Does this help?

✅ Difference between Case Response SLA and Case User Response SLA in Sprinklr:

Case Response SLA:

This metric tracks the overall SLA for responding to the case, regardless of who responds or how many responses are given. It usually refers to the first response to the case after it has been created or assigned — depending on configuration — and is focused on the case-level response commitment.

Case User Response SLA:

This tracks each individual response from an agent to a user, typically after the case is assigned. It resets each time the user replies and the agent is expected to respond again. It’s often used for ongoing conversations to ensure timely back-and-forth.

🔁 Why might the numbers look the same?

If you're seeing the same values for both metrics, it could be because:

You're looking at cases with only one interaction, where the first response also happens to be the only one.

Your dataset is filtered in a way that only first-response SLAs are being counted.

The case configuration might treat both as functionally identical if response timing and case handling are tightly coupled.

Hi Brianna! 👋

This is another confusing metric! Here's how I break it down:

📌 Case First User Response SLA from Assignment

This tracks the time it takes for the agent to make their very first response after a case is assigned. It’s a one-time measurement per case — just that very first agent reply.

➡️ Think of it like: “How fast did we get back to the customer the first time after assignment?”

🔁 Case User Response SLA from Assignment

This tracks the SLA time for every agent response after assignment — not just the first. It includes all agent replies throughout the life of the case.

➡️ So this is more like: “On average, how long did it take for agents to respond to each message after the case was assigned?”

🤔 Why Are You Seeing the Same Values?

If your dataset only includes cases with a single response, or if the first response time is similar to average response time (because there weren’t many replies), the two metrics might look the same — especially when you're calculating the average across a small or similar set of cases.

Also, since both are set to “average” in your widget, they’ll report a similar number unless you have multiple responses per case to differentiate the second metric.

Sometimes the visual setup or filters make a big difference in how these metrics behave. 😊

Hope this helps!