Can your agency tech stack meet the demands of modern retailing?

The knock-on effect of content fragmentation and customer expectations 

Travel agency systems already consume content from multiple sources. This will become increasingly difficult to manage as content fragmentation continues, for example, displaying NDC and EDIFACT content from the same airline in one interface. The eventual phasing out of the PNR will add another layer of tech complexity. Agency leaders need to consider current and planned tech capabilities, and the interdependence of internal and external systems (front, mid, and back office). 

As travelers’ expectations remain high for always-available online experiences that load quickly and provide bookable content, agency leaders should consider cloud-based infrastructures if they haven’t already. This will unlock the speed and scalability to handle seamless experiences at peak traffic and minimize loading times and network errors that frustrate customers and lead to abandoned bookings.  

Lastly, ‘build vs buy’ decisions will persist for agency tech leaders. With the growing demand for exceptional travel experiences, agencies need to balance resource allocation and expertise with the blend of in-house versus outsourced systems and content supply to achieve the most effective, cost-efficient tech stack. 

Let’s get personal: using data to delight customers 

Agencies can use modern retailing capabilities to better serve known customers with personalized offers and communications throughout their lifecycle. To get a more complete understanding of repeat customers, agencies can expand customer profiles by integrating data from multiple sources. For example, combining membership details from various programs including airline frequent flyer, hotel loyalty, ride-hailing, and credit card. New and strengthened partnerships with third parties like these can unlock valuable insights into retail behavior across channels and industries. 

Tailoring offers and experiences is made more difficult with unknown, first-time customers. As most leisure customers only book with an airline once a year, agencies may know little or nothing about them. This is where segmentation based on inferred characteristics will be important, along with collecting data during the shopping and booking process – a practice many agencies have already perfected. For example, prompting first-time customers to select their preferred airline or alliance, preferred destination types (beach, city, adventure), trip duration, and trip purpose (business, leisure, bleisure). 

Protect your most valuable asset: data 

Using customer data in new ways, including tailoring offers and product bundles, presents new data governance considerations. Agency leaders need to establish privacy protocols for expanded data sharing which could include customizable consent and relevant opt-out mechanisms for travelers to manage permissions. Building and maintaining trust with customers is crucial, and transparency in what and how data is used to personalize experience will help achieve this. 

With processing data comes risk and the travel industry isn’t immune from fraud and data breaches: hotel reservation systems, airlines, and frequent flyer programs have all been targeted in recent years. It’s important to consider regulatory compliance (e.g., GDPR and CCPA) to safeguard customer and booking data and to conduct regular penetration tests to assess potential vulnerabilities. 

From AI/ML experiments to impactful solutions 

Artificial intelligence and machine learning have been used by the travel industry for years, but recent developments combined with the public release of large language models has dramatically increased the number of travel industry use cases. For example, AI/ML chatbots can provide travel inspiration and personalized itinerary recommendations for flights, hotels, excursions and more. Going beyond the user interface (i.e. customers interacting with chatbots), there are opportunities to scale operations and unlock deeper insights with fraud detection, shopping cache innovations, aggregated data analysis and reporting, and customer behavior prediction. 

Agencies need to consider how to move from novel experiments to impactful business solutions. However, many agencies don’t have access to the tech resources, scalable infrastructure, or quantity of data needed to build and maintain solutions tailored to the travel industry. Outsourcing to tech providers will likely be the best option to leverage expertise in AI/ML product development and data processing at scale.