As airports embrace digitalization to optimize operations and increase asset lifespans, they also see digitalization 鈥� and particularly data analytics 鈥� as a means to improve the customer experience.

With the exponential growth in air travel, enhancing the passenger experience has become a top priority for busy airports around the world. Toronto Pearson Airport (GTAA), for example, to enable passengers to quickly report problems using their mobile phones.

Singapore Changi Airport, renowned for its exceptional passenger experience, is leveraging to offer passengers a contactless experience from check-in to boarding. Seattle-Tacoma International Airport (SEA), meanwhile, has created a that reduces congestion, shortens wait times, and enhances the security screening process.

Why this steady drumbeat of passenger experience improvements driven by data analytics? Largely because airports know that improved passenger experiences and satisfaction lead directly to growth in non-aero revenue. According to , an increase of 1% in global passenger satisfaction (as defined in the ASQ Survey) generates, on average, a non-aero revenue (NAR) growth of 1.5%.

But airports are just getting started. Airports generate vast amounts of data, yet this data remains underutilized 鈥� and customer data and analytics is . If airports can use their growing wealth of customer data to create personalized offerings 鈥� services tailored to individual passengers 鈥� they will redefine the passenger鈥檚 relationship to the airport and supercharge the profitability gains stemming from sophisticated customer experiences. 聽

The Data Foundation for Next-Gen Customer Experiences

To improve the passenger experience and pursue non-aero revenue growth, airports must capture more passenger data and use that data to deliver a hyper-personalised experience for passengers. The way to start is by building a 360-degree profile 鈥� a unique, individualized perspective 鈥� on every passenger.

To achieve a 360-degree view of passengers, airports need to first build a centralized operational data layer.聽This centralized data layer (or data lake) will leverage integration technologies such as APIs, data connection bridges, SQL queries, and batch uploads to capture data from niche airport systems and operations such as flight schedules, the Airport Collaborative Decision Making system (A-CDM), terminal ops, safety and security, and preventive maintenance. These kinds of operational data will help in mapping the passenger journey from entry to exit.

Beyond this operational data, it鈥檚 vital to capture data from passenger touchpoints like the airport鈥檚 mobile app, free Wi-Fi registration, and duty-free shopping in international terminals. Of course, data capture plans must comply with relevant data privacy and compliance laws and regulation, such as the EU鈥檚 General Data Protection Regulation (GDPR).

Acting on Passenger Data to Elevate the Experience

A robust analytics layer can turn a deep pool of passenger data into actionable insights. This business intelligence layer is critical in understanding data and using it to generate insights and predictive intelligence. This analytics layer will allow airports to:

• Embrace predictive intelligence:聽A centralized data system can identify, for example, passengers who are above-average spenders at airports and slot flights with high-value spenders into gates with high-value shopping opportunities. This tactic can go much further: As passengers approach duty-free stores, data fed into predictive intelligence systems can optimize offers and messaging for these customers, delivering automated welcoming messages and promotions in their language of choice. The shops themselves can even ensure that salespeople with appropriate language skills are ready to serve large incoming flights from overseas destinations.聽
• Deliver hyper-personalization:聽Process automation combined with contactless digital technologies can enable true personalisation of the passenger journey. Airports can identify repeat customers and offer discounts and services based on their profiles. For example, the system could recognize a frequent business traveller who rarely checks a bag, has prepaid for a customs clearing service, and frequently shops at Da Milano, M&S, and Starbucks. This traveller would automatically receive personalized offerings such as tailored retail and dining offers, VIP lounge experiences, specialized amenities driven by their card/loyalty status, and perhaps even family member gift recommendations. In aggregate, such offerings are likely to drive a significant increase in non-aero revenue.聽
• Ensure passengers have opportunities to shop:聽Another way to increase non-aero revenue is to encourage passengers to spend time in the airport鈥檚 retail and dining areas. Airports can reduce waiting time for check-in, boarding, and security by implementing smart technologies and self-service processes. For example, rapid self-service bag drop combined with biometric paperless check-in and boarding will inevitably give passengers more time to shop and eat.
• Provide an omnichannel experience:聽Airports can also improve revenues by delivering seamless omnichannel experiences using advanced websites and eCommerce platforms as well as digitally powered visual displays and interactive kiosks. For example, streaming advertisements through flight information display systems will help drive traffic to stores and restaurants. Similarly, interactive kiosks can help passengers find and book non-airport services such as pre-ordering restaurant meals and arranging future flights, cabs, and hotels. Most importantly, airports should focus on delivering consistent messaging and experiences across all of these touchpoints as well as through passengers鈥� mobile devices.

Realizing the Customer-Centric Airport Future

Non-aeronautical revenue growth can be an important component of an airport鈥檚 bottom line, and data analytics, harnessed well, can generate real growth. It requires the ability to unlock synergies between airport operations and airport facilities and, most important, to be able to hyper-personalize the passenger experience.聽

A good first step for an airport is to start with a short data strategy phase designed to provide a 鈥渃urrent state鈥� assessment of their聽existing聽data landscape. That discovery initiative will inform the creation of聽a data and technology roadmap to help improve airport KPIs such as operational excellence, customer satisfaction, and non-aero revenue. If they can effectively use data to improve passenger experiences, non-aero revenue will follow.

Manish Kumar
Head of Consulting, EC&O and Airports

Manish leads 91快活林鈥檚 Engineering, Construction, and Operations (EC&O) industry practice, which focuses on built environment and infrastructure sectors such as the construction, airports, real estate, facilities management, and smart cities. He is a seasoned professional with 25 years of diverse experience in evangelizing and delivering successful digital solutions. Manish has led business transformations across the globe aimed at achieving smart 21st century infrastructure. He has been recognized by 91快活林 as a Best People Manager. Manish is active in key industry forums and speaks at premier academic institutes across India.