Leveraging AI/ML(Personalization) to Increase Checkout Ratio & Rationalize Discount Coupons for a leading B2C E-Ticketing Platform
Increase in Checkout Ratio by 2 basis points. Decrease in cost to business by categorizing into 6 categories
About the client
The client is South India’s largest e-ticketing portal for buses, trains and hotels. They are pioneer in providing end-to-end software and other value-added solutions such as e-ticketing systems, fleet management solutions, vehicle tracking systems, passenger information systems, logistics management backed by a 24×7 customer support center. The company also provides technology solutions to more than 300 large private bus partners in India, 5 state transport corporations and 2 international bus partners.
- Increase Checkout Ratio hovering around early 20% by at the least few basis points, across channels (Android, IOS, WAP, Web)
- Rationalize cost to business due to discount coupons currently over 40K+, thereby increasing bottom-line revenue
AWS Services Used
- Amazon Personalize
Increased Checkout Ratio
Model 1 - Contextual Travel recommendations through Hyper-personalization (Personalize model)
Improved relevance of user recommendations within a context of device type, time of day, and more.
Unique landing page experiences, Fresh, new content delivered based on unique tastes and preferences.
Model 2 - Similar Travel route and operator recommendations (SIMS Model)
Refined & Improved discoverability and utilization of Bus operators by surfacing similar items to users.
Faster products discovery , Boost cross-sell and Upselling of bus operators and routes.
Rationalized discount coupons
Model 3 - Highly relevant Travel Product rankings (Discount Ranking Model)
Dynamically re-ranked relevant product recommendations to drive tangible business outcomes.
Increased content consumption, Enhanced marketing communications.