How Airlines Can Improve CSAT Scores Through Better Passenger Communication

20 May, 2026By Ricky Vashi

22North and Jazeera Airways case study cover showing a passenger rating their flight experience on a smartphone, highlighting a 108% increase in CSAT response rates.

Customer Satisfaction Scores (CSAT) help airlines understand how passengers feel about their travel experience. They reveal what works, what frustrates travellers, and where airlines can improve.

In a competitive aviation market, passenger satisfaction matters. It can influence loyalty, repeat bookings, brand reputation, and revenue. Most importantly, it helps airlines make better decisions based on real passenger feedback.

Why Does CSAT Matter in Aviation?

Passengers interact with an airline at many points. These include booking, check-in, boarding, baggage collection, and customer support. Every interaction can shape their overall experience.

CSAT helps airlines identify service gaps and understand passenger expectations. Teams can then use this feedback to improve staff training, processes, technology, and communication.

Airports can benefit too. Programs such as ACI’s Airport Service Quality (ASQ) help airports measure passenger satisfaction and compare service quality.

How 22North Helped Jazeera Airways Increase CSAT Survey Responses by 108%

In September 2025, Jazeera Airways partnered with 22North by Phonon. Since then, CSAT survey response rates have increased by 108%, according to 22North’s reported results.

More responses give airlines a clearer picture of passenger sentiment. They also help teams spot recurring issues and decide what to address first.

For example, are passengers increasingly giving neutral ratings? Is meal quality affecting their experience? Could better communication improve their perception of boarding, check-in, or flight punctuality?

These questions turn feedback into practical opportunities for improvement.

CSAT in Aviation: Turning Feedback into Action

Many airlines rely on different systems for reservations, operations, customer support, and passenger communication. When these systems work in silos, teams may struggle to see the full passenger journey.

A connected approach helps airlines share relevant information and respond more proactively. Instead of waiting for a complaint, teams can identify potential service gaps and improve the experience before frustration grows.

A useful way to approach customer satisfaction is through three principles:

Customer-centricity: Understand what passengers need.
Communication: Share timely, relevant information.
Consistency: Deliver a reliable experience across touchpoints.

Why the Right Survey Channel Matters

A well-designed survey needs more than good questions. Airlines must also reach passengers at the right time and through a convenient channel.

WhatsApp can make feedback easier to share by bringing surveys into a familiar messaging experience. Airlines can also use SMS, email, RCS, and WeChat to reach passengers across different channels.

With 22North, airlines can connect passenger communication with feedback journeys. This helps reduce delays between a service interaction and the survey, giving teams more timely insights.

Make Every Passenger Interaction Count

CSAT is more than a score. It is a way to understand passenger needs, improve service, and build stronger relationships.

By combining thoughtful surveys, effective communication, and meaningful analysis, airlines can turn feedback into better experiences.

Discover how 22North helps airlines connect passenger communication with more informed customer experience decisions.

For broader passenger trends, explore the IATA Global Passenger Survey, which examines traveller preferences and expectations across the journey.

Reader Feedback

Was this insight helpful?

Cast your reaction to help us calibrate future aviation analyses.

