Etsy Reviews Sentiment Analyzer — Shop Sentiment, Themes & Star Breakdown

Turn raw Etsy reviews into insight. Point the actor at one or more shops (by name, URL, or ID — or discover them by keyword) and get a per-shop sentiment report: an overall sentiment score, positive/negative/neutral counts, the star distribution, and the most common praise and complaint themes. Optionally export every individual review tagged with its own sentiment. No API key, no Etsy login required.

What Data You Get

Per-shop summary

Field	Description
shop_name, shop_url, shop_id	Shop identity
total_reviews_on_etsy	Total reviews the shop has
reviews_analyzed	How many were analyzed this run
avg_rating	Average star rating of analyzed reviews
sentiment_score	−1 (very negative) to +1 (very positive)
sentiment_label	very_positive … very_negative
positive_count / neutral_count / negative_count	Review breakdown
photo_review_pct	% of analyzed reviews that include a buyer photo
response_rate_pct	% of reviews the seller replied to
star_percents	Etsy's 1–5 star distribution
top_positive_themes	Most common praise keywords
top_negative_themes	Most common complaint keywords

Optional per-review rows (emitReviews)

rating, sentiment, language, review, listing_id, has_photo, helpful_votes, has_seller_response, listing_title, review_date.

Use Cases

• Competitor research — see exactly what a rival's customers love and hate.
• Product insight — surface recurring complaints (shipping, quality, sizing).
• Shop audit — benchmark your own shop's sentiment against others.
• Due diligence — vet a supplier or partner before working with them.

How to Use

1. Add shops (names, URLs, or IDs) — or set a Search Query to find them.
2. Choose Max Reviews Per Shop (default 100).
3. Toggle Emit Individual Reviews if you want every review row.
4. Run.

Example Input

{
    "shops": ["CandlesandFavors"],
    "maxReviewsPerShop": 100,
    "emitReviews": false,
    "language": "en"
}

Example Output (shop summary)

{
    "row_type": "shop_summary",
    "shop_id": 5588285,
    "shop_name": "CandlesandFavors",
    "shop_url": "https://www.etsy.com/shop/CandlesandFavors",
    "total_reviews_on_etsy": 12235,
    "reviews_analyzed": 100,
    "avg_rating": 4.86,
    "sentiment_score": 0.93,
    "sentiment_label": "very_positive",
    "positive_count": 94,
    "neutral_count": 3,
    "negative_count": 3,
    "photo_review_pct": 18.0,
    "response_rate_pct": 12.0,
    "star_percents": { "five": 95, "four": 2, "three": 1, "two": 1, "one": 1 },
    "top_positive_themes": ["quality", "fast", "beautiful", "cute", "perfect"],
    "top_negative_themes": ["shipping", "late", "broken"],
    "scraped_at": "2026-06-09T00:00:00Z"
}

Scheduling & Automation

Track how a shop's sentiment shifts over time:

1. Open your run → Schedule tab, set a CRON expression.
2. Add a webhook to POST summaries to your dashboard or sheet.

POST https://api.apify.com/v2/acts/axlymxp~etsy-reviews-sentiment-analyzer/runs
Authorization: Bearer YOUR_API_TOKEN

Use with AI Agents (MCP)

Available on Apify's MCP Server — connect to Claude or ChatGPT and ask "what do customers complain about most in this shop?"

FAQ

How is sentiment calculated? A transparent rule-based model: 4–5★ = positive, 3★ = neutral, 1–2★ = negative. The shop score is the mean rating mapped to −1..+1. Themes come from keyword frequency in positive vs. negative reviews.

Can I analyze reviews in one language only? Yes — set the language field (e.g. en) to filter.

Do I need an Etsy API key? No.

Can I export individual reviews? Yes — enable Emit Individual Reviews to get one labeled row per review.