Insights recipe: Reviewing SLA performance in Insights

Zendesk is removing Insights reporting on February 5th, 2021. If you are using Insights, you need to move to Explore, the latest generation of reporting for Zendesk products, before that time. If you need more time to move to Explore, you can apply for an extension using this form before January 22, 2021.

Note: This recipe provides an example of how you can build your own SLA performance reports. Alternatively, you can use the pre-built SLA reporting dashboard in the Zendesk Support agent interface. See SLA reporting dashboard overview (Professional and Enterprise).

If you've gone to the Reporting Overview page of Zendesk, you've probably seen a section that looks something like this:

These numbers give you "buckets" of tickets that have different first reply times. This is pretty useful to get a general overview of how you're doing as a company in getting back to your customers. However, this may not fulfill your needs for a number of reasons:

• These buckets don't match your company's SLA targets.
• These numbers include deleted tickets and you want to remove those.
• You need to report on a longer time frame (the Reporting Overview maximum is 90 days at a time).
• You want to look at other metrics than just the First reply time. Perhaps you want this configuration for First resolution time instead.

If that's the case then you'll need to build this out within your Insights project as custom metrics. This article will walk you through how to do this, using the default Overview report as a template.

If you need to make alterations to fit your company's SLA policy, feel free to do so. You may want to replace First reply time in minutes with First resolution time in minutes . Or perhaps you'll want to simply change the beginning and end times for each bucket.

Note: If you've never built a custom metric before, see Create a Metric. During metric creation you'll be selecting elements available to you from within your Insights project. For a list of the default facts and attributes see objects reference guide.

Step 1: Creating a set of custom metrics that look at the number of tickets falling into each SLA bucket

First you'll need to go to the GoodData portal (to get there, in Insights, click the GoodData link in the upper-right corner), then select Manage > Metrics .

Create a new metric and select the custom metric option. Now you'll want to build the following metrics to set up your buckets:

Step 2: Adding these metrics to a report

With these metrics created, you'll be able to add them to a report.

Go to Reports > Create Report and add the above metrics to the WHAT section. Now you'll want to configure it in graph form, so click on the bar chart option to the upper right.

Your results should be something like this:

Now you'll want to add labels to each graph to see the number it's representing.

Click Show Configuration in the upper-right and then go to Advanced Configuration > Global Settings and check the Data Labels option.

With that checked you'll see how many tickets represent each graph. You'll notice that this isn't a percentage and, unfortunately, there isn't a way to make these percentages through the report options. You'll either have to create new metrics to show the percentages in the bar graph, or you can look at this data through a pie chart instead.

Since all of the buckets should add up to 100% of your tickets, the pie chart might be a good option for you. You'll just need to be sure to check the As % option in the Advanced Configuration >> Global Settings >> Data Labels section.

It would look something like this:

As mentioned earlier, the alternative is to create percentage metrics that you can use in a bar chart.

Step 3 (Optional): Creating the percentage metrics

In order to find the percentage each bucket represents, we need to compare the buckets to the total number of tickets that have actually received a reply.

Skipping this step might throw off your numbers a bit since there are instances where agents don't need to reply before you solve the ticket. In that case the ticket wouldn't show up in any of the buckets we already created.

We'll create another metric to represent this total number of tickets:

Now we can use that as our denominator. (Please note that if you're using a First resolution time in minutes or a Full resolution time in minutes based metric then you might want to use # Solved Tickets for the denominator.)

While you're creating the metrics, remember to change the format of the metric so it is in % format instead of a decimal format. You'll be able to find this option on the metric edit page after creating each metric.

With these metrics created all you need to do is add them to a report and look at it in bar graph form. Remember to show the data labels under the Advanced Configuration >> Global Settings configuration section.

Step 4: Reordering and relabeling

You're almost finished. There are a couple of options to tweak that will increase readability in your report.

First, you'll want to rename your labels. Something like % Tickets 1hr < FRT < 8hr, while descriptive in your metrics page, is a bit cumbersome while looking at it from the context of a report based on first reply time.

To change the label all you need to do is go to the table format of the report, double-click that header, type in a new label (I like changing it to a simple 1-8 hrs format), and hit enter. Repeat this step for each of your metrics if you wish.

Next, you'll want to be sure your metrics are in the right order. Order the metrics from left to right while in table form by dragging and dropping the header cell. The left-to-right format will be reflected when going back to the bar graph.

Step 5: Review

You're finished! Now all you need to do is review the numbers to make sure they look accurate and add this report to an Insights dashboard for easy access (optional).

If you think your numbers look off, or if you need help with any of these steps, you can comment here. We're more than happy to help!