I was thrilled to be invited to comment in an article by Federico Pascual, Co-Founder and COO of MonkeyLearn. In the article, I discuss how well-deployed artificial intelligence can result in faster and more consistent responsiveness to client requests. A link to the full article appears below.
Automatically tag customer service tickets
Customer service teams handle vast amounts of tickets every day – reading, processing, and tagging them so that they’re routed to the correct team to deal with the issue. It’s a time-consuming task and one that is slowly being replaced by AI tools such as text analysis.
Text analysis is the process of automatically obtaining information from text, analyzing it, and auto-tagging it. However, rather than spending hours going through thousands of tickets, text analysis models can whip through them in seconds!
Investment management solution company Archer uses AI to tag around 6,000 tickets a day. Most of their traffic is from emails, dealing with everything from live trading and reconciliation on stocks, to account maintenance requests and cash withdrawals.
To deal with the ticket volume, Archer turned to automation with MonkeyLearn. They’re now able to predict the action required automatically using AI, which has led to faster response times.
“We have cut down our response time in half, which is significant,” said Alyssa Wilkowski, Senior Programmer Analyst at Archer and Zendesk Certified Support Admin. “We're more efficient in getting the right responses to the right people, right away.”
When it comes to financial operations, processes are sometimes repetitive, which is another reason why Archer implemented MonkeyLearn. “We’ll do the same operations processes across numerous accounts, so we use AI to build repeatable, consistent service models,” said Alyssa. "Our people and our clients are happier, response times are better, service delivery is more consistent, and no one is left waiting in a queue."
