Conversation Log Review Cadence (Retention)

Conversation Log Review Cadence (Retention)

1. 01

   Pull the prior week's full transcript export from the client's chatbot platform

   Request raw logs rather than dashboard summaries. Platforms such as Chatling and Chatbase expose conversation-level exports that preserve the exact user phrasing, which summary metrics strip out.

2. 02

   Tag every conversation that ended without a resolution or a captured lead

   Sort into three buckets: unanswered question, wrong answer, and user abandoned mid-flow. The third bucket is the one clients never see and the one that predicts churn.

3. 03

   Sample 20 transcripts per bucket and read them end to end

   Twenty is enough to surface a pattern and small enough to finish in under an hour. Reading beats scanning; the failure usually sits two turns before the visible breakdown.

4. 04

   Log each failure against a named cause in the shared tracker

   Causes worth separating: missing knowledge source, stale knowledge source, guardrail too tight, guardrail too loose, and no escalation path defined. Anything that does not fit one of those five is a configuration defect, not a content defect.

5. 05

   Rewrite or add the knowledge entries that caused the top three failure causes

   Fix the source document first, then retrain. Editing the bot's instructions to paper over a bad source document produces a fix that breaks on the next retrain.

6. 06

   Re-test the corrected flows against the original failing transcripts

   Paste the real user messages back in, not paraphrases. A bot that handles your rewritten version of the question has not been tested.

7. 07

   Send the client a two-page review note with counts, fixes, and the next review date

   Lead with the number of conversations that ended unresolved and the number now resolved. This note is the artifact that justifies the retainer line item when the client asks what ongoing optimization means.