Sentiment Signals - Scrunch API Docs

Get a Sentiment Snapshot

A quick read on how AI assistants currently talk about the brand, and whether that’s shifting.

For [brand name], get sentiment metrics for the last 30 days, and again for the 30 days before that.

Show the positive/mixed/negative split for both periods and the change. Break it down by AI platform — is sentiment consistent across ChatGPT, Perplexity, Gemini, and Google AI Overviews, or is one platform notably more critical?

Summarize in one sentence: is sentiment improving, holding steady, or declining?

Compare Sentiment Against a Competitor

Not just “are we positive” — positive relative to who.

For [brand name], get sentiment metrics for the last 30 days for [brand name] and [competitor name] side by side.

Compare the positive/mixed/negative split for both brands. If one brand is described more favorably, pull 2-3 example prompts that illustrate the gap.

Drill Into a Negative Sentiment Read

Don’t just see the negative percentage — read what’s actually being said.

For [brand name], get sentiment metrics for the last 30 days filtered to negative sentiment only. List the specific prompts and platforms where this occurred.

For the 3 highest-observation prompts, pull the full response text with get_response. What specific claim, comparison, or complaint is driving the negative read? Is it the same issue repeating across responses, or several unrelated ones?

Brand Presence & Visibility

Pair sentiment with the presence numbers for the fuller picture of how the brand shows up.

Competitive Intelligence

Extend the sentiment comparison prompt to your full tracked competitor set.