Cannabis review schema

Review schema marks individual customer reviews with name, rating, date, and reviewer information. The aggregateRating property consolidates multiple reviews into an overall rating. When implemented correctly, your review count and average rating appear in search results.

The review date property is critical. Recent reviews are a stronger signal than old ones. Recent reviews are generally more valuable than a higher rating built on old reviews.

Review schema is structured data that identifies customer reviews, including ratings, dates, and reviewer names. Aggregate rating schema consolidates individual reviews into overall ratings that appear in search results and influence click-through behavior and ranking signals.

Cannabis retailers typically have reviews scattered across Yelp, Google Business Profile, Leafly, Weedmaps, and your website. Aggregating these into unified review schema is critical for search visibility.

Your aggregateRating property consolidates reviews from all sources into one overall rating. If you have reviews on both Google and Yelp, your aggregateRating should reflect the combined average.

our cannabis regulatory mapping helps aggregate reviews from Yelp, Google, Leafly, and Weedmaps automatically, pulling current ratings and updating your aggregateRating dynamically. Manual aggregation goes stale quickly.

The datePublished property for each review shows when it was written. Recent reviews are a stronger signal than old ones.

This creates a dynamic where active review generation (consistent new reviews) becomes more important than total review count. A dispensary earning steady new reviews can hold its own against a competitor with a large total but stale reviews.

Encourage customers to leave reviews frequently. Implement review request emails through Springbig or post-purchase automation. Make review-leaving easy, accessible through Google, Yelp, and your website.

Review recency matters alongside total review count. Cannabis dispensaries generating consistent monthly reviews can compete with rivals that have larger historical review counts.

Cannabis reviews often reference effects, potency, and personal preferences. A strain earning 3 stars from one customer might deserve 5 stars from another based on their needs. This creates legitimacy for varied ratings.

Customers appreciate honest reviews acknowledging strain characteristics. A review saying "Great for sleep, not for daytime use" provides more value than generic praise.

Don't be concerned if you have lower average ratings than competitors. Cannabis effects are personal. A slightly lower average with many recent reviews suggests diverse customer feedback reflecting real product variation.

Some cannabis reviews reference health conditions or sensitive personal information. If a review mentions "This helps my PTSD" or "I use this for my anxiety," leave it in. These are legitimate customer experiences.

However, if reviews make specific health claims beyond the reviewer's personal experience (e.g., "This cures PTSD"), you can edit them to reflect the reviewer's personal experience ("This helps me with my PTSD symptoms").

Never remove reviews because they mention health conditions or cannabis effects. These are protected speech and often reflect legitimate use cases.

Your schema should reflect your actual review moderation policy. If you remove reviews for being abusive or off-topic, disclose this. If you remove bad reviews for legitimate spam reasons, be honest about it.

Don't remove legitimate negative reviews. Customers expect some negative reviews. Ratings with zero negative reviews look fabricated.

Include not just your overall aggregateRating, but also ratingCount (total review count). The same rating backed by many reviews is more credible than one backed by a handful.

Show rating distribution if possible, such as how many reviews fall at each star level. This transparency prevents perception of rating manipulation.

Your review schema can include a reviewAspect property identifying what the review discusses (e.g., "Product Quality", "Customer Service", "Store Cleanliness"). This helps categorize reviews by topic.

Example: A review praising your staff could include reviewAspect: "Customer Service". A review criticizing product quality could include reviewAspect: "Product Quality".

This categorization helps customers find reviews relevant to their concerns.

Include both detailed reviews (several sentences) and brief reviews (one sentence). Long reviews provide depth; short reviews provide quick credibility signals.

Your reviewBody can be many sentences or just one sentence. Both have value in different contexts.

If competitors have higher average ratings, focus on recency, not total volume. Encourage recent reviews from your best customers. Highlight that your reviews are current while competitors' might be old.

Don't compete on fabricating reviews. Compete on service quality that naturally generates good reviews.

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• Back to Schema Markup Optimization Hub
• Business Schema for Cannabis
• Product Schema for Cannabis

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Schema.org's review specification enables automated rating display in search results, featured snippets, and knowledge cards, creating visibility multipliers for businesses with healthy review profiles. For cannabis dispensaries specifically, where regulatory restrictions limit marketing claims about product benefits, customer reviews become the primary mechanism for communicating product quality and effects to potential customers. Dispensaries with aggregated rating schemas from multiple platforms (Google, Yelp, Leafly) give shoppers a fuller picture than single-source review displays.

Recency rewards active review generation strategies. Dispensary SEO success depends on sustained review generation momentum, not only historical review volume, because inactive review profiles lose ground as competitors add newer reviews. That is why review management platforms like Springbig and Blaze have become essential infrastructure for competitive dispensaries.