How connected conversational AI can help airlines automate everyday passenger requests, reduce avoidable contact-center interactions and create more opportunities for digital servicing. What Can an Airline WhatsApp Chatbot Do? For airlines, passenger service is no longer just about answering questions. It is about helping travellers get things done, quickly and conveniently, without unnecessary dependence on contact centres. An airline WhatsApp chatbot can make this possible by turning everyday enquiries into connected self-service experiences. From checking flight status and retrieving booking details to accessing boarding passes and managing travel requests, WhatsApp can become a practical extension of an airline’s digital service ecosystem. The opportunity goes beyond automation. By connecting conversations with airline systems and enabling passengers to complete routine tasks independently, airlines can reduce avoidable interactions, improve operational efficiency and deliver a more seamless passenger experience. The everyday questions driving airline customer-service demand For passengers, many travel-related questions are simple: Is my booking confirmed? Has my flight been delayed or rescheduled? Where can I find my itinerary or boarding pass? Can I update my contact information? What happens if my flight is cancelled? For airlines, however, thousands of similar requests can create significant operational pressure. These enquiries often reach contact centers, even when the information is already available within airline systems. Agents spend valuable time retrieving booking details, checking flight status or guiding passengers through repetitive processes. The challenge becomes greater during peak travel periods and irregular operations (IROPS), when passenger demand can increase rapidly. Airlines need a service model that can handle routine requests independently while preserving human assistance for situations that genuinely require it. This is where WhatsApp-based conversational AI can make a difference. From chatbot responses to completed passenger journeys Traditional chatbots are often designed to answer questions. They recognize keywords, display predefined responses and redirect passengers to websites or support teams. A connected airline WhatsApp chatbot takes a more practical approach. By integrating with airline systems such as passenger service systems (PSS), reservation platforms and flight information sources, it can retrieve relevant information and support authorized passenger actions. Consider a passenger checking an upcoming flight. Instead of navigating multiple websites or waiting for an agent, the passenger can initiate a WhatsApp conversation, provide the required booking details and receive information relevant to their journey. Depending on the airline’s integrations and business rules, the same conversation may support itinerary retrieval, travel-document access, booking-related requests or escalation to an agent. The objective is not simply to respond faster. It is to help passengers complete their requests with fewer steps and less effort. How does WhatsApp passenger self-service work? A connected passenger-service journey typically follows five stages: Passenger initiates a conversation The passenger contacts the airline through its official WhatsApp channel. The chatbot understands the request Conversational AI identifies the passenger’s intent, such as checking a booking, retrieving flight information or requesting assistance. Airline systems provide relevant information Through authorized integrations, the platform retrieves available booking, passenger or operational information. The passenger completes an eligible task The chatbot guides the passenger through the available self-service options and confirms the outcome where supported. Human assistance remains available If the request requires an exception, additional verification or manual intervention, the conversation can be transferred to an agent with the relevant context. This creates a more connected experience between automation and assisted service. Can airline WhatsApp chatbots reduce contact-center workload? Yes, airline WhatsApp chatbots can help reduce avoidable contact-center interactions by resolving eligible passenger enquiries through automated self-service. However, the actual reduction in calls or agent workload depends on how many passengers use the chatbot, which requests it can complete and whether those passengers would otherwise have contacted an agent. For example, when passengers can retrieve their booking information or flight status independently, they may have less reason to contact customer support. This allows contact-center teams to focus more attention on complex booking changes, exceptional circumstances and disruption-related assistance. The operational opportunity extends beyond reducing enquiry volumes. A connected chatbot can also improve the quality of agent handovers by preserving passenger context and reducing repeated information gathering. For a broader perspective, read 22North’s article on the future of airline contact centers. Why airlines should begin with a phased chatbot rollout Airline passenger servicing involves complex rules, integrations and operational dependencies. A booking enquiry may be straightforward, while rescheduling, refunds or passenger modifications can depend on fare conditions, eligibility, available inventory and airline-specific policies. Introducing every journey simultaneously can make it difficult to identify where improvements are needed. A phased deployment allows airlines to begin with frequently requested services, evaluate real passenger behavior and gradually introduce more complex transactions. It also creates opportunities to improve conversational prompts, reduce incomplete journeys, strengthen exception handling and refine agent escalation. Rather than measuring success by the number of available chatbot features, airlines should focus on whether passengers can successfully complete the tasks those features support. How to Measure Airline WhatsApp Chatbot Performance? A useful measurement framework should distinguish between chatbot activity, successful automation and operational impact. Measurement What it helps airlines understand Conversation volume Passenger adoption and demand Intent distribution Most frequently requested services Automated resolution rate Proportion of conversations completed through automation Journey completion rate Whether eligible tasks are successfully completed Agent escalation rate Requests requiring human assistance Abandonment rate Where passengers leave before completing a journey Contact-center enquiry trends Whether assisted demand changes after deployment Customer satisfaction Passenger experience with automated servicing These metrics provide a basis for improving the service over time. For example, an airline may observe that a particular journey has high demand but relatively low completion. That insight can guide improvements to prompts, system integrations or eligibility handling. It is equally important to distinguish automated resolutions from verified contact-center call reductions. A resolved chatbot conversation is a useful outcome, but it does not automatically prove that an inbound call was avoided. Beyond routine enquiries: The Future of WhatsApp Passenger Self-Service Once foundational self-service journeys are established, airlines can expand conversational automation into more operationally and commercially valuable areas. Disruption management

