Diagnose a sudden drop in appointment attendance for support ticket summarizer

Problem Statement Description

Procurement teams use a support ticket summarizer to quickly understand open supplier, contract, invoice, or internal support issues and decide whether a scheduled follow-up appointment is still needed. Recently, appointment attendance for this segment dropped suddenly, raising concerns that users may be missing, canceling, or deprioritizing meetings after interacting with summarized ticket content.

Your task is to diagnose the issue before proposing any fixes. Treat this as a root-cause analysis problem: define the anomaly clearly, verify whether the drop is real, identify where in the workflow the decline is happening, and determine which user, product, data, or operational factors could explain the change.

The investigation should account for the fact that procurement workflows are often time-sensitive, involve multiple stakeholders, and depend on trust in the accuracy and completeness of ticket summaries. A misleading summary, notification issue, scheduling integration problem, segment-specific rollout, or measurement gap could all affect attendance, so the analysis should separate correlation from causation.

The experience should consider:

- How “appointment attendance” is defined, including denominator, time window, status handling, and edge cases such as reschedules or late joins.

- Whether the drop is isolated to procurement teams or visible across other customer segments, regions, account sizes, ticket types, or platforms.

- Where the funnel changed: summary viewed, appointment suggested, appointment booked, reminder received, meeting joined, or appointment marked attended.

- Instrumentation checks for tracking changes, calendar integrations, event logging, bot/user-agent behavior, and data pipeline delays.

- Recent product, model, question, ranking, notification, calendar, permission, or workflow changes that could affect attendance.

- Hypotheses related to summary quality, user trust, perceived meeting necessity, scheduling friction, reminder reliability, and stakeholder availability.

- Evidence needed to validate or reject each hypothesis, including logs, cohorts, experiment exposure, user feedback, support complaints, and qualitative review.

- Immediate mitigation, monitoring, and prevention considerations once the likely root cause is confirmed.

The goal is to show a structured diagnostic approach that narrows the problem from a broad attendance drop to the most likely root cause, using segmentation, instrumentation validation, and evidence-driven reasoning before moving into recommendations.