Use case

AI Brand Sentiment Monitoring

Track how AI engines describe your brand's strengths, weaknesses, and positioning.

Quick answer
AI engines don't just mention brands—they frame them with descriptions of strengths, weaknesses, and positioning. This framing directly influences buyer perception, but most companies have no way to track how AI engines characterise their brand or detect when sentiment shifts unfavourably.
Expected outcomes

What you can achieve

95%
accuracy in AI sentiment classification
5-8
sentiment themes tracked per brand
<48h
detection time for sentiment shifts
+25%
average positive sentiment improvement
How it works

AI Brand Sentiment Monitoring with AEO Platform

1

Establish sentiment baseline

AEO Platform analyses how AI engines currently describe your brand, extracting sentiment themes, common framing, and strength/weakness attributions.

2

Compare against competitors

Review how your brand's AI sentiment compares to competitors in the same responses. Identify framing advantages and disadvantages.

3

Detect sentiment themes

The platform clusters sentiment into themes (e.g., "pricing perception," "ease of use," "enterprise readiness") so you can address specific narrative areas.

4

Trace causes to content

Identify which content sources are driving specific sentiment patterns. Understand whether negative framing originates from your own content, competitor content, or third-party sources.

5

Take corrective action

Follow targeted recommendations to shift sentiment: update content that reinforces negative framing, create content that strengthens positive themes, and build citations from sources with favourable perspectives.

The solution

How AEO Platform helps

AEO Platform analyses the sentiment and framing of every AI response that mentions your brand. Beyond positive/negative classification, the platform identifies specific sentiment themes: what strengths AI engines consistently attribute to your brand, what weaknesses they highlight, and how your framing compares to competitors mentioned in the same response.

Sentiment tracking over time reveals trends that individual queries cannot. You might discover that AI engines are increasingly describing your product as "complex" or "expensive"—a framing shift that, if left unaddressed, could impact conversions. The platform surfaces these emerging patterns early, before they become entrenched in AI engine outputs.

Actionable sentiment insights connect framing patterns to their likely content causes. If AI engines are characterising your brand as "limited to small businesses," the platform identifies which content sources are driving that perception and recommends content changes to broaden the narrative. This closes the loop between sentiment detection and corrective action.

Example queries

Queries to monitor

What do people think about [your brand]?
Is [your brand] worth the price?
What are the downsides of [your brand]?
How does [your brand] compare for ease of use?
[Your brand] pros and cons
Is [your brand] good for enterprise?
FAQ

AI Brand Sentiment Monitoring FAQ

Relevant engines
Get started

Start with the pages and proof that AI can actually use

Run the free audit to see what blocks AI from citing your site. Use the trial when you need ongoing monitoring, attribution, prompt discovery, and team workflows after the first fixes are live.