Customer service leaders are under increasing pressure to improve customer experience, reduce operating costs and scale support without continuously increasing headcount. Yet, when customer conversations are fragmented across channels, routine requests depend on manual intervention and customers repeatedly have to explain their problems, delivering efficient service becomes difficult. The result is familiar: higher cost-to-serve, repeat contacts, longer handling times and inconsistent customer experiences. Conversational AI for customer service helps organisations move beyond disconnected chatbots and channels towards connected service journeys that resolve customer requests more efficiently. By bringing together omni-channel messaging, voice AI, customer context and workflow automation, businesses can reduce avoidable contact, improve service outcomes and make better use of their support teams. That is the thinking behind ConverseMax by 22North. 1. Move Beyond Chatbots to Connected Customer Service A traditional chatbot may answer a question. A connected conversational AI platform should help the customer get something done. For an airline passenger, that could mean: Checking flight status and retrieving booking details Managing flight disruptions and exploring rebooking options Checking baggage information Receiving a boarding pass Requesting a refund Changing a booking Connecting with a human agent when assistance is needed The distinction is important. Providing information is only one part of customer service. The real value comes from helping customers progress towards a resolution. With conversational AI, customer interactions can become part of a structured service journey, connecting customer intent with relevant information, business workflows and the next appropriate action. The objective is simple: move every eligible conversation closer to resolution, not just provide another answer. 2. Turn Customer Questions into Resolutions Consider an airline passenger who messages customer support: “I want to change my flight.” A basic chatbot might return a link to the airline’s help page or ask the passenger to contact another department. A connected conversational experience can take the interaction further. Depending on available integrations and business rules, it can retrieve relevant booking context, understand the passenger’s request, present eligible options and guide the passenger through the appropriate next steps. The same principle applies to refunds, baggage enquiries, disruption support and other service journeys. When conversational AI is connected to operational workflows, businesses can work towards: Fewer repeat contacts Faster request resolution Lower manual servicing effort Improved First Contact Resolution (FCR) Reduced pressure on customer service teams The goal is not simply to automate replies. It is to reduce the effort required to complete a service task. 3. Extend Customer Service to Conversational Voice AI Customers should not always have to navigate complex IVR menus or wait for an agent before the organisation understands what they need. Conversational Voice AI allows customers to describe their requirements naturally and move towards the appropriate service path. Consider a hotel guest calling and asking: “Can I get a late checkout tomorrow?” Instead of merely explaining the hotel’s checkout policy, a connected voice experience could use reservation context, check relevant availability and guide the guest towards the appropriate next step, subject to the hotel’s rules and system integrations. The same approach can support: Reservation enquiries Early check-in and late checkout requests Housekeeping requests Restaurant bookings Airport transfer enquiries Hotel information and guest assistance Where human judgement or approval is required, the interaction can be transferred to the relevant employee with the available context preserved. This helps address a common source of service frustration: having to repeat information when switching channels or speaking to a different agent. When implemented effectively, conversational voice AI can complement existing service teams while helping customers access assistance more naturally. 4. Create Continuous Conversations Across Channels Customers do not think in terms of communication channels. They think about the problem they are trying to solve. A passenger might begin a conversation on WhatsApp, move to voice and later speak to a customer service agent. Ideally, these interactions should feel like one connected service journey rather than three separate conversations. Omni-channel customer service connects interactions across channels while maintaining the relevant customer and conversation context. This can help organisations reduce repetition, improve agent handoffs and deliver more consistent experiences across digital and voice touch points. A connected service model can also help teams monitor performance through metrics such as: Repeat Contact Rate: How frequently customers contact the organisation again about the same issue. First Contact Resolution: How often a customer request is resolved during the initial interaction. Average Handling Time: How long an interaction takes to handle. Escalation Rate: How frequently conversations require additional intervention. Customer Satisfaction (CSAT): How customers rate their service experience. These metrics help businesses evaluate whether connecting conversations is translating into measurable service improvements. 5. Use Customer Context to Make Better Service Decisions The latest customer message rarely tells the whole story. A passenger asking about delayed baggage may be making their first enquiry. Another passenger may have already contacted the airline several times without receiving a satisfactory resolution. Treating both interactions identically can lead to unnecessary frustration and inefficient use of service resources. Conversational AI can help interpret signals such as customer intent, urgency, sentiment and previous interaction history. Subject to the data available and the organisation’s policies, these signals can help prioritise conversations, route requests and identify when additional attention is needed. For example, a routine flight-status enquiry may be suitable for automated handling, while a repeated unresolved baggage complaint may require escalation to an experienced agent. Better customer context also helps agents spend less time reconstructing what happened and more time resolving the issue. The objective is not to automate every interaction in the same way. It is to make each interaction more relevant to the customer’s situation. 6. Connect Conversational AI to Business Systems Conversational AI becomes significantly more useful when it can work with the systems that power the customer experience. Depending on the organisation, these systems may include: Booking and passenger service systems Customer Relationship Management (CRM) platforms Loyalty management systems Payment and refund platforms Order management systems Reservation and property management systems Other operational applications For example, an airline passenger requesting a booking

