The financial services landscape has fundamentally changed.
According to The Economist's 2016 retail banking report, 49% of banking executives say the traditional transaction/ branch based banking model will be dead by 2020.
Consumers increasingly expect highly contextual, personalized experiences across their connected devices. Banks and other financial service providers who can't deliver are under threat of extinction.
As non-traditional retail banking players, such as Amazon, Google and other tech giants who have developed intensely personalized customer interactions, start to infringe on the market entry, the urgency for this increases.
And most banks are not ready. In fact, fewer than 20% of bank executives feel prepared for the future. (PWC Retail Banking 2020)
70% of millennials are open to financial services from a company currently outside of the category. (Accenture's Banking Consumer Pulse: Banking Customer 2020)
In order to compete, banks must demonstrate customer behavioral and profile knowledge throughout the entire customer lifecycle and leverage that understanding to provide pitch perfect customer experiences at key points along the customer journey.
Existing marketing and IT infrastructure and processes have hindered banks from achieving this in the past, but the focus on impacting the customer journey in a meaningful way has become mission critical.
2017 Industry Guide: Addressing Banking's Digital Intelligence Debt
Traditional marketing cloud offerings and platforms can't keep pace. Instead, marketers need machine learning-powered digital intelligence that provides the following benefits:
- Nano-Clustering – Dynamically cluster your customers into 1000’s of nano segments for marketing and experimentation. Stop segmenting. Start engaging.
- Machine Learning Automation – Break all the rules by moving from human driven marketing automation solutions to machine learning platforms.
- Continuous Experimentation – Your A/B testing tool is officially too slow for today's connected consumer. Instead, rapidly run 1000’s of recursive tests to maximize performance of customer-oriented KPI’s such as average revenue per user, retention rate, and customer lifetime value.
- Adaptive Optimization – Optimize every interaction. Every time. Adaptive Optimization utilizes multi-armed bandit capabilities to automatically adapt campaigns to ongoing shifts in customer behavior or market conditions. This results in rapid lift as the tool identifies and takes action on additional pockets of value.
Explore how Amplero leverages machine learning to drive engagement lift and digital transformation across the entire customer lifecycle for our Fortune 1000 clients.