Every organization faces the challenge of improving customer service and delivering experiences that delight customers.
Swedbank Insurance, Get’mo and OREA, three teams participating in the SAS Hackathon, are no exception. Each encountered unique obstacles in delivering better experiences for their customers. With creative solutions tailored to their specific needs, these teams transformed how they interact with and serve their customers. Here’s a closer look at their journeys and the results they achieved.
Swedbank Insurance: Personalizing insurance campaigns, boosting efficiency
Swedbank Insurance struggled with inefficiencies and high costs in promoting their insurance products, which are not part of their core offerings. They needed a way to better engage customers and offer more personalized services.
The Swedbank Insurance team adopted a data-driven strategy, using machine learning and data mining to analyze nonpersonal data from banking and insurance clients. They built decision trees and gradient-boosting models to identify highly engaged customers and prioritize them for targeted campaigns. These models were deployed on the SAS® Viya® platform, which provided an intuitive interface and powerful machine learning capabilities.
This new approach allows Swedbank Insurance to deliver personalized insurance offers at the right time, significantly improving customer satisfaction. By being more efficient, the Swedbank Insurance team’s goal is to more than double their productivity in targeting new clients. As a result, Swedbank Insurance now has a more customer-centric and data-driven insurance strategy that delivers the right products at the right time.
Get’mo: Empowering consumers with smarter shopping decisions
Consumers face decisions trying to choose between varying product options, influenced by dynamic factors like price changes, seasonality and promotions. The Get’mo team’s goal was to enable fast, informed shopping decisions by comparing dynamic options while improving the overall shopping experience.
Get’mo visualized product availability and pricing variations by web scraping and catalog digitization from major retail chains like Walmart and Costco. They used SAS Viya for data scraping, standardization and error detection to ensure platform reliability. This analysis isolated price inconsistencies across stores and identified opportunities for cost savings based on product and location data.
The team developed a platform that empowers consumers with dynamic recommendations for the optimal product mix and route, while also considering price variations and other factors such as free delivery or discounts. For example, users were advised to go to Store A for a 20% discount on paper products, plus also buy sugar there. On the way, stop at Store B because it’s offering a 23% discount on Brand X coffee. Also, order detergent from Store C, which is offering an 18% discount plus free shipping.
This improved shopping experience delivers better savings for consumers while optimizing their decision-making process. The Get’mo team plans to expand the platform’s functionality and expand into other sectors, such as travel and logistics, to further enhance consumer satisfaction.
OREA: Turning to data for improved customer engagement
The OREA team sought to improve its ability to attract and retain hotel customers by comparing two campaign strategies: a traditional common-sense approach and a data-driven approach. OREA anticipates that the data-driven approach will yield better results, including higher engagement levels, bookings and ROI.
The traditional common-sense approach relied on broad, one-size-fits-all marketing strategies that sent promotions to all past guests with no specialized targeting. In contrast, the data-driven approach employed propensity models to analyze factors such as past booking behaviors to predict which customers are most likely to return - allowing for personalized, targeted communications and discounts. OREA also used SAS analytics to analyze customer behavior and satisfaction attributes, helping the team further refine their marketing efforts.
As expected, the data-driven approach significantly outperformed the traditional method, achieving higher click-through rates and generating three times more revenue. Looking beyond the numbers, being data-driven allows OREA to personally connect with guests by understanding their preferences and tailoring communications that lead to better customer experiences.
