Your Desk.com data reveals a lot about your business. Customer support data provides great insights into not only how you can improve your customer support itself, but also how you can improve your overall product. By taking advantage of this data, you can build a better product and optimize your organization.
DataHero, now available on the AppExchange, integrates directly with Desk. Analyzing your support data can be difficult or cumbersome. However, what we’ve learned is that by breaking your support analytics into more digestible, bite-sized chunks, you narrow your focus and answer the questions that are most critical to your support efficiency and product development. Here are four actionable best practices on how to best leverage integrated customer support analytics for your fast-growing business.
The goal of customer support is to help the user as quickly and as thoroughly as possible, so monitoring the amount of time until each case is received and resolved is a great way to do this. First, take a look at the response time for cases by channel. If you’re seeing long resolution times, you can do a number of things to find out why this is happening: collect more information around the “first touch” interactions from your agents, develop open-ended questions for your users to provide more feedback on their confusion, or even monitor how many times a ticket has been updated, or re-opened. Again, if there are a high number of “touches” that is slowing down response time, it may be time to look into how to streamline the support process.
Average response times are great for giving you a high level view of support performance, but you can answer many more specific questions using custom segmentation. Separate out response times by channel, for example, and you can tell at a glance if you’re allocating your time effectively. Likewise, segment by priority. If high priority cases are starting to come through Twitter more, then you may want to stress this channel to your support team. Or perhaps one channel is being neglected; you may want to remind your team to check on this one more frequently. You can also look at specific agents to identify your top performers and determine what makes them more efficient, then share that knowledge with the rest of the team.
This is a metric that helps companies not only monitor the effectiveness of support that users are receiving, but starts to cross over to product development as well. If you see that one help page is being accessed far more than many others, you should strongly consider re-vamping that content to better guide a user through this certain experience or even break the content into more parts to address specific issues.
Similar to tracking most popular help pages, tracking the number of cases by label over time allows you to see where users are struggling on your site, and thus where you could improve your service. In the example below, a client noticed that the “Reservation Date Changes” label made up a significant amount of support cases in January. A product improvement was then implemented to allow users to more easily change their own reservations, making the experience easier for the user and cutting out some support time. We can see that from February on, the number of Reservation Date Change cases decreased.
Data analysis, much like everything we do in business, is a constant work in progress and should be tailored to your specific business needs. Having an integrated analytics platform allows you to constantly monitor your support efficiency, identify improvement opportunities, implement those improvements, and then track the real effect on your site and customer service.
Start streamlining your process today. Import your own Desk.com data and create the charts you need to drive your business decisions.
Get the fastest, easiest way to understand your data today.Sign up for free