See the language that matters
Group recurring praise, concerns, tradeoffs, and inaccuracies by brand or product.
AI brand sentiment monitoring
Understand how AI answers describe your brand.
Measure positive, neutral, and negative treatment, and see the language shifting over time.
app.wild-card.ai/tracking/sentiment
IllustrativeTracking
Brand language monitor
Language mix by model
Compared with prior 30 days
ChatGPTPositive +6 pts
Positive 68%Neutral 24%Negative 8%
GeminiPositive +2 pts
Positive 61%Neutral 31%Negative 8%
PerplexityPositive -1 pt
Positive 56%Neutral 34%Negative 10%
Observed positive language
62% · +3 ptsMay 18Jun 22
Language clusters & evidence
Positive34 mentions
lightweightclear ingredient detaileasy to layer
“Often described as lightweight with clearly listed active ingredients.”
Neutral17 mentions
mineral formulamid-range pricedaily use
“Presented as a daily mineral option in the mid-price range.”
Negative6 mentions
limited shade detailfinish varies
“Some answers note limited detail about finish across skin tones.”
Sentiment reflects language observed in sampled model responses, not audience opinion, causation, or brand control.
Description themes, movement, excerpts, and sources by brand and product. Illustrative data.
What you get
Brand sentiment in three moves.
Follow changing descriptions
Compare sentiment themes over time instead of hiding movement in a single score.
Connect evidence to action
Review excerpts and sources before clarifying product data or content.
How it works
From signal to next move.
- 01
Choose the scope
Select brands, products, prompt groups, topics, markets, and AI surfaces.
- 02
Cluster descriptions
Wildcard groups positive, neutral, and negative language while preserving each answer.
- 03
Inspect the excerpt
Read the full response, cited source, and product context before assigning work.
- 04
Route to a fix
Confirmed findings become catalog or content recommendations on the weekly roadmap.
FAQ
Questions about brand sentiment.
What is AI brand sentiment monitoring?
It measures the stance (positive, neutral, negative) models use when describing your brand or product and clusters the recurring themes behind those descriptions. Wildcard keeps the full excerpt, prompt, and source for every classified answer so you can act on evidence.
Prompt trackingWhat is the difference between sentiment and perception?
Sentiment is the direction of treatment. Perception is the specific attributes and objections attached to your brand. Wildcard reports both so you can locate favorable or unfavorable treatment and understand exactly which claim is driving it.
Can sentiment be reviewed by product or audience?
Yes. Wildcard filters sentiment by product, persona, platform, topic, and funnel scope so a weak SKU or persona-specific objection is not hidden inside a brand-wide average.
Competitor rankingsHow do I turn a negative finding into action?
Open the excerpt and full answer before assigning work, then correct the underlying product data or content. Wildcard converts confirmed findings into catalog enrichment or content refresh recommendations on the weekly roadmap.
Recommendation roadmapCan Wildcard make AI models describe my brand positively?
No platform can guarantee a preferred description from an independent model. Wildcard measures observed sentiment and helps you fix the product data and owned content that shapes what models cite.
Catalog enrichmentRelated features