AI powered search and recommendation tools are becoming more embedded in how people discover products and services by the day. This is the driving force behind the upcoming Agentic Commerce development in anticipation of how users will engage with ecommerce in an AI world. Whilst the development team are busy working on the functionality of this, a new question is emerging for marketers: How do I make sure AI agents actually reference my brand’s reviews?

Why It's Important For AI Agents To Reference Reviews

It’s no longer trying to simply rank on Google or collecting five-star ratings. AI agents are increasingly having to act as “curators of trust” - pivoting to build trust in the quality of answers they provide. Whether it is AI agents embedded in search engines, shopping assistants, or chat interfaces, providing a variable mix of reliable information is crucial. We all know that UGC (user generated content) is an excellent marketing tool which can impact any buying decision. Reviews are therefore one of the most valuable data sources available to AI agents.

If your reviews aren’t structured, visible, and credible; they simply won’t get picked up. Here’s how you change that to make your reviews front and centre of the future Agentic Commerce landscape:

Your Guide To Reviews in the Age of AI Agents

1. Make Your Reviews Machine-Readable (Not Just Human-Friendly)

AI agents don’t “browse” the way we humans do. They parse, extract, and synthesise content and data. If your reviews live as plain text buried in a page, you’re already at a disadvantage.

What to do:

• Implement structured data (schema markup) for reviews (e.g. Review, Product, AggregateRating)

• Ensure key fields are included:

• Reviewer name

• Rating value

• Review date

• Review body

• Use consistent formatting across all product/service pages

Structured data helps AI agents confidently interpret your reviews as trustworthy, attributable content rather than anonymous text blobs.

2. Prioritise First-Party Reviews (But Don’t Ignore Third-Party)

AI systems tend to weigh credibility and source diversity heavily. If all reviews are first-party on your site with no attributed source and being passed through a vetting process before being visible, this can diminish trust rather than build. This is where a blend of review sources can help - and there are opportunities in splitting service and product reviews here. 

Third party review platforms (like Trustpilot, Reviews.IO) add independent validation and neutrality which is a strong indicator for AI. First party reviews give you full control - which can be positive and negative, but allow you to structure properly and really reinforce your brand authority. 

What to do:

• Actively collect reviews on trusted platforms

• Ensure consistency in brand naming and product naming across platforms

• Encourage detailed, descriptive reviews (AI prefers richness over volume)

3. Optimise for Natural Language, Not Just Star Ratings

AI agents don’t just summarise ratings, they extract meaning. A 5-star score is useful of course, however a sentence like: “This is the best giftable drink I’ve tried - great packaging and smooth taste. Delivery was really fast” is far more valuable to an AI. It also infers time commitment rather than a button click - another strong indicator.

What to do:

• Prompt customers with guided review questions, such as:

• “What problem did this solve for you?”

• “Who would you recommend this to?”

• “What stood out most?”

These phrases become citation-ready snippets that AI agents can reuse when recommending products.

4. Create Review-Led Content Around Your Products

Don’t just host reviews, amplify them. AI agents comb sites for information, meaning they pull from product pages, blog content, buying guides, comparison pages for example.

Content creation ideas:

• “Best of” lists featuring your own products (supported by real reviews)

• Case studies using customer feedback

• Roundups like: “Why customers love [product name]”

Quote real reviews verbatim and attribute them clearly. This increases the chance of AI citing them as trusted statements.

5. Ensure Your Brand and Products Are Unambiguously Named

AI struggles with ambiguity more than humans do. And we can struggle with it a lot. If your product naming or even brand name is inconsistent across your website, other retailers, or review platforms, it can be harder for AI to connect the dots

Standardise product names everywhere across your site and marketing messaging. Include brand and product consistently and most of all, avoid unnecessary variations. 

6. Build Authority Signals Around Your Reviews

AI doesn’t just ask “what are people saying?” it asks “should I trust this?”. If users can’t believe what they read, then they won’t engage - similar to any listing on a Google SERP. Therefore AI needs to build that trust and look beyond just common discourse. 

Some useful ideas to strengthen your credibility:

• Include reviewer profiles where possible

• Highlight verified purchases

• Add timestamps to reviews

• Showcasing volume (e.g. “500+ reviews”)

If your reviews are cited or referenced elsewhere (blogs, media, forums), this creates a network of validation AI can follow. More sources saying the same thing, more trust, more credibility.

7. Make Your Reviews Easily Crawlable

If AI agents can’t access your content, they can’t cite it. Some technical essentials to making your reviews accessible to agents are

• Avoid hiding reviews behind logins or scripts that block crawling

• Ensure pages load quickly and reliably

• Use clean HTML structures

8. Encourage Reviews That Compare and Contextualise

AI thrives on comparative insight. “I chose A over B because…” “Looking for a functional low cost option, C was more affordable than D”, “I really enjoyed the taste of E but F was a nicer package for gifting”. 

Prompt users to compare experiences and what alternatives they may have considered. Use case can also be helpful. These signals help AI position your product in recommendations.

Final Thought: Think Like a Source, Not Just a Brand

The brands that should win in AI-driven discovery won’t just have the best products; they’ll have the most usable, trustworthy, and well-structured information. Reviews are no longer just social proof. They’re training data for decisions. If you treat them as such - structured, enriched, and strategically distributed - you dramatically increase your chances of being cited when it matters most - when your ideal customer is browsing.

At Mucky Puddle, we are at the forefront of the AI Agentic Commerce roll out in ecommerce. As Shopify partners and experts, we are already implementing the key foundations of the evolving ecosystem into the design and development of our Shopify themes. Working with our expert in-house marketing team, we are helping our clients cross into this new digital landscape - and we can help you too. Contact us today and talk to our team about your Agentic Commerce future.