How to monitor and improve brand sentiment across AI models
Track how positively or negatively AI models describe your brand and systematically shift sentiment in your favour.
- 1
Measure your current sentiment baseline
Run a RankSignal scan and review the Sentiment signal for each AI model. Read the raw model responses and classify each statement about your brand as positive, neutral, or negative.
- 2
Identify the sources of negative sentiment
For each negative statement an AI model makes, search Google for the likely source. Common causes are negative reviews, critical press coverage, forum complaints, and social media incidents.
- 3
Address legitimate complaints
If the negative sentiment reflects real issues, fix them. Respond to negative reviews with specific resolution details. Update outdated information. Publish post-mortems for past incidents showing how you improved.
- 4
Increase the volume of positive signals
Request reviews from satisfied customers. Publish customer success stories and case studies. Seek testimonials from recognisable industry figures. The ratio of positive to negative content directly influences AI sentiment.
- 5
Create positive content that AI models prefer
Publish data-backed content, original research, and expert guides. AI models favour factual, well-structured content from authoritative sources. Avoid promotional language that models may discount.
- 6
Track sentiment trends monthly
Re-scan monthly and compare sentiment scores over time. Sentiment shifts slowly - expect 4-8 weeks for changes to appear in ChatGPT and Claude, though Perplexity may reflect changes within days.
See what AI says about your brand
RankSignal.ai scans ChatGPT, Claude, Gemini, Perplexity, and Grok to show how AI models perceive your brand. Try a free scan.
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