Combining Messenger platform features and machine learning to provide faster and more efficient customer service
First-class customer service
KLM Royal Dutch Airlines has been using Messenger for over 10 years, providing its passengers with fast, convenient, and round-the-clock customer support from its more than 350 agents worldwide.
When restrictions related to the coronavirus (COVID-19) pandemic took effect in March 2020, KLM received upwards of 50,000 messages a day – 5X more daily messages than its previous daily message volume record – and the number of Messenger conversations rose by 4.3X year-on-year, as the KLM team assisted thousands of travelers with repatriation flights. On top of the enormous volumes of customer queries, some of the airline’s service centers had lower occupancy due to strict local lockdowns, adding to the challenge of responding to the messages in a timely manner.
of the queries related to the COVID-19 pandemic received on Messenger were resolved with the automated experience
of all incoming queries received on Messenger were supported by automation, resulting in faster and more efficient replies from human agents
minute average response time for conversations prioritized as urgent, with almost real-time response time for those prioritised as most urgent
Faster responses for passengers
Due to the overwhelming volume of messages KLM received daily, the average case age on Messenger grew to an average of five days and customer satisfaction dropped by 20%. The team needed a solution for providing faster, more efficient service while also managing the workload of its customer service team.
Increasing efficiency with Messenger platform features, machine learning and better prioritisation
Facebook assisted KLM with managing the increased volume of conversations by changing the policy for the Human Agent Tag from a seven-day response time to a 21-day response time. Further, KLM adjusted its use of Messenger platform features to help manage wait time expectation, share information pertaining to COVID-19 guidelines and restrictions through its greetings and menu options, and to collect customer details upfront, enabling service agents to reply faster.
What’s more, KLM’s product team built an in-house solution powered by Salesforce Service Cloud to prioritize cases on Messenger by creating connections with the airline’s internal APIs.This helped the customer service team identify the urgency of a case based on flight departure time, flight status and keywords. This prioritization system helped KLM’s customer service agents assist passengers with an upcoming and disrupted flight first.KLM furthermore sent over 65,000 automated messages on Messenger to customers who had missed a flight or had a departure time further out, providing them with necessary information such as travel restrictions and self-service options for requesting a voucher.
In addition, 850 KLM employees from all over the world volunteered as temporary service agents to answer customer service queries on Messenger, closing 70,000 cases.
A smooth landing
By automating answers to frequently asked questions related to the COVID-19 pandemic, implementing new prioritization models, and using enhanced machine learning to its customer service platform, KLM was able to categorize conversations according to urgency and respond to customers as quickly as possible. To prepare for the return of travel, the airline has expanded the use of these solutions and scaled its use of DigitalGenius-built machine learning to identify sales opportunities. Between March 2020 and March 2021, it earned the following results:
- 10% of the queries related to the COVID-19 pandemic received on Messenger were resolved with the automated experience.
- 20% of all incoming queries received on Messenger were supported by automation, resulting in faster and more efficient replies from human agents
- 15-minute average response time for conversations prioritized as urgent, with almost real-time response time for those prioritised as most urgent
“Working closely together with our partners during the height of the COVID-19 pandemic helped us build solutions that allowed our service agents to respond faster to customers in urgent situations and introduce them to Messenger, one of our customer’s preferred communication channels. Looking forward, we want to grow our automated capabilities further to work towards real-time responses in all situations by combining the strengths of technology and the human touch of our service agents.”
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