Hazel reads your full Okendo review history (ratings, written reviews, review attributes, reviewer profiles, and tags) and answers business questions in plain English. No dashboards to build.
May 23, 2026
Hazel is an AI coworker that connects to Okendo and answers business questions about your reviews the way an analyst would. Once your Okendo API key is connected, Hazel ingests your full review corpus (star ratings, written review text, structured review attributes like fit, quality, and value, reviewer profile data, and tags) then refreshes every few hours. Ask Hazel about average ratings by product, the themes hiding inside your five-star reviews, the language customers use when describing a specific use case, or which SKUs are trending toward lower ratings, and you get an answer with the underlying reviews quoted back. For consumer brands running on Okendo, Hazel replaces the work of clicking through review feeds and tagging sentiment by hand, and it pairs Okendo reviews with your Shopify orders, ad platforms, email, and subscription data so you can ask whether reviews are influencing repeat purchase, conversion, or return rate in a single prompt.
Hazel reads the Okendo data that matters for analyzing a consumer brand and lets you query it conversationally:
Hazel keeps the full review history, so trend analyses going back to your first Okendo review are one prompt.
Common questions consumer brands ask about their Okendo data:
"What's the best, most compelling Okendo review we have for our focus SKU? Short and sweet. I need it for a landing page."
"Which product has the lowest review score this quarter, and what's the dominant complaint theme?"
"Top three themes in our one-star reviews this year, broken out by product vs. site reviews, with example quotes for each."
"Pull any strong snippets from five-star reviews that mention subscription, repeat purchase, or refilling. I need quotes for the subscription PDP."
"For repeat buyers (2+ orders in Shopify), how does their Okendo review rating distribution compare to first-time buyers? Are loyal customers our harshest critics?"
"NPS by customer cohort: break out promoters, passives, and detractors by the quarter they first purchased, and show whether NPS improves or degrades with tenure."
"Show me the month-over-month sentiment trend for our top 5 SKUs. Flag any product where average rating dropped more than 0.3 stars."
"What percentage of reviews mention a product-feedback suggestion (new flavor, new size, packaging change)? Group them by theme so the product team can prioritize."
Paste your Okendo API key into Hazel. The key lives in your Okendo account settings. It takes about a minute end-to-end and no engineering work.
Reviews (with star ratings, written text, and timestamps), review attributes (fit, quality, value, and any custom structured attributes), reviewer profile attributes, and review tags. Today Hazel reads Okendo reviews, review attributes, reviewer profiles, and tags. Quizzes, Surveys, Loyalty, and Referrals data from Okendo's other apps is not ingested. No cap on lookback. Hazel pulls your full Okendo history forward.
Roughly every 6 hours, automatically.
Okendo data gets sharper the moment Hazel can join it against your order history. Once both are connected, you can correlate ratings with sales, return rates, and repeat purchase without exporting anything.
API key from your Okendo account. Hazel only reads your data; it never writes back to Okendo or to the customer-facing review widget.
Okendo doesn't ship a public MCP server today. Their AI surface is built around in-app features: AI-Generated Review Summaries on the product page, AI Review Moderation and Replies, AI Multi-language Translation, Smart Content Analysis, and the generative-AI quiz builder in Okendo Quizzes Pro. Those are great for shopper-facing conversion and admin efficiency.
Okendo also ships its own Analytics and Reporting suite: dashboards for review request email performance, ratings generation rates, customer sentiment score, and reward ROI. That's the right tool for tracking your Okendo program itself. Hazel goes one layer up: join Okendo's review and rating data with your Shopify orders, ad spend, email engagement, and subscription data, and ask any cross-source question, not just the questions a dashboard was designed to answer.
Some brands pipe Okendo data into Zilliz via Fivetran for vector search on review content. That works if you have an engineer and an ongoing maintenance budget: schema, deduplication, embedding model, refresh cadence, and join logic to your other sources are all yours. Hazel is the managed alternative: same conversational outcome, no warehouse to operate.
Rather than waiting for a vendor MCP or stitching the Okendo API into your own agent, Hazel ingests your full review corpus into an analytical store, joins it with your Shopify orders, subscriptions, ads, and email data, and gives your team a single conversational interface for review-driven business questions. No MCP setup to manage, no per-prompt schema discovery, no rate limits, and the same agent answers questions across every source you've connected.
If you specifically want MCP access to Hazel itself, that's available too. Ping us at https://calendly.com/clint-dunn/clint-hazel-intro.
Yes. Paste your Okendo API key into Hazel, and Hazel ingests your full review history (ratings, written reviews, review attributes, reviewer profiles, and tags) refreshed every few hours.
Okendo's AI-Generated Review Summaries are designed for shoppers on the product page. A short blurb of pros and cons to drive add-to-cart. Hazel is built for your team behind the scenes: ask any business question about your review data, pull exact quotes for landing pages, correlate ratings with sales and refunds across Shopify, and segment by reviewer attributes. Different audience, different surface.
Okendo Analytics and Reporting tracks your Okendo program. Review request email performance, ratings generation rates, sentiment score, reward ROI. Hazel is the cross-source layer: it joins Okendo review data with Shopify orders, ad spend, email, and subscriptions, and answers business questions that span sources. Like whether low-rated products have higher return rates, or whether ad-acquired customers leave different reviews than organic.
The Zilliz + Fivetran path gives you vector search over Okendo review content, which is powerful if you have the engineering resources. You own the schema, dedup, embedding model, refresh cadence, and join logic. Hazel is the managed alternative: same conversational outcome, no warehouse to build or maintain, and cross-source joins to Shopify, ads, email, and subscriptions are built in.
Those are review platforms that include their own dashboards. Hazel is platform-agnostic and analyst-first: it connects to whichever review tool you're on, joins your reviews with the rest of your stack (orders, subscriptions, ads, email), and answers any question about your business, not just the questions the dashboard was designed to answer.
Not yet. Okendo's AI is in-app today (AI Summaries, AI Moderation, Smart Content Analysis, Quizzes Pro AI). Hazel is the analytics layer that fills the gap: it ingests your Okendo review data and makes it queryable alongside every other source you've connected.
Today Hazel ingests Okendo reviews, review attributes, reviewer profiles, and tags. Quizzes and Surveys data is not ingested. If your quiz or survey data matters for analytics, connect the underlying Shopify order data and Hazel can analyze conversion and retention patterns from the order side.
Roughly every 6 hours.
No. Hazel only reads. We never write to your reviews, your widget, or your review request flows.
Yes. You can ask for a short five-star review that mentions a specific ingredient, body area, or use case, and Hazel returns the actual review text so you can quote it on a PDP, in an email, or in a landing page.
Yes. This is one of the most common patterns. Connect both sources and you can ask whether lower ratings correlate with higher return rates, whether five-star reviewers subscribe at a higher rate, or whether a launch's ratings improved with each new batch.
Yes. Structured attributes (fit, quality, value, true-to-size, etc.), reviewer profile fields, and your review tags are all queryable. You can pivot any analysis by your existing Okendo conventions without writing SQL.
Book a call and we'll walk through your data, the questions you want to answer, and what the rollout looks like.
Hazel helps your team uncover new revenue, catch problems early, and make smarter, faster decisions before you even know what to ask.