How Copenhagen Airport Improved Its Use of Passenger Feedback

January 2026 - PresentClient Copenhagen Airport

Custom AI AlgorithmVoice of the Passenger

Copenhagen Airport (CPH) is Scandinavia's largest airport, welcoming more than 30 million passengers each year, and consistently ranked among the most efficient in Europe.

With passengers moving through hundreds of physical and digital touchpoints, CPH has long prioritised passenger experience as an important part of its commercial strategy.

There is a rule at the heart of great airport experience: done right, nobody notices anything. Just a sense of ease, with a touch of welcome and thoughtfulness in the small details.

But managing something designed to feel invisible is one of the hardest challenges in customer experience. Feedback arrives from multiple sources, in different formats, at scale, and in a constant flow. Understanding what passengers actually feel, quickly enough to act on it, requires more than good intentions. It requires the right infrastructure.

This was the challenge CPH set out to solve.

"We had no shortage of passenger feedback. The challenge was bringing together insights from multiple sources in a way that made them easier to understand and act on across the organisation. VoP has made it much faster to identify patterns and respond to passenger feedback." Henrik Gregor Knudsen, Consumer Insights Manager, Copenhagen Airport.

The Challenge

CPH had access to a wealth of passenger feedback: internal surveys, open-ended responses, and more than 20,000 Google Reviews, including images and videos. The problem was not a lack of data. It was that the data was fragmented, multilingual, and arrived in formats that were impossible to process manually at the speed and volume needed.

Quantitative scores showed what was happening at a surface level. But the emotional why, the insight needed to actually improve the experience, was buried in thousands of unstructured responses across the airport's own surveys and public platforms alike.

Without a unified system to consolidate, translate, and analyse this feedback, valuable insights were regularly missed. Teams spent significant time on manual data gathering and structuring, and the window to act on emerging issues was often too narrow.

CPH needed a solution that could:

• Handle high volumes of diverse, multilingual data from multiple sources
• Deliver quick, actionable insights across all key touchpoints, from security and check-in to shopping and gates
• Identify and track themes and sentiment automatically
• Require minimal onboarding and scale across the organisation

At the core of VoP is a hybrid search engine that combines keyword matching with semantic AI. This means the platform surfaces relevant insights even when feedback is phrased differently, contains spelling errors, or consists entirely of images and videos. This reduces the need for manual filtering and makes it easier to identify relevant insights across datasets.

The platform introduced automated satisfaction scores and AI-generated summaries for each touchpoint and theme, explaining both what is happening and patterns in passenger feedback.

Teams can filter by source, language, time period, or topic, and track trends continuously over time.

Built for fast integration, VoP can be implemented quickly, depending on setup and available data, when touchpoints and themes are predefined, and is designed to scale as needs evolve.

Results

VoP made it faster and easier to get a clear overview across multiple data sources, enabling CPH to identify patterns and respond more quickly to developments in the passenger experience.

• A unified view of passenger sentiment across all key touchpoints
• Faster identification of patterns and trends across multiple data sources
• Insights that support faster responses to passenger feedback
• Reduction in manual data gathering and reporting effort
• Continuous monitoring of satisfaction scores across touchpoints over time
• Inclusion of both survey-based and publicly available passenger feedback