How AI-enabled Contact Centers Expedite Resolutions & Improve the Travel Experience.

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Between shopping for fares online, booking flights, and getting through an airport, there are a lot of touchpoints which are critical to an airline’s relationship with its customers. The biggest building block of this relationship is typically taking place through the airline’s customer service center.

That’s exactly why airlines are turning to machine learning tools and AI to make sure customer service requests, tickets, and queries get answered quickly and accurately. It’s a harsh reality, but for airlines, customer service is a fundamental gateway towards building or damaging their relationship with customers.

One expert from Astute Solutions, provider of call center technology to large brands, observes that upwards of 80 percent of customers that call in to get their ticket changed don’t end up doing so. Ticket changes, and many other services processes for airlines, often frustrate customers who give up and end up taking a hit in the wallet or end up dissatisfied and switching to another airline in the future.

Thankfully, some brands in the airline industry are leveraging technology to help expedite customer service requests, and expand the channels through which customers can connect with airlines. According to Deloitte, 62 percent of brands now view customer service as a competitive differentiator.

Routing Cases
Part of the problem for airlines when it comes to rapid issue resolution is that there are so many people, departments, and touch-points for the myriad of issues that arise for passengers. A flight change might require a different agent with separate expertise than for other problems like lost baggage, or issues with frequent flyer miles. Traditionally, passengers had to navigate lengthy automated phone systems, or log email inquiries and wait to hear back while their email sits in a message queue for hours, if not days.

Thus far, scripted chatbots have provided some halfway solutions in terms of getting information to their customers, but successful use cases for scripted bots are still mostly limited to sending one-way notifications around flight updates or gate changes.

Forward-thinking airlines are embracing machine learning tools, which are trained on vast amounts of historical data to provide more accurate classification and routing of cases — to rapidly reduce the amount of time a given email has to sit in an agent queue or backlog. Over time, these AI tools also learn from specific patterns present in common support issues.

Enabling Agents
While scripted chatbots can be effective in pushing out immediate, automated responses and obeying simple logic, proper machine learning tools work alongside customer service agents to expedite resolutions. Agents get the benefits of automated classification, saving valuable time, and can see potential answers recommended by the AI model right on their screen, further accelerating response rates.

In this way, AI is seen by agents as an enabler, helping them discover better ways to expedite service resolutions. For example, agents that handle lost baggage requests will leverage an automated AI-sequence to collect necessary information from the passenger, including flight number, any connecting flights, and a description of the actual luggage, before diving in to solve their issue. Over time, agents will leverage machine learning tools to improve the overall process rapidly.

Integrating with Messaging Apps
Airline passengers are also turning to third-party messaging apps, such as WhatsApp, Facebook Messenger, and WeChat, to contact airlines for customer service. For instance, KLM Royal Dutch Airlines was the first airline to enable Facebook Messenger and Whatsapp for its customer service operation. As a result, customers have more convenient ways to connect with the airline for service related questions as well as other topics.

As messaging apps continue to grow, it is important for airlines to consider how they handle, route, and expedite requests they receive through these channels. To handle the subsequent increase in message volume, forward-thinking airlines are implementing machine learning and AI tools to streamline the support process and keep customers happy.

Customers are moving in just one direction: forward. To keep up with their growing set of expectations, tech-savvy brands are quickly adopting new channels and technologies to enhance their service offerings and enable their teams to perform at their best every single day.

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