Client- Jet Airways
Service rendered- NPS® and Text Analytics (Comment Analysis)
Jet Airways is an erstwhile Indian international airline. Before ceasing operations, it held the last share in the commercial passenger airline segment in India.
Therefore, we did a complete overhaul of their CX initiative to find research-backed data that was also highly actionable.
Mainly, we had 3 challenges.
We created a short survey with specific drilldowns and an open comment box. Short surveys usually have a higher response rate, which is why we kept ours under a minute.
The survey was send immediately after touchdown to increase the accuracy of the feedback.
FINDING 1– DELAYED FLIGHTS HAD LOWER NPS®
Customers were unhappy on delayed flights.
Interestingly, customers were angrier if the flights were delayed early morning or late night as compared to during the day. (see chart 1)
In additions, we also found out best performing city, airport, and much more.
Key Drivers Analysis allows companies to fix/prioritise the most important factor and quickly increase their NPS.
By analysing various drilldowns, we found out the drivers that had the highest impact on customer satisfaction. What’s more, we also set specific internal targets to further improve the overall CX. (see chart 2)
FINDING 2– Boarding experience,
In-flight meal, and Cabin appearance have the highest impact on overall customer experience.
In-flight meal has the highest impact on NPS for on-time flights.
On the other hand,
For delayed flights, boarding experience has the strongest effect on customer satisfaction.
Using Machine Learning and Text Analytics, we created word clouds from comments to understand emerging issues.
FINDING 3– “Hours”, “time”, “boarding gate”, “bad experience” were the words that commonly came up in comments (for boarding experience).
This suggests that customers must have found the boarding process to be time consuming and arduous, which made them unhappy.
Since, Numr is an agile solution, everything was done in a collaborative, real-time format.
We created role-based, easy-to-understand and customisable dashboards. See chart 2.
These dashboards allowed the airport managers to quickly discover common issues. By promptly fix them at their level, they prevented them from becoming huge problems later on.
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