How SAS Enables Banks to Deliver Better Customer Experiences
Improve customer experience with real-time, contextualized interactions. Analyze all data to gain a holistic view of the customer experience. Accelerate the value derived from AI and fintech technologies to boost customer profitability, streamline operations and foster loyalty.
- Better identify and gain a deeper understanding of customer needs using advanced analytic techniques with embedded AI.
- Deliver more relevant, personalized communications and recommendations using self-learning marketing algorithms and machine learning to guide analytical processes.
Customer journey optimization
- Understand customer contact and response history by collecting and analyzing customer interaction data from all touch points.
- Orchestrate optimized, contextually relevant engagements that ensure consistency across all touch points of the customer journey.
Real-time customer experience
- Automate real-time customer experience decisions at scale across all channels.
- Anticipate customer needs and create contextual, real-time digital engagements that customers value.
How does one of the largest community banks in the state of Florida use customer information to deliver a better customer experience?
SAS helped Seacoast Bank:
- Build a customer lifetime value (CLTV) model, which looks at all customers, measures their value and specifies why they’re valuable so the bank can determine how much to invest in reaching and serving individual customers to get maximum ROI.
- Add predictive models and apply machine learning to solve specific business problems, such as personalization at scale.
- Market to each customer individually based on preferences and transactional history.
- Grow risk-adjusted revenue per customer by 30% and achieve ROI in the high triple-digits for automated marketing campaigns.
How does a fast-growing Turkish bank produce better-targeted customer communications and cut campaign costs in half?