When a flight is delayed, airlines need to make several decisions quickly. Which passengers need assistance? Who qualifies for a voucher? Which connections are at risk, and what recovery options are available? Answering these questions requires information from multiple systems, clear business rules, and coordinated actions. Intelligent automation helps airlines bring these elements together to manage complex operational workflows more efficiently. What Is Intelligent Automation? Traditional automation follows predefined workflows. A flight delay triggers a notification, a cancellation initiates a recovery process, or a passenger enquiry creates a service case. Intelligent automation goes a step further by using operational data, business rules and AI-enabled capabilities to determine the appropriate next action. For example, when a delay puts connecting passengers at risk, an automated workflow can identify affected bookings, evaluate available recovery options, communicate relevant information and route unresolved cases to an agent. How Does It Work? Intelligent automation in airline operations brings together three key elements: Business rules: Define eligibility, compensation policies, rebooking restrictions and operational requirements. Data and AI: Provide passenger and flight context, identify potential risks and support recommendations. Human oversight: Manage exceptions, handle complex cases and maintain control over critical decisions. Together, these capabilities help airlines automate routine tasks while ensuring that actions remain aligned with operational policies and passenger needs. Where Can Airlines Apply Intelligent Automation? Intelligent automation can support several areas of airline operations: Disruption recovery: Identify affected passengers and coordinate rebooking and assistance workflows. Passenger communications: Deliver relevant updates across channels based on changing operational conditions. Customer servicing: Automate routine enquiries and route complex cases to the right team. Revenue optimisation: Support commercial decisions using demand, availability and business rules. Operational workflows: Reduce repetitive manual tasks and improve coordination across systems. The benefits depend on the quality of integrations, the workflows selected for automation and how performance is measured. Airlines should evaluate success through outcomes such as recovery completion, servicing effort and the number of unresolved passenger cases. How 22North Approaches Intelligent Automation At 22North, we focus on connecting airline systems, operational intelligence and passenger-facing workflows. From identifying passengers affected by a cancellation to coordinating recovery options, updating bookings and communicating confirmed arrangements, the objective is to make passenger operations more connected and manageable. By combining automation, AI-enabled capabilities and system integrations, 22North helps airlines streamline workflows, reduce manual servicing effort and deliver more consistent passenger experiences. Intelligent automation is not just about completing tasks faster. It is about connecting the right information to the right action at the right time. Explore 22North’s passenger operations solutions at 22north.io.

How Airlines Can Improve CSAT Scores Through Better Passenger Communication

Why Does CSAT Matter in Aviation?

How 22North Helped Jazeera Airways Increase CSAT Survey Responses by 108%

CSAT in Aviation: Turning Feedback into Action

Why the Right Survey Channel Matters

Make Every Passenger Interaction Count

Was this insight helpful?

Related insights & articles

Airline WhatsApp Chatbots: From Routine Enquiries to Real Passenger Self-Service

Resolve More. Serve Better: How Conversational AI Improves Customer Service

Intelligent Automation in Airline Operations: From Data to Action