Turn customer reviews into your AI discovery engine

Countdown timers, strike-through pricing, and scarcity badges might catch a human’s eye, but AI shopping agents pass right by them.

New research from Harvard Business Review shows that AI agents prioritize authentic user-generated content (UGC) over promotional tactics. When AI recommends products on behalf of shoppers, authentic star ratings and detailed reviews are the single most consistent buying signal across every major model.

In our latest breakdown, you’ll learn:

What AI agents look for: Why star ratings, specificity, and semantic depth matter more than discounts
The Triple-A Framework: How to make your review data Accessible, Authentic, and Abundant for AI discovery
3 invisible brand risks: Why old reviews, missing Q&As, or unverified feedback make products invisible to AI search
Two quick wins: Simple tweaks you can make this week to optimize your top-performing SKUs

Don’t let your products get left out of AI-mediated discovery.

White Paper from

Complete the form below to download the content:

Answer the following questions about your organization below:

What is your primary challenge with User-Generated Content (UGC) right now?

You have been directed to this site by Global IT Research. For more details on our information practices, please see our Privacy Policy, and by accessing this content you agree to our Terms of Use. You can unsubscribe at any time.

If your Download does not start Automatically, Click Download Whitepaper