Boosting Airline Efficiency with Personalized and Optimized Dynamic Offers

Industry:	Airline
Location:	UK
Client since:	2022

Personalized persona-based offers

Dynamic air bundle implementation

Improved response time by 20%

Enhanced ancillary offerings

Services used

Application modernization Software development

Background

With the fierce competition in the airline industry, tailoring products and services to individual customer preferences has become essential. By segmenting passengers based on their journey touchpoints, airlines can focus on personalized upsell opportunities at each stage of the travel experience.

This customization leverages persona characteristics such as age, gender, passenger composition, and loyalty tier, as well as travel requests like origin, destination, and travel dates. Airlines can dynamically offer ancillaries and bundled services based on these factors, providing relevant offers and discounts for additional services like seat upgrades, early check-in, and in-flight experiences.

Such personalization not only enhances customer satisfaction and loyalty but also significantly increases revenue through effective upselling and cross-selling strategies.

Client

Our client is a budget airline, focusing on providing affordable fares for shorter and medium-haul flights. They boast a large network of routes across Europe, connecting major cities and leisure destinations via major hubs.

Challenges

The primary challenge for the project was to enhance the current functionality of the implemented air search and merchandising engines. This project came with stringent requirements on transactions per second and strict response time limits.

Given the legacy nature of the project, the main challenge lay in refactoring the existing legacy codebase while simultaneously adding new features.

Solutions

To address the challenges, the following solutions were implemented:

Implemented dynamic air bundles based on persona characteristics and search parameters according to the client’s requirements.

Maintained existing configurations and added new ones as per the requirements, ensuring integration with the legacy system while enhancing functionality.

Ensured that the dynamic air bundle configurations were kept isolated for the customer.

Refactored the existing legacy codebase to add new features and improve overall system performance.

Implemented enhanced memory management techniques, leading to a significant reduction in resource requirements.

From an implementation perspective, the project primarily involved configuration changes of existing legacy options and bug fixes, as much of the functionality already existed. This approach allowed for the efficient enhancement of the system while maintaining stability and performance.

Results

The results demonstrate significant improvements in personalization, performance, stability, and resource efficiency, thereby enhancing the overall user experience and operational effectiveness.

Enhanced Personalization:

Offers are now personalized based on persona characteristics, providing a more tailored and relevant user experience.

Dynamic air bundle with ancillary suggestions are personalized based on search characteristics, enhancing the relevance of offers and potentially increasing ancillary sales.

Performance Improvement:

Overall response time improved by ~20% compared to the default flow, leading to a more efficient and user-friendly application experience.

Optimized cache storage resulting in a reduction in memory disk requirements. This optimization not only improved performance but also contributed to cost savings on memory storage.

Stability and Reliability:

Configuration changes and bug fixes addressed legacy issues, leading to increased stability and reliability of the application.

Leveraged existing functionality that was never used, thereby maximizing the use of available resources and reducing the need for extensive new development.