Improving CX in the Airline Industry: Empower Your Contact Center Reps with Data

Beset by bad press over dog poop-covered seats, racial profiling and forcibly dragging passengers off planes, the airline industry doesn’t have a stellar reputation for customer experience.

A recent study by the University of Nevada, Reno, claimed that airline profits are unaffected by poor customer service, but research shows that on average, each US airline forgoes $1.4 billion in annual revenue by not improving CX.

One AI startup based in Tel Aviv, Israel, believes one way to a better passenger experienceis investing in CX automation tools designed specifically for frontline support reps at the contact center so they can focus on providing customer care. Reps.ai focuses on the airline and B2C insurance industries, using machine learning technology to show customer service teams how to uplift customer satisfaction and reduce handle time.

“It’s a huge challenge for both these industries to move away from focusing on growth and acquisition to prioritizing customer service,” says David Rubinstein, VP of strategy and customer success at Reps.ai. 

Both industries offer complex products where support reps field mostly repetitive questions, and yet, in order for a rep to answer a single customer query they need to consult an average of 8-12 different systems. For this reason, handling a single support ticket can cost a contact center $10-20, says David Rubinstein, VP of global customer success at Reps.ai.

“For airlines and insurance, we found that the number of clicks a rep has to do in order to correctly resolve a problem or provide good service is more than 20 clicks per request,” he adds.

Rubinstein visits call centers to meet with frontline agents, listen to their biggest gripes and difficulties, and design machine learning solutions. The technology uses machine learning natural language processing to automatically detect the highlights and lowlights of any support team based on ticket history. The AI studies best responses based on customer sentiment and then acts as a recommendation engine that reads customer intent to help agents provide the best answers or take needed action as quickly as possible.

For example, if a customer requests an invoice, the AI will pull the invoice for that customer from the CRM system and present it as a downloadable PDF for the agent to send to the customer.

Founded in 2017 after snagging first place at a startup pitch competition in Paris, VivaTechnology 2017, Reps.ai has been working with EasyJet, Britain’s largest budget airline, whose call center is based in South Africa.

Read: Special Report - Empowering Customer-Centric Engagement

JetBlue invested in a similar technology in 2017, Gladly, to design a new customer support system by streamlining communications. Gladly delivers a wide variety of essential customer information to the airline rep such as customer contact info, past and upcoming flights, and the entire history of customer interactions, which used to be siloed in separate channels. 

Service organizations that make their frontline reps a top priority can improve agent productivity and reduce attrition. However, the average service organization operates under a model that puts customers as a priority. Research shows that improving the agent experience can increase customer satisfaction by 11 percent and reduce customer effort by 9 percent.

The main takeaway: Emphasize the importance of holistic CX

When airlines make headlines about customer experience failures – or, more rarely, exceptional experiences – it’s usually related to the flight itself. Even though the contact center doesn’t necessarily make headlines, it’s still a potential improvement area in the overall passenger experience. With airlines, most customer complaints are for factors outside of the airline’s control, but the contact center is entirely under your brand’s control, and is an important factor customers will rate you on.

As customers focus more intently on speed and frictionless experiences, your brand needs to anticipate what customers are looking for, so it’s important to use AI and omnichannel capabilities in the contact center to understand customer intent.