Airline Passenger Experience in Arabic: GCC Touchpoint Guide

A passenger books on your app on Sunday, sits in your lounge on Thursday and has reviewed both by Friday. The app gets a line in a reply on X. The lounge gets three stars on Google Maps. The new dessert on your business-class menu gets 30 seconds in a TikTok trip report, with a long comment thread under it.

None of it tags the airline. Most of it is in Arabic, in the dialect of whoever is flying. And the post-flight survey, sent a week later, asks questions the passenger has already answered in public.

This guide shows how to read the journey touchpoint by touchpoint, which team acts on each, and how to benchmark a rival, with a one-page scorecard and a worked example.

Step 1: Map the journey and give every stage an owner

Start with the stages your passengers actually go through, and give each one an owner. Insight about a touchpoint nobody owns goes nowhere.

Stage	Touchpoints	Where passengers talk about it	Owner
1. Inspire and book	Fare search, offers, payment, seat selection	Replies on X, Instagram comments on offer posts	Commercial and digital
2. App and check-in	Online check-in, boarding pass, app updates	X threads, replies under creators' posts	Digital
3. Airport and lounge	Bag drop, lounge food, seating, showers, staff	Google Maps reviews, Instagram posts and comments	Ground and lounge operations
4. Boarding	Gate, boarding order, the welcome on board	X, TikTok	Ground
5. Cabin	Seat, meal, crew, entertainment, Wi-Fi	YouTube and TikTok trip reports and their comments, Instagram	Product, cabin crew and catering
6. Arrival and baggage	Leaving the aircraft, bags at the belt	X	Ground
7. Loyalty and after the trip	Points, tier status, partner offers, the survey	X threads, Instagram comments	Loyalty

Step 2: Read each touchpoint in the passenger's own words

Here is what each touchpoint sounds like, written the way passengers in the region write it.

Touchpoint	What passengers write	Sentiment	Leading emotion	Decision and owner
Booking app	"التطبيق يعلّق كل ما أجي أختار المقعد" (Saudi: the app freezes every time I try to choose a seat)	Negative	Frustration	Digital checks the latest release
Check-in	"سويت تشيك إن من التطبيق في دقيقتين، وايد سهل" (Emirati: I checked in on the app in two minutes, so easy)	Positive	Relief	Digital promotes the feature in passengers' words
Lounge	"اللاونج وايد حلو بس القهوة مو شي" (Kuwaiti: the lounge is lovely but the coffee isn't good)	Mixed	Satisfaction with mild disappointment	Lounge operations fixes the detail before it becomes the lounge's reputation
Seat	"الكرسي مريح أوي، والرجلين واخدين راحتهم" (Egyptian: the seat is really comfortable, plenty of legroom)	Positive	Satisfaction	Product evidence for marketing and benchmarking
Meal	"الوجبة مرة لذيذة بس الكمية قليلة" (Saudi: the meal was really tasty but the portion was small)	Positive	Mild disappointment	Catering adjusts the portion, not the recipe
Crew	"الطاقم ما قصّروا، يكلمونا بالعربي والإنجليزي" (Emirati: the crew were wonderful, they spoke to us in Arabic and English)	Positive	Gratitude	Cabin crew recognition and training material
Entertainment	"el shasha kanet 7elwa bas el aflam el 3arabi 2alila" (Franco-Arabic, Egyptian: the screen was nice but there were few Arabic films)	Mixed	Mild disappointment	Product reviews the Arabic content mix
Baggage	"الشنطة طلعت بسرعة هالمرة" (Saudi: my bag came out quickly this time)	Positive	Relief	Ground tracks the monthly trend
Loyalty	"النقاط تنتهي بسرعة، ما لحقت أستخدمها" (Kuwaiti: the points expire fast, I didn't get to use them)	Negative	Disappointment	Loyalty reviews expiry rules and reminders

Two patterns run through all of these. Passengers switch languages mid-sentence: "The business seat كان comfortable بس الواي فاي ضعيف" (the business seat was comfortable but the Wi-Fi was weak). And they rarely use the airline's handle.

