Companies will go to great lengths to find out what customers think about their business. From expensive surveys to focus groups and everything in-between, customer information traditionally isn’t obtained overnight or on a shoestring budget. But, with this information now being so vital to customer success teams, a standardized method of obtaining real information at an affordable price has emerged. Known as the Net Promoter Score (NPS) it asks customers one simple question…

The size of a business can be a defining characteristic for any interaction. When it comes to sales, they will approach and speak with you differently based on how many employees and offices you have. With this said, customer support interactions and expectations also vary based on what growth stage a company is currently in. So, how should your company approach customer support at each unique stage of growth and what’s the best technology for you (both now and in the future)?

With more companies discovering the value of customer support, and how it’s now a profit center and no longer a cost center, company executives are placing a higher value on support metrics. Data is king in modern business, with more decisions being driven by analytics than ever before. So, if you’re a customer support leader, how can you maintain accurate reporting and metrics in your customer support software? Here are some of the best tactics…

Like any business, we all have different customers with different needs. Some customers have basic issues, while others have highly complex problems that can’t be solved in a single response by even your best agents.

In the business world, catch phrases come and go. Remember when “the net” was a thing? Running to your desk to grab a spreadsheet from “the net” was once a common task, but if you told an intern this right now they’d probably just give you a blank look!

The B2B customer is unique and requires a special kind of support strategy. In addition, the metrics that a company uses to measure success are also unique and very important. Utilizing the wrong data can cause a company to miss what it should catch and prioritize unnecessary actions.