In our previous post, we looked at how you can use your data to make your support team more successful. In a similar vein, you can track customer support data to identify and fix issues with your product.
Often, the best way to improve customer support is to fix things so that your customer doesn’t need help in the first place. You can spot areas to prioritize by examining your ticket data to see which parts of your website, app, service, or product generate the most questions. Or, if a product change isn’t in the cards right now, you can use the data to improve your self-service so customers can get the help they need.
Let’s dive in and take a look!
You can use your support platform to track lots of different things, but if you would particularly like to identify ways to reduce the need for support, I recommend tracking the types of questions you get and the features or products that generate the most questions.
Figure out why your customers are reaching out. Questions about billing will require a very different solution than questions about product features.
On your support platform, you can set up a field to track “question type.” If possible, tailor the field values to your own unique situation. Not every platform offers this option, but if your platform does, I highly recommend you take advantage of it. Your team can then select the appropriate value as part of their support workflow. (Note that you can also add the field to your contact forms so your customers can choose a value, but the data customers provide might be less accurate than what you’ll get from your own team.)
The values I generally use are:
If you use Zendesk, for example, there are a couple of ways to track this data. You can:
As well as tracking question types, I recommend tracking which features or products your customers are asking questions about. While this is most applicable to supporting software products and their features, it’s also something that can come in handy for identifying the products you’re selling on an ecommerce site that require the most support.
By combining these two data points (question types and features/products) you can learn details such as 20% of your support inquiries are bug reports for your widget tracker. Knowing this information means you can work with engineering to reduce bugs in this area, which could dramatically decrease your customers’ need for support and lower your support costs. As another example, if you know that 10% of your support inquiries are about how to correctly fold your sheets, you might decide to make an educational video to reduce your incoming request volume.
How do you use your support platform to track features or products? Let’s use Intercom as an example.
In Intercom, you can use the “Tag” feature to tag conversations, or messages within a conversation, that relate to particular features or products. To do this, you need to set up a tag for each feature or product. For example:
Since Intercom doesn’t have custom fields, you might also want to use tags to track question types. You can even combine question types and features within a tag. For example:
Whether you choose to use combined or separate tags is up to you. Either way, you’ll be able to easily generate reports for them within Intercom.
You’ll need at least 30 days of data before you can discover any actionable insights, but the longer you track the data, the more useful it’ll be. A snapshot of what your customers need is useful, but changes over time are even more valuable.
Unfortunately, not every platform will allow you to track these fields and tags in time-based reports. If yours is one that does not, I suggest taking whatever snapshots you can get (often 30 days) and adding them to your own separate spreadsheet. If you gather reports monthly, over time you’ll be able to see the bigger picture in your spreadsheet.
If your platform does allow time-based reporting, that’s where you’ll want to view it. For example, in Help Scout you can head to your Channel report. From there, create a view, and select your question type field and the option you want to view. Then change the date to your time period. From there, you’ll see your Tags on the left side.
For example, I set my view to How-To Questions and filtered by one of our subscription plans, and got the following report:
In the report, you can see that 20% of the questions we received are about Integrations, 11% are about our Quotes feature, and 10% are about our text Styles.
Because Help Scout has a comparison period, you can also see how the displayed time period compares to the previous period (see the △ column). Because the percentage difference is 0-1%, I can tell these areas cause questions consistently over time.
Using my Help Scout report from the previous section, let’s see what we could do with this information.
Since the most common questions are about integrations, I’d view those tickets first. I might notice that there are several areas where customers aren’t finding the features intuitive. Possibly some changes to the product could solve these issues, or where an integration is complex and customers need a bit more help, additional education could make a difference.
Here’s what I would do to make a case for product changes:
While my example above was for a single subscription, I generally run reports for all our customers, and then only pass on the metrics for our ideal customers. The way you break it down will depend on how your product team looks at things and considers changes.
From here things will vary depending on your setup. Because I work for a software company and I lead the customer-facing division, I have regular meetings with the product leaders. I take my reports to them and we discuss getting these suggestions onto their roadmap for more research or product changes. At other companies, you might submit an internal request or send a written report to the team. The important thing is to have the data to back up your proposed changes.
I’d do something similar for the areas where education could help. Since education is part of my team, I can add these changes to the roadmap myself. If you have a separate education team, bring them your metrics and work with them to make the changes.
If you’re not already tracking information about your types of support requests, start doing it as soon as you can. Bringing metrics and data to the table when you advocate for changes can make all the difference because it’s concrete evidence of what’s not working. It will also help your team set priorities for product improvements that will enhance the customer experience and lower your support costs.
If you found this useful or there are more things you’d like to know, let us know on LinkedIn! We’d love to hear from you.
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