Measure AI Sentiment Shift
Before-and-after AI sentiment comparison, with model-level detail.
ChatBakers 
Claude What this workflow does
Sentiment scores in aggregate hide more than they reveal. A score of 72 last month and 68 this month is a four-point drop, but which models drove it, which prompts, and which sources were retrieved in the conversations where sentiment fell?
This workflow produces the model-level breakdown: sentiment before and after a defined period, indexed by model and by prompt cluster, with the specific AI conversations and sources that drove the largest shifts surfaced for review.
Use it to measure the impact of a PR campaign, a product launch, a negative press cycle, or a competitor announcement.
Example prompt
ChatBakers MCP connected ❯ Pull our brand sentiment report for [period A] and [period B]. For each AI model, calculate the sentiment change between the two periods. For models where sentiment dropped more than 5 points, pull the specific conversation IDs driving the lowest scores. Return a structured comparison table with: AI model, sentiment in period A, sentiment in period B, change, and the 3 conversations with the lowest scores per model.
Related use cases
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