Conversation by Date per Assistant Disposition — Dedicated Sub-View

This sub-view adds a temporal dimension to the disposition analysis, plotting each disposition type as a separate line over time. It allows analysts to observe how Success and Failure rates trend day-by-day and identify specific dates where quality degraded or improved.

Figure 1: Conversation by Date per Assistant Disposition — Multi-Line Time-Series

1. Chart Details

Visualization Type: Multi-line time-series chart. Y-axis: Conversations count. X-axis: Day of Conversation Date. A dashed horizontal reference line marks the dataset average.

Legend and line behavior from the visible data:

Disposition Line	Color
Success	Gold/olive — dominant line; peaks at 5 on Wed 3/25/26, drops to 2 by 3/26, then 2 on 4/1/26
Failure	Light green — active from 3/11 at 2, holds around 1, then rises to 4 on Wed 4/1/26
Null	Dark green — low activity throughout, mostly 1 per active day
AbandonSuccess	Blue/gray — minimal activity, appears as isolated data points

A critical pattern is visible: on Wed 4/1/26, the Failure line rises to 4 while the Success line holds at 2. This crossover — where Failure volume approaches or exceeds Success volume — is a quality alert signal. It suggests that on this specific date, the assistants in the STG environment were failing more often than succeeding, which warrants investigation into what changed on or before that date.

The additional filter available in this sub-view is Assistant Disposition (in addition to the standard Channel, Stage, Assistant, Business Day filters), enabling analysts to show or hide specific disposition lines.

2. Business Value

Time-trending disposition data is essential for detecting regressions after assistant updates. If a bot update was deployed on 3/30 and the Failure line spikes on 4/1, the temporal chart makes this correlation immediately visible. Conversely, a drop in Failure counts following an optimization confirms the improvement was effective. This view supports post-deployment quality monitoring, SLA tracking, and trend-based alerting for AI operations teams.