This is a viewpoint from Scott Kendrick, VP of Marketing at CallMiner.

After the debacles that occurred within domestic air travel in 2017, it’s clear airlines need to look carefully at their customer service tactics.

Unfortunately, airlines often get away with poor customer service due to near-monopolies in some geographies. And this poor service most often hits the economy passenger rather than the high-tiered frequent flyer who receives a markedly different experience.

With the increase of social media coverage of customer service incidents, airlines are being forced to address these shortcomings. It’s a step towards a future that will see new technologies such as artificial intelligence play a more central role in service for airlines, as they uncover its ability to help manage overbookings, missed baggage, and other customer pain points.

How airlines are using new AI-based tools

Artificial Intelligence (AI) is the broad category of technology that mimics human intelligence using logic, decision trees, and modeling for predictive analysis or machine learning. AI includes systems that leverage programmed logic and those that are more advanced, learning based on analysis of historical or dynamic data sets.

AI-driven tools are being used in conjunction with customer service teams to perform myriad tasks. For example, these tools can be setup to resolve many customer questions, including boarding pass delivery, gate change notifications, and other data that can be easily “pushed” to the customer’s phone.

On the customer service side, the growing usage of AI-powered chatbots and virtual assistants is transforming how customers receive the latest information.

These solutions and IVR systems provide airlines with a cost-effective method of answering a significant portion of customers’ questions. Icelandair is one company that uses chatbots within the Facebook Messenger platform to allow flyers to search and book flights in a conversational manner. Users enter information about their travel details and the system is able to understand certain phrases such as “book a flight” or “book a stopover”. The system seamlessly moves the customer to the Icelandair website once payment and seat selection is required.

Airlines are also adding a layer of AI to their operations that agents can leverage to complete more complex tasks. If the customer wants to reroute their itinerary to a new destination in advance of expected bad weather, AI can provide the right options to the agent, who then performs the necessary actions. Some airlines are leveraging the technology in the baggage process, a common area of customer frustration.

Airlines such as Delta and Air New Zealand are leveraging AI and biometrics to eliminate the need for human involvement in the check-in and baggage check process. Robots and biometric cameras verify identity through facial recognition, then confirming any baggage restrictions, and get people on their way to the gate without having to wait in a long line for a manual process.

Delta uses an advanced IVR solution that features natural language processing. This system includes hundreds of customer “tags” that can be attached to the call and are visible to the human agent. So when they receive a call request through the IVR, they already have the context into the caller’s issue. The IVR’s intelligence allowed it to parse out what the customer needed through the actual conversation.

Managing overbookings through AI

For another example of utilizing AI and data, consider seat overbookings. Airlines are using solutions that can collect demographic data about passengers, and then adjust offerings to them that match their likely needs/wants. So, if there’s an overbooking situation, the airline could use intelligent data to pull info about the pool of passengers and then offer LEGOLAND tickets to a family of three, or cash to a single traveler.

The overbooking nightmare that ended with the United “dragged off the plane incident” could be avoided through the smarter usage of AI. For example, an AI program could provide airlines with near real-time data on who is going to board based on any flight changes and delays. The AI could use predictive analytics to determine if someone boarding a certain plane is the most logical move.

Meaning, will there be a certainty that one or more people will need to de-board the plane, and if so, what other options can be presented to avoid that situation or at the very least make it more palatable to the affected passenger.

Data analytics and customer satisfaction

While booking and simple changes are easy to resolve online, many customers still find they prefer to talk to a customer service agent when they have a problem. Especially if weather or mechanical issues delay a flight, the traveler wants to know a person can reroute them as quickly as possible.

What many of these centers are lacking is data specific to the actual content of the call. They might have a solution that records the call, length of the call, and similar metrics, but this does not provide data on the actual conversation.

The solution can be found in speech analytics platforms that can transcribe 100 percent of call conversations and transcribe them into searchable text, so management can monitor and improve agent performance These solutions hold enormous value because they provide the airlines with data that can be analyzed and categorized. The speech recognition that drives analytics solutions has significantly improved in accuracy in recent years due to AI, through machine and deep learning methods to improve language models.

Taken in the aggregate, speech analytics enable airline customer service managers to analyze 100 percent of calls, chats, and emails and find trends in the customer’s experience – both positive and negative. Perhaps there’s a spike in complaints about the ground operations crew at a certain airport. Or the system can identify tens of thousands of requests for a route between cities that aren’t offered by the airline.

Such a system helps airlines to understand customer preferences, and shows them how to use predictive modeling to stop negative occurrences before they turn into massive problems. The best of these analytics solutions will capture content from multiple customer service channels, so management can have the clearest picture of performance and the complete customer journey.

Why use automation to understand customer interactions

By automatically analyzing conversations, airlines can provide agents with context about how they typically interact with customers and insights into how they can improve. These advanced solutions can capture not only if the agent follows the right compliance and regulation scripts, but also if they use empathy-based language and the correct tone. Predictive models can help identify which language leads to a positive customer experience, or the desired outcome. Air travel can be stressful, especially with weather or maintenance delays, as people might be missing vacations and other important life events.

Airlines that can leverage AI within chatbots, IVR solutions, and the contact center can provide faster delivery and more relevant information to customers. The airline industry is vastly complicated with many working parts, and the carriers need to adopt technology that can make sense of all the data points and smooth out some of the bumps such as overbookings and lost luggage. AI-based tools can also provide call center agents with continuous feedback.

Consistent poor performers can be coached on the specific areas they need to improve or they can be moved out of their position.  Consistent high performers can be aptly rewarded and the successful language they use can be used in training other agents. This, in turn, improves the customer service they are providing every day to travelers.

This is a viewpoint from Scott Kendrick, VP of marketing, at CallMiner. Opinions and views expressed by all guest contributors do not necessarily reflect those of tnooz, its writers, or its partners.

Photo by Andre Hunter on Unsplash