The core is around customer journey management. Know who your best customers are and build out journeys that deliver all the way into the channel. Push personalization into your mobile apps. Have a customer data platform that enables all related data to come together. Use historical purchases data alongside current behaviors across digital properties to amp up insights that you can deliver.
A digital customer innovation strategy revolves around 5 stages:
- Digital/customer analytics
- Customer journey test & learn
- Marketing attribution
- Customer journey analysis
- Customer journey optimization
Eggers shared her views and definitions on each.
Digital/Customer Analytics: Analyze and understand cross channel customer interactions. Banks do customer analytics well today. In the recent past, digital and customer operations were broken because they got stuck in siloes. Now we have the tools available to bring groups together to gain powerful insights. Once we have the data, we can collect it and interpret it at the customer level. Automation takes the steps out so you can do the analysis and reporting, marrying digital analytics with customer insights to build predictive models.
Customer Journey Test & Learn: Understand which marketer-defined customer journeys perform better. Test and learn entails machine learning using several techniques. Test and learn capability, or multi-variate testing gives you the ability to look at an entire experience within your website gauging the impact of one page vs. another.
- Multi-arm bandits are self-learning capabilities within A/B testing. This is a decision-helper that makes testing quicker, results quicker, and gives you the ability to make adjustments quickly.
- Testing versions, or pick a winner. Another machine-learning tool that allows you to discover unknown better performing segments of your population and compare them to other segments. This technique is closer to the channel and dynamic in nature and gets you closer to a more personalized marketing experience.
Marketing Attribution: This stage tests key touchpoints within predictive and scenario analysis.
Customer Journey Analysis discovers and analyzes the various paths to conversion at the touchpoint level.
Customer Journey Optimization is the AI-driven self-learning approach that discovers levers that influence goal achievement.