Predict Airline Customer Complaints

Airlines Customer Service Marketing / Sales Improve Customer Experience Churn / Retention Executive Summary
Predict customer complaints in order to discover drivers and take preventative action.
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Overview

Business Problem

The airline industry, like many others, faces tremendous threats from customer dissatisfaction. In the first 9 months of 2014 alone, the Department of Transportation’s Aviation Consumer Protection Division received over 12,000 complaints including: flight delays, overbooking, mishandling of baggage, and poor customer servicing to name a few. Furthermore, given regulation in certain geographies like EU261 which mandates compensation for pre-defined service failures, this can be very costly. Whether it is a polite email notifying the customer about repatriation of lost luggage, a proactive callout to apologize for a recently delayed flight or financial compensation for a cancellation, there are actions an airline can take to delight the customer.

Intelligent Solution

AI can help empower your airline by predicting customer complaints and their severity. Your organization will be able to predict this information by using past complaints data in order to determine when a complaint is likely. Understanding when and why a complaint may occur will allow your organization to underpin a more effective service recovery strategy. The most common use cases include: forecasting volumes of complaints to inform call center staffing, predicting each customer’s propensity to complain, recommending the best service recovery solution; and where financial compensation is involved, recommending the depth of compensation. A lot of benefit can be measurably demonstrated through AB tests by operationalizing this insight and switching to a proactive service recovery approach, as opposed to being reactive to the customers’ calls. The service recovery paradox demonstrates that with the right targeting methodology, customers can actually be more delighted with proactive service recovery over-and-above if they were not service failed in the first place.

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