Our customer wanted to increase the user engagement and conversion rates for the booking of hotels, flights, and their holiday packages. To make this happen, they wanted a custom end-to-end platform and solution that enables personalized user experiences leveraging machine learning and artificial intelligence.
The client faced low conversion rates and less user satisfaction due to these challenges:
- Inefficient flight recommendations leading to low click rates
- Lack of recommendations for hotels and holiday packages
- Outdated technologies and disparate systems that did not help in transforming usage and click-thru’ analytics to personalized experiences
- Absence of a systematic data pipeline to pass on the required data to the personalization system on time and get the relevant recommendations
Srijan created an AI/ML-based personalization solution with the below key features:
- Personalization and backend integration that built more relevant and personalized customer experiences for booking services.
- Personalization enabled for these user personas - New unknown, Returning unknown, and Registered returning users
- Provides personalized recommendations and Insights based on usage, the user (Demographics), and transactional data - ‘Searches, Views, Similar users, Most popular, Similar content’ etc. leveraging machine learning, NLP, and deep neural networks at its core.
- Personalized content and recommendations are shown on Home page or other pages (thru’ Widgets)
- API-based Integration with CMS to serve the right recommendations with their content
- Configurable parameters by content editors to edit the recommendation parameters easily
- Trigger associated campaigns to drive more bookings (at offer price points) and push notifications for cart abandonments
Here is an overview of our implementation. We built:
- An API-based solution to provide personalization (both Containerized and AWS Managed solutions)
- Data Lake to capture JS-based user activity data (light-weight JS) as well as CRM and Transactional systems integration thru’ an API approach
- Backend layer with Caching as appropriate for specific needs; Personalization “Gateway” to route this to Caching layer for near Real-time recommendations
- Automated and ongoing ML Model training and refinements based on newer data
Fig: Personalization System interaction with CMS
Fig: Event-Driven Model Training
Our solution revolved around improving the customer experience by better understanding their needs through data-driven methodologies. We leveraged the cutting edge deep learning techniques and natural language processing to:
- build profile vectors for known users based on their implicit and explicit feedback
- the item vectors/embeddings of all resources including hotels, flights, packages, etc.
- Natural language Processing (NLP) and Deep Learning
- AWS Cloud - Managed Services, Serverless, and Elastic Compute instances
- AI/ML-based personalized recommendations for immersive exploration and booking experience
- Increase in customer delight and return rates to the site, driven thru’ associated campaigns
- Ability to leverage near real-time feedback to enhance user experience
- Improvement in brand awareness and customer loyalty
- Overall increased conversion rates by ~14%
- Enable content editors and business managers to easily configure personalization parameters