E-Commerce Marketing in 2020

Some retailers are already relying on advanced techniques that incorporate predictive analytics to learn more about their customers. For example:

• Customer lifetime value: How much will a customer spend over time?
• Predictive shopping affinity: What's a customer likely to buy?
• Lifecycle marketing: When and how often is a customer likely to make purchases?
• Contact frequency and channel affinity modeling: How often and by what method do customers like to be contacted?

For marketing to truly take a leap ahead, brands first must be able to organize and draw meaning from the wealth of data in front of them. These data sources will only become larger and more complex as time passes. To prepare, companies are investing in three missions: