Personalize Fitment to determine AI/ML driven Solution Roadmap for a leading B2C E-Ticketing Platform
1CloudHub helped one of India's largest online e-ticketing company in Data Acquisition, Data Validation, Fitment to Personalize services and Roadmap with future insights
About the client
The client is a 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.
Business Challenge
- Improve Checkout Ratio for an e-ticketing platform leveraging data
- Reduce cost to business due to discount coupons, thereby increasing bottom-line revenue
- Bridge the skew in the usage among the channels (web/mobile)
Project Scope
Data Acquisition, Data Preparation, Personalize Fitment and Roadmap with future insights
Our approach
Data Acquisition
Data Preparation
Personalize Fitment
Road-map
01. Data Acquisition
Ingest Data from multiple event sources like CleverTap, Gamooga across channels like web, android, ios into the DataLake
02. Data Preparation
Validate data quality and chose the right metadata with significant co-relation, which would have influencing behaviour on the models to be built
03. Personalize Fitment
Evaluated fitment to leverage Amazon Personalize for real time personalization, similar item recommendations and personalized rankings. Identified Insights about business performance and data gaps
04. Road-map
Detailed Roadmap based on influencing factors to increase checkout ratio
Outcomes
Comprehensive Business insights based on the trends of influencing factors
Directions to unlock the full value of the existing customer base and attract new consumers
Optimal path to maximize the usage of transport inventory mix to increase revenue
Looking forward
We are delighted to have helped the client by providing personalization to determine AI/ML driven Solution Roadmap. We look forward for the production phase to deploy the AI models.