Boosting IAGL rewards redemptions with intelligent AI recommendations

The client

IAGL

Since the launch of Avios in 2011, when British Airways and Iberia merged and International Airlines Group (IAG) was born, IAG Loyalty (IAGL) has evolved from a leader in travel rewards to loyalty pioneers. Over their 30-year history, they’ve created millions of memories for members around the world, harnessing their loyalty and love for travel with hotel and flight rewards and unforgettable experiences.

Today, IAGL is continuing that growth on a global stage, with millions of members and partnerships with the biggest names in travel, retail, hospitality, finance and more. Their people are driven by data and digital technology, and are proud to create the world’s most rewarding experiences.

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Key Outcomes

We created a proof of concept (PoC) - named Genie - proving that GenAI could help IAG Loyalty solve the challenge of finding available reward flights in a more efficient manner. Usability testing of the PoC with IAGL customers had universally positive results. Customers appreciated that the PoC application didn't feel like a traditional chatbot and removed the need to speak to a real person.

Pace 7 weeks to design and build a working proof of concept (PoC), to search for and recommend available reward flights using the power of generative AI (GenAI)
Usability 100% of test users felt that the PoC application performed better than a traditional search engine
Preference 83% of test users preferred using the PoC application over the current reward flight search

The Challenge

A complex reward flight redemption process led to a high rate of unbooked flights

IAG Loyalty partnered with AND Digital to determine how generative AI (GenAI) could benefit their business. Together, we identified five potential use cases, the most promising of which was advanced search and recommendations for reward flights.

Currently, the process of finding an available reward flight can be a stressful experience for customers. They struggle to effectively understand and use their rewards, such as Avios and companion vouchers, and must navigate multiple channels to find and redeem their rewards. Additionally, customers must know their desired destination in order to search for a reward flight, which can be a time-consuming and frustrating process involving a lot of trial and error. Furthermore, IAG Loyalty is limited in their ability to recommend flights or destinations to customers, particularly if the customer already has something in mind but there is no availability.

Recognising the complexity and value of this use case, we decided to collectively create a proof of concept (PoC) - named Genie - to test whether Gen AI could help IAG Loyalty solve the challenge of finding available reward flights in a more efficient manner. The key question was whether Gen AI could help match customers to their perfect reward flight more easily and efficiently.

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THE SOLUTION

A working PoC demonstrating a simpler, more intuitive user experience

In just 7 weeks, we turned the initial brief into a concrete idea of what the product should look like, we narrowed our focus down to the most critical features that would help us test our Gen AI hypothesis, and then we went and built a working PoC.

Along the way, we came up with the architecture and tech stack, an approach on governance and ethics, and a plan for how this could be brought to life in production the following year.

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The Results

The possibilities are endless for Genie

We have validated that Genie can help users find rewards flights and destinations in a way that isn’t possible today, offering them far more flexibility and personalisation than existing solutions.

Importantly, users feel this is a genuinely useful application of Gen AI -- without feeling like a chatbot. Critically, we have demonstrated that we can provide IAGL customers a unified view of available rewards and redemption options - delivering a simpler, more intuitive, and engaging user experience.

In support of this, we’ve shared critical insights into how IAGL can bring Genie to life in production, and what tech, data, and resources would be needed to do so. IAGL are excited about the early results and are interested in investing further into Gen AI by taking an incremental approach and continuing to build out the PoC to really validate whether this is something they want to eventually productionise. The future possibilities for Genie are endless.