We are currently running an A/B test comparing Skills Based Routing against Bullseye routing. The control group uses a Data Action to fetch customer priority from an external CRM before queue assignment.
Environment details:
Issue:
During peak hours (10:00 AM - 12:00 PM EST), the average wait time increases significantly for the Bullseye variant. The Data Action execution time averages 2500ms, which exceeds our SLA target of 1500ms total interaction time.
Data Table:
| Variant |
Avg Wait Time (s) |
Data Action Latency (ms) |
SLA Breach % |
| Skills Based |
45 |
N/A |
2.1% |
| Bullseye |
68 |
2500 |
8.5% |
We suspect the synchronous call to the external API blocks the flow execution. The Data Action definition uses a GET request with standard headers.
Has anyone implemented a similar integration? What are your recommendations for reducing latency during routing decisions without caching sensitive data?
Reviewing the configuration suggests the synchronous execution model is the bottleneck. We experienced identical issues in the APAC region where regulatory compliance checks add additional overhead to API calls.
The timeout setting on the Data Action definition defaults to 10 seconds, which allows the flow to wait unnecessarily. Adjust the timeout to the minimum required value and consider moving the logic out of the routing path.
Additionally, ensure the external endpoint supports HTTPS with TLS 1.2 or higher. AU regulations require specific encryption standards that can impact handshake time during high load.
Check the API response headers for cache control directives. If the CRM allows caching, configure the header to reduce repeated lookups for the same customer ID.
Implement async processing for the priority check instead of blocking the flow execution. The Data Action execute endpoint allows POST requests with a callback URL if supported by your integration pattern.
Alternatively, move the lookup logic to a pre-dial cache system or utilize the Contact Data API to enrich contacts before they enter the queue. This removes the routing decision latency entirely.
For the A/B test results, compare abandonment rates during high latency periods. If abandonment increases beyond 5%, the current architecture requires immediate optimization regardless of SLA targets.