Let’s face it, nobody enjoys dealing with ticket escalations. When a ticket is escalated, it means there’s a problem that your ground-level employees can’t solve. The customer will have to wait, rather impatiently, for a solution; and if it escalates beyond that, it indicates a systemic issue that will require your developers to pull all-nighters. It’s an unpleasant situation all around!

When you talk about your business’s customer experience, it’s easy to get caught up in the bigger picture of what you want to achieve. Meaning, it’s easy to just imagine the ideal experience you want your customers to have, but not actually focus on what will help you achieve this.

Every company has its own unique audience — and should have a unique approach to customer engagement to match. After all, when it comes to creating great customer experiences and achieving high levels of satisfaction, there’s no one-size-fits-all approach that’s guaranteed to work for every brand.

Measuring and analyzing your customer support team’s performance can be challenging. The quality of an interaction between two people is subjective, and given that customer interactions are ultimately what make up the majority of a support team’s work, standard metrics like costs and returns aren’t often the best way to gauge and improve quality.

In the past few years, companies have become significantly more interdependent—users share passwords, and systems use backend technologies operated by third parties. So when hackers breach a company’s security, they often gain access to a wider set of services and information than initially expected.

Artificial intelligence, or AI, has been a hot topic within the customer support community recently and there are many good reasons for that. By using AI intelligently (no pun intended) support teams can be more efficient and effective, and create a better experience for customers, all without sacrificing quality.

A whole lot of data comes out of support interactions, enough so that astute support leaders can pull insights, discover trends, and improve how their business serves customers. While the data may only suggest what’s going on with your customers and agents, it’s important to be able to spot trends quickly.