Daniella's Customer Brain

Dark Horse <> OneAI: Agent Status catch up

3 min read

Dark Horse <> OneAI: Agent Status catch up

Date: 2026-05-05 | Duration: 35.22999954223633 min | Account: dark-horse

External attendees: justin@darkhorse.cpa

Summary

The team reviewed performance metrics, highlighting stable call volumes with fluctuating answer rates for both scheduler and validator agents. Optimizations are underway to mitigate integration challenges affecting client trust, especially regarding call timing and routing errors. Discussions included the necessity of updating agent scripts to improve accuracy and responsiveness during calls. Future plans aim to expand agent responsibilities to manage diverse inbound calls, requiring detailed mapping of caller types and workflows. Continuous monitoring and weekly reviews will support ongoing improvements, ensuring effective communication and transparency in progress.

Key Points

📊 Scheduler call volumes ranged from 4 to 38 daily: Answer rates fluctuated between 30% and 80%. ✅ Validator calls showed 100% answer and conversion rates: This indicates strong performance. ⚠️ Integration issues caused confusion: Fixing them is a priority to enhance client trust. 📝 Agent scripts require updates: These updates are essential to ensure they handle calls accurately and reduce errors. 📞 Plans are in place to map inbound call types: This will improve agent routing.

Overview

  • Scheduler call volumes ranged from 4 to 38 daily; answer rates fluctuated between 30% and 80%.
  • Validator calls showed 100% answer and conversion rates, indicating strong performance.
  • Integration issues caused confusion; fixing them is a priority to enhance client trust.
  • Agent scripts require updates to ensure they handle calls accurately and reduce errors.
  • Plans are in place to map inbound call types for improved agent routing.
  • Weekly call reviews will focus on identifying issues and tracking improvement progress.

Action Items

Daniella Block Have analyst review all calls from the past week(s) for scheduling issues and provide a report on findings and improvements (12:01) Create and share weekly status updates of top call issues found and fixes applied related to agent performance and workflow (18:55) Adjust the number of call attempts for both scheduler and validator agents to 5 and monitor effects on answer rates (29:17) Continue optimizing the agent’s script and response handling based on data and feedback, including adding suggested phrasing for callers with existing appointments (16:31) Coordinate with Michael Gur to demonstrate HubSpot queues and workflows for detailed joint debugging sessions (06:36)

Michael Gur Lead analysis and screen-share review of CRM workflows, especially concerning recent problematic calls (e.g., Susan Miller case) (09:02) Verify and confirm that meeting cancellation and rescheduling are fully functional via HubSpot API integration (27:10) Participate in follow-up calls to manually review recent call logs to ensure workflow issues are resolved (11:19)

Justin Kurn Provide a detailed document outlining all inbound call types, volumes, and routing workflows at Dark Horse for agent main line handling design (25:03) Monitor ongoing call feedback and raise specific cases for review to maintain trust in correct prospect targeting (12:49) Evaluate weekly reports on call analysis and agent script suggestions to decide on updates and improvements (18:55)

Yochai Levi Lead the planning of next meeting’s agenda to include a presentation summarizing current call performance, issues, and improvement roadmap aiming for higher call success rates (22:49) Facilitate the discussion on expanding the agent’s role to cover complex inbound main line call handling based on Justin’s contextual data (24:39) Encourage ongoing collaboration with the analyst team to continuously review and improve call handling quality (19:02)

Graph View