It’s tough to know how great your customer support actually is without actively measuring your results...but you have to measure the right things, and in the right way.
Analytics are a vital tool for high-quality customer service. And Helpshift has an extensive platform available for objectively assessing the right metrics, so that you can help your agents help your users in the most efficient way possible.
By regularly monitoring analytics, and then interpreting and implementing the information, customer experience can be improved, along with your agents’ ratings. Here are some of the actionable insights that can be extracted from the ‘Helpshift Analytics’ data.
1. Efficacy of FAQs.
There are a lot of variables that go into the ratio of how many users read FAQs compared to how many of those users report issues. The idea is to decrease the number of reported issues by having a thorough FAQ base that effectively answers user questions. But this isn’t always black-and-white and requires a nuanced approach for accurate assessment.
Helpshift Analytics shows you which FAQs are being read the most frequently, and the types of issues that are being reported. So if you see the same issue-type flooding in, but you have an FAQ that should be answering it, then you can rework that FAQ to make it more effective. And if you don’t have an FAQ that addresses a recurring issue, you know to create one!
2. Efficacy of Individual Agents.
Having CSAT scores for your agents is definitely helpful. But there are also a lot of variables that factor into how a customer rates your agent. And some of these factors are out of your agent’s control: like when a customer is dissatisfied with a product feature or company process that is not up to the agent’s discretion.
Helpshift Analytics allow you to get a macro view of your agent’s performance beyond CSAT. These metrics include details like the average ‘time to first response’, ‘time to resolve’, first contact resolution rate’, etc. These paint a much more complete picture of agent performance.
3. Prioritization of Users and Issues.
With a finely-tuned tagging system, you can properly assess which issues demand more attention, not just based on the frequency that they are being reported, but by the user group that is reporting them.
For example, there might be an issue that has been reported a few times, and isn’t urgent at first glance, but might demand attention because it’s your VIPs who are reporting it. Analytics can help you visually understand that correlation so that you can better structure your support strategy around it.
To learn more about using ‘Analytics’, please visit the Helpshift resource base.