The Requirement
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 Challenges
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- Outdated technologies and disparate systems that did not help in transforming usage and click-thru’ analytics to personalized experiences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
The Solution
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:
Our Approach
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.
Our ML algorithm also was equipped with various custom techniques to handle the cold start situations for the new users as well as unknown/anonymous users with no previous history/usage patterns. To capture the near real-time events and adapt the algorithm quickly over the new behavioral patterns, we built our own custom activity tracker leveraging vanilla javascript. It collects the user activity and pushes it into the data lake so that the personalization system can update the results of the recommendations based on accommodating those near real-time patterns. Our personalization system helped the client to effectively map the right resource to the right consumer which further helped them achieve good conversion rates and much better engagement.
Tech Stack
- Python
- Natural language Processing (NLP) and Deep Learning
- Vanilla Javascript
- AWS Cloud - Managed Services, Serverless, and Elastic Compute instances
Business Benefit
- 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