Okendo + AgentReady: Getting Your Reviews into Google and AI Answers

Okendo does the hard half of social proof: collecting reviews that carry real substance, with attribute ratings, photos, and video. AgentReady does the other half: making sure that proof is machine-readable everywhere decisions about your store get made, from Google results to AI shopping assistants. This is the integration guide, with the exact mechanics. Facts checked June 10, 2026.

What the integration does

Okendo maintains review data on your products as Shopify metafields. AgentReady reads that data on every product sync and builds two things from it:

1. AggregateRating markup on the product's JSON-LD, with the rating value and review count from your actual Okendo data. In ProductGroup mode (the variant-aware markup Google's product-variants documentation describes), the rating is mirrored so agents entering through the group node see it too.
2. Individual Review nodes when Okendo's review content is available on the product, so search engines and assistants can read what customers actually said, not just the average.

The output looks like this on a product page:

{
  "@type": "ProductGroup",
  "name": "Harbor Tee",
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": 4.8,
    "reviewCount": 132,
    "bestRating": "5",
    "worstRating": "1"
  }
}

No theme edits are involved. The markup ships through the same metafield-based rendering AgentReady uses for everything else, which means it survives theme changes and updates with your syncs.

Turning it on

There's no "on." If Okendo's data is on your products, AgentReady finds it:

1. In AgentReady, open Settings, then Reviews.
2. The detector samples your catalog and shows what it found, with the exact metafields that signaled the match, so you can verify the detection instead of taking it on faith.
3. Confirm Okendo as your review source, or just leave the detection as is. If you ever run two review apps during a migration, the override picker makes Okendo authoritative with one click.

From that point, every product sync carries current review data into the markup. Leave a product unreviewed and it gets no rating markup at all, because invented ratings are the fastest way to lose rich results entirely.

Why this pairing specifically

Any review app can put stars on a product page. The reason we built first-class Okendo support comes down to data quality on both ends:

• Okendo's reviews carry attributes. Fit, quality, value, whatever you configure. Richer inputs make richer outputs, and as AI assistants get better at reading review content rather than just counting stars, substance compounds. Okendo holds a 4.8 rating across 1,350+ reviews on the Shopify App Store (checked June 10, 2026), and plans start at $19/month.
• AgentReady's markup is honesty-first. Ratings come only from real data, the markup validates against Google's merchant listing requirements, and the same data flows to the agent-facing surfaces (llms.txt, the MCP endpoint, the agentic commerce feed) that review widgets never reach.

The combination means a shopper asking ChatGPT or Perplexity "is this brand any good" gets an answer grounded in your actual review data, and you can verify those agents visited in AgentReady's server-side traffic reporting.

Setup checklist for Okendo stores

If you run Okendo today, this is the whole adoption path:

1. Install AgentReady (free up to 500 products, no card).
2. Open Settings, then Reviews, and confirm the Okendo detection.
3. Run the first sync and spot-check a well-reviewed product with Google's Rich Results Test. You should see the Product or ProductGroup markup carrying your real rating.
4. Check the agent traffic report after a week to see which AI crawlers are reading the result.

Already running both and seeing something off? Tell us and we'll dig in. The integration is maintained code, not a one-time mapping, and review app integrations are a place we want bug reports.