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AI for Customer Support Managers Improves CSAT

Why taking on an AI initiative can get you to your goals faster

The job of a customer support manager is not easy — that’s no secret. Working long hours, balancing a loaded case backlog, and still handling customer complaints with grace is no small task. All of these moving parts, combined with limited budget and limited daylight, can make it hard to keep your eye on the true customer support prize: improving customer satisfaction (CSAT).

CSAT scores are often used as an end-all-be-all customer support metric, but anyone who works in the industry knows this can be misleading. CSAT scores are squishy — irritable customers, product failure, and even individual bias can all unfairly affect CSAT scores independent of agent engagement.

How can customer support managers improve CSAT in spite of all of these challenges?

CSAT is a resultant metric, which means it can be broken up into several smaller, controllable factors. By focusing on the individual facets of CSAT, and working “smarter”, you can move the needle more readily toward true customer satisfaction. The recipe for improved CSAT scores comes down to improving these three elements: 

  • First contact resolution (FCR) 
  • Average handle time (AHT) 
  • Agent happiness

Let's explore each of these factors individually to better understand how to improve CXM efficiency and, in effect, boost CSAT scores with the help of AI for customer support.

FIRST CONTACT RESOLUTION
This is the Holy Grail of customer support because your team’s ability to deliver quick and efficient resolution is a key contributor to customer satisfaction. This is fairly intuitive — when a customer reaches out for support, the last thing they want is to brave a maze of redirects!

The best way to measure FCR is coverage: the percentage of tickets that are resolved with one touch. While this might seem like a far-away ideal, the best support organizations actually resolve over 60% of e-cases with one touch.

You might think to yourself, “that sounds great, but my team’s cases are far too complex for quick resolution.” Challenge your team to simplify things. In the end, the simple answer is what your customers are looking for. There are tools available to make even the most complicated products and services eligible for FCR.

The best support managers can extrapolate ticket intent, and use common inquiries to help build simple decision trees. But this is easier said than done as a company grows and tickets pile up.

Here’s the solution: A good AI-powered customer support solution can help you read through your historical tickets and will give you an analysis of how to design decision trees and content that increases first contact resolution.

Continue reading this article. Download our new white paper here to learn how implementing an AI-based system can put you in control of your CXM and make you and your support team shine.

AI features help reduce AHT and improve FCR — effectively promoting agent efficiency and, in turn, boosting CSAT scores. Ready for that promotion? Buckle up!

Topics: Machine Learning, Customer Support, Artificial Intelligence, AI, Triage, CSAT, AnswerIQ, email macros, automation, backlog, nlp

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