of Sept 2017 We predicted a 46% growth In LTV over the next 12 months Sept 2017 Sept 2018 However we exceeded this target by 38% 11
- 12. By 2020, customer data platforms will power 20% of current multichannel marketing hub deployments By 2020, over 50% of multichannel marketers will fully leverage multidimensional segmentation and predictive analytics to engage with consumers, up from 35% who did so in 2017. Source: Gartner - Smart Hubs and Dumb Spokes12
- 13. Travis Perkin’s have increased customer value by 38% 13
- 14. Continue the discussion… at the picnic table! RedEye Confidential 14 Chief Commercial Officer www.redeye.com @redeyematthew Matthew Kelleher matthew.Kelleher@redeye.com