Step 3: Read sentiment and emotion together

Sentiment tells you whether a touchpoint is praised or criticised. Emotion tells you what sits behind it: joy, surprise, frustration, disappointment or gratitude. The two often disagree, and the gap is where the insight is.

• Positive sentiment with mild disappointment (the meal above) means keep the product and fix one detail.
• Negative sentiment with frustration that rises after an app release points to a bug, not a policy.
• Neutral sentiment with surprise usually marks something new that passengers have not made up their minds about yet.

Step 4: Fill in the touchpoint scorecard (one page)

Fill in first: route set · period (four weeks) · rival carrier · platforms (X, TikTok, Instagram, YouTube, Facebook, Google Maps reviews) · dialects (Emirati, Saudi, Kuwaiti, Egyptian, plus English and Franco-Arabic).

Touchpoint	Owner	Share of journey conversation	Sentiment and leading emotion	Most praised / most requested fix	Vs rival, same routes	Action this month
Booking and app	Digital
Check-in	Digital
Lounge	Lounge operations
Boarding	Ground
Seat	Product
Meal	Catering
Crew	Cabin crew
Entertainment and Wi-Fi	Product
Baggage	Ground
Loyalty	Loyalty

How to use it: fill it in monthly. Sort by share of conversation, then by the gap to your rival. Touchpoints near the top where you trail are your fix list. Touchpoints near the top where you lead are your promote list.

Step 5: Benchmark a rival on the same route set

1. Pick the same routes. Compare carriers on the city pairs you both fly, not on two whole networks.
2. Use the same weeks. Same four weeks, same season. School holidays, summer and Ramadan change who flies and what they talk about.
3. Compare share, not volume. A larger carrier always has more mentions. Compare each touchpoint's share of each carrier's journey conversation.
4. Read sentiment and emotion side by side. Two seats can both score positive while one draws excitement and the other quiet approval.
5. Separate creators from passengers. One trip report with a large following can move a month, so report the two separately.
6. Turn the gaps into two lists. Where you trail: a fix list with an owner. Where you lead: a promote list, in the passenger's own words.

Worked example: Airline A's new business-class menu (illustrative)

Illustrative example. Airline A is a fictional Gulf full-service carrier. It introduces a new business-class menu with regional dishes on its Gulf to Europe routes. Airline B, also fictional, flies the same routes. Nothing below is real data.

1. Set-up. The listening set covers the menu name in Arabic and English, likely misspellings, everyday words such as "المنيو الجديد" (the new menu) and "درجة الأعمال" (business class), and the Franco-Arabic "el menu el gedid". Airline B's cabin terms are tracked the same way.
2. Week 1. Two creators post trip reports on YouTube and TikTok. Meal's share of Airline A's cabin conversation rises. Sentiment is positive and the leading emotion is surprise: "ما توقعت أكل بهالمستوى في الجو" (Saudi: I didn't expect food this good in the air).
3. Week 2. Passengers post their own photos and the dessert becomes the most praised dish. One request repeats: "ليش ما يقدمونه في الرحلات القصيرة؟" (why don't they serve it on shorter flights?).
4. Week 3. Most new mentions do not tag Airline A, and several misspell the menu name. They count only because the listening set includes those variants. Excitement starts to settle.
5. Week 4. Sentiment stays positive. The leading emotion moves from surprise to satisfaction, the sign of a lasting improvement rather than a novelty. Against Airline B on the same routes, Airline A now leads on meal and still trails on seat comfort.
6. Decisions. Catering keeps the menu and tests it on two shorter routes. Marketing uses passengers' own words about the dessert in creator briefs. Product takes the seat gap into the next cabin review.

What actually decides it

A touchpoint scorecard is only as good as the mentions behind it. Passengers rarely tag the airline. They write the destination, the cabin or a nickname, and they misspell route, lounge and menu names all the time. A tool that tracks only the handle sees a thin slice of your journey, and a different slice of your rival's. dima captures tagged, untagged and misspelled mentions with 100% coverage, and reads them in the dialects they were written in. That is the specific problem it was built to solve.

Choosing a platform for this work? See the best social listening tools for airlines in the GCC, or dima's social listening and analytics.

Which touchpoint are your passengers reviewing right now that never reaches your dashboard?

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