Getting started with an effective SLA to drive productivity forward
Having impactful Service-Level Agreements (SLAs) in place can be an incredibly effective method to ensure that your team members are meeting their time-sensitive goals. Handling volume efficiently is an essential part of any support operation, and SLAs will set the pace for your team members to bring assistance to clients based on these organization-wide policies. They can also help to identify strengths and weaknesses along the way.
SLAs provide an additional timing metric to your Conversations- one that can be reported on and displayed prominently in the subheader of any Conversation.
Without further adieu, let’s dive in and get our first SLA set up:
Step 1: Determining the targets of your SLA
First and foremost, we’ll navigate to Settings > Workplace > Service Level Agreements in the Kustomer dashboard. There, we should see a list of SLAs we have created for our Conversations.
SLAs can be applied to as many or to as little Conversations as you feel necessary. In certain situations where a client expects immediate, instantaneous response, you may want to apply a different SLA to these clients than the regular list of non-urgent clients.
Filters for SLAs allow you to use many of the same attributes you will find in Searches. For this example, we want to make sure our SLA applies to any conversation that falls into the Chat channel where the Company of the Customer sending the Conversation is Detroit Automatic Tooling.
As with Searches, these filters support an ANY, as well as an ALL logic for searches, depending on the need.
Step 2: Determining Time Constraints
Conversations moving from a Queue to an assigned User will be given a Priority based on the Team Routing Profile of the Users’ assigned Team(s). The next step takes these priority values into closer consideration.
Setting an accurate metric for your SLA is a crucial step for those who heavily rely on prioritizing Conversations. Here, we can see where the SLA is split into 4 major categories:
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First Response time: The length of time it takes for a User to send an initial response to the customer
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Longest Unresponded to Message: The time between the last inbound customer message to the agent outbound message.
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Total Conversation Open Time: The total time a Conversation remained open from when it was created to when it was closed. This does not count time the Conversation spends snoozed.
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Total Customer Wait Time: The total time a customer has waited for a responses from an agent, including the time Conversations were spent snoozed
For any Conversation that makes it through the filters we set earlier, we will enable any number of desired timing metrics for Conversation priority levels 1 through 5. Playing around with these settings a little bit in order to set the desired expectations for your Agents is usually encouraged.
Step 3: Setting Alerts and Applying during Business Hours
The 3rd and final steps are pretty self-explanatory. We can give alerts to certain Users or Teams based on the proximity of SLAs that are about to breach.
We can set a window to query Kustomer in a declared interval for these values as well. Making the time gap between when Kustomer searches for these values larger or smaller will determine how accurately you will be notified of when an SLA is about to breach. A larger value will check for breaching Conversations less frequently, and thus help to lower your Org’s number of API calls per minute/hour.
Finally, we need to give our SLA a Business Schedule to know when it should be applied. Once an option is selected from the dropdown bar, the timers on this SLA will only start ticking down during the open Business Hours specified in the schedule. Whenever the SLA on a Conversation would otherwise continue to count towards breach time, if the time of day exits the range of Business Hours defined on your schedule, the SLA will pause its countdown.
Send a couple test Conversations in and take notice of how each of your metrics begin to count down while they remain in an open status.
Establishing and optimizing SLAs for your team will become a crucial way to stay on top of and track response times.
When an SLA becomes established an object on the Conversation data (reached by the /v1/conversations/{:id} endpoint) becomes populated:
This object is able to be reported on and pulled with Workflows and even Searches. Simply refer to the endpoint and drill down through the JSON path to access the desired values.
This has been a basic rundown of how to get your company started with using SLA. For more information, you can always reach us by emailing: support@kustomer.com