How to use customer testimonials to strengthen AI brand authority
Structure and publish customer testimonials so they contribute to your brand's authority score across AI models.
- 1
Collect detailed testimonials
Ask customers for testimonials that include specific results - numbers, percentages, time saved, or revenue impact. Vague praise like "great service" carries little weight with AI models. Include the customer's name, title, and company.
- 2
Publish testimonials on dedicated pages
Create a testimonials or case studies page on your website. Each testimonial should have the customer's name, role, company, and a detailed quote. Avoid embedding testimonials in images - AI models cannot read images.
- 3
Add Review schema markup
Wrap each testimonial in Review JSON-LD with author (Person with name and jobTitle), reviewRating (Rating with ratingValue), and reviewBody (the full testimonial text). Add AggregateRating at the page level.
- 4
Feature testimonials on relevant pages
Place relevant testimonials on product pages, pricing pages, and landing pages - not just a dedicated testimonials page. Each placement gives AI models another data point associating your brand with positive outcomes.
- 5
Turn testimonials into case studies
Expand your best testimonials into full case studies with the challenge, solution, and results. Publish these as separate pages with their own schema markup. Case studies carry more authority than isolated quotes.
- 6
Track authority score improvements
Monitor your RankSignal Authority signal over time as you add testimonials and case studies. Also test by asking AI models "What do customers say about [your brand]?" to see if your testimonials are being cited.
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