From Booking to Baggage Claim: Lifting Customer Satisfaction by 18% with Touchpoint Sentiment Analysis

Our client, a major international airline, was facing a frustrating paradox. They were investing millions in enhancing their in-flight experience—upgrading meal services, refreshing cabin interiors, and expanding their entertainment library. Yet, their Net Promoter Score (NPS) was stagnant, and customer complaints on social media seemed to be rising. Their traditional post-flight surveys provided vague feedback, leaving their operations team guessing where the real problems were. They were spending money, but it wasn't moving the needle on customer satisfaction.

We proposed a radical shift in perspective. Instead of looking at the flight as a single event, we needed to deconstruct the entire passenger journey into a series of distinct touchpoints. The hypothesis was that a single, intensely negative experience on the ground could erase all the goodwill generated in the air. To prove this, our team at Iceberg Data initiated a Passenger Journey Sentiment Mapping project. We deployed a fleet of custom web scrapers to gather real-time, unstructured feedback from Twitter, airline review sites like Skytrax, and deep-dive travel forums where frequent flyers share candid experiences.

The core of our solution was a sophisticated Natural Language Processing (NLP) pipeline. We didn't just perform a simple positive/negative sentiment analysis. First, our model identified any mention of our client. Then, a custom-trained classifier, which we built specifically for the airline industry, categorized each post into a specific stage of travel: 'booking', 'check-in', 'boarding', 'in-flight', 'baggage claim', and so on. Only then did we analyze the sentiment within that specific context. This gave us a granular, touchpoint-by-touchpoint view of the customer's emotional journey.

The results, delivered via a live dashboard, were immediate and revelatory. The data confirmed that our client was excelling where they were investing: their 'booking_website' and 'in_flight_service' consistently received high sentiment scores, with passengers praising the friendly crew and easy-to-use site. However, the dashboard lit up with overwhelmingly negative sentiment in two key areas: 'boarding_process' and 'baggage_claim' . These two ground-based touchpoints were the source of nearly 70% of all negative mentions. Our crawlers surfaced thousands of comments with recurring themes like 'gate crowding' , 'zone confusion' for boarding, and 'long wait times' and 'damaged luggage' at the carousel.

This was the 'aha' moment. The client had been trying to improve a part of the journey that customers were already relatively happy with, while completely missing the immense frustration building up before passengers even stepped on the plane and after they landed. Armed with this specific, actionable data, they were able to pivot their strategy. They paused a planned catering upgrade and immediately redirected resources to form a 'Ground Experience Task Force'.

Using our continuous data feed, they trialed new, streamlined boarding procedures at key airports, monitoring the sentiment shifts in real-time. They invested in new baggage handling equipment and implemented stricter targets for 'first bag on belt' delivery, directly addressing the pain points our data had uncovered. Over the next six months, the results were dramatic. Negative mentions related to the boarding process fell by 45%. Their internal NPS score saw a 12-point jump, and formal complaints about ground services dropped by 25%. By mapping the entire journey, our client was finally able to stop guessing and start investing in the moments that truly mattered to their customers, turning points of friction into a competitive advantage.