SmartCustomer Reviews Scraper
Pricing
from $0.27 / 1,000 review item extracteds
SmartCustomer Reviews Scraper
Scrape public SmartCustomer and legacy Sitejabber company reviews with ratings, review text, public reviewer metadata, and business metrics.
Pricing
from $0.27 / 1,000 review item extracteds
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0.0
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Developer
Fetch Cat
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3
Monthly active users
17 days ago
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Extract public SmartCustomer reviews and legacy Sitejabber review pages for reputation monitoring, complaint triage and competitor research. Export review text, star ratings, public reviewer details and available business metrics. No login is required.
Quick start
Enter a company domain and start with a small review limit:
{"companies": ["etsy.com"],"maxItems": 10,"maxReviewsPerCompany": 10}
Open the completed run’s dataset to inspect the reviews. Results depend on public availability and your filters. Source failures can leave partial results or fail the run.
Prefer a video guide? This short Apify walkthrough shows you how to set up and run an Actor. It uses a different Actor, but the setup steps are the same.
What you get
- Review records: Public titles, text, star ratings, dates and source links.
- Business context: Available aggregate ratings, review counts and category information.
- Flexible targets: SmartCustomer URLs, legacy Sitejabber links and company domains.
- Filters: Selected star ratings and visibly verified reviews.
Who is it for?
- Reputation researchers reviewing exposed feedback for selected brands.
- Customer-support teams grouping public complaints for their own triage.
- Ecommerce and market analysts comparing source-limited review samples.
- Trust and data teams retaining review evidence for separate reporting or analysis.
How you can use the data
- Prepare an Etsy complaint sample. Use the existing etsy.com recipe with one- and two-star filters and a small cap. Keep reviewUrl, title, body, rating and date for your own recurring-topic review, without treating a filtered sample as all customer sentiment.
- Compare Etsy and eBay with separate company caps. Use the existing two-domain recipe, keeping businessDomain and public aggregate context distinct from individual review ratings. Disable reviewer fields if unnecessary rather than inferring missing author details.
- Preserve a legacy company-page workflow. Supply the existing Sitejabber Etsy URL directly and retain sourceUrl with normalized SmartCustomer links. This accepts old review-page targets rather than providing private account access or a complete old archive.
- Join your own reputation snapshots. Keep reviewId, source links and collection time in your destination before producing comparisons or notifications. Review IDs may come from anchors or content, and visible verified markers are source labels rather than independent identity or claim verification. Sentiment scoring and alerts are downstream work.
Input settings
| Setting | JSON key | Use it for | Example |
|---|---|---|---|
| Review URLs | startUrls | SmartCustomer or legacy Sitejabber review pages. | https://www.smartcustomer.com/reviews/etsy.com |
| Company domains | companies | Convert domains into SmartCustomer review pages. | etsy.com |
| Maximum records | maxItems | Cap total saved review rows and spend. | 20 |
| Per-company limit | maxReviewsPerCompany | Keep batches balanced across companies. | 20 |
| Star ratings | ratings | Keep only selected ratings. | [1, 2] |
| Verified only | verifiedOnly | Keep visibly verified reviews only. | false |
| Business metrics | includeBusinessInfo | Include aggregate business context on each row. | true |
| Reviewer info | includeReviewerInfo | Include public reviewer display name/profile URL. | true |
| Request delay | requestDelay | Slow down pagination between pages. | 0 |
| Proxy | proxyConfiguration | Optional managed Apify Proxy. Direct by default, no automatic fallback. | { "useApifyProxy": false } |
Supply at least one company domain or review URL. Both lists can be combined. The form defaults to 20 total reviews and 20 per company. With limits omitted from an API input, the runtime uses 50 total and the same per-company limit.
Input recipes
Brand reputation monitor
{"companies": ["etsy.com"],"ratings": [1, 2],"maxItems": 20,"maxReviewsPerCompany": 20,"includeBusinessInfo": true,"includeReviewerInfo": true}
Competitor benchmark
{"companies": ["etsy.com", "ebay.com"],"maxItems": 30,"maxReviewsPerCompany": 15,"includeBusinessInfo": true,"includeReviewerInfo": false}
Legacy Sitejabber URL export
{"startUrls": [{ "url": "https://www.sitejabber.com/reviews/etsy.com" }],"maxItems": 50,"maxReviewsPerCompany": 50}
Output data
| Field | Description |
|---|---|
businessName | Company name shown on SmartCustomer. |
businessDomain | Business website domain. |
businessUrl | SmartCustomer business review page URL. |
categoryBreadcrumbs | Public category path for the business. |
overallRating | Aggregate SmartCustomer rating. |
totalReviews | Aggregate review count. |
ratingDistribution | Best-effort counts/percentages by star rating. |
keywordMentions | Best-effort public keyword mention chips when visible. |
reviewId | Stable review identifier from the review anchor or content hash. |
reviewUrl | Direct review URL when available. |
title | Review headline. |
body | Full public review text available on the page. |
rating | Review star rating. |
publishedDate | Review publication date. |
isVerified | Verified marker when visibly available. |
isUpdated | Updated marker when visibly available. |
reviewerName | Public reviewer display name. |
reviewerUrl | Public SmartCustomer reviewer profile URL when visible. |
helpfulCount, commentCount, mediaCount | Best-effort engagement/media counts when visible. |
sourceUrl | Original input that produced the record. |
scrapedAt | ISO timestamp for the scrape. |
Example record
The following is a synthetic shape-only excerpt, not a newly collected review:
{"businessDomain": "example.com","businessUrl": "https://www.smartcustomer.com/reviews/example.com","reviewId": "illustrative-id","title": "Illustrative review title","body": "Illustrative public review text.","rating": 4,"publishedDate": null,"reviewerName": null,"reviewerUrl": null}
Optional values can be null. Lists can be empty. Disabling business or reviewer information leaves the corresponding fields empty.
Download your results
Open your run's dataset, choose Export and select JSON, CSV or Excel. JSON keeps nested fields together. CSV and Excel are useful when you want to review the records in a spreadsheet.
See Apify's download and export guide for the available formats and field options.
Pricing
A one-time start event is charged when a run begins. An item event is charged for each saved public review record.
Empty results do not incur review-item charges. The start charge can still apply. Use maxItems and maxReviewsPerCompany to bound saved results.
See the live Pricing tab for current rates and discounts.
Tips for best results
- Start with domains:
companies: ["etsy.com"]is the simplest way to target a business page. - Use legacy links directly: Old
sitejabber.com/reviews/...links are accepted and normalized. - Filter low ratings: Use
ratings: [1, 2]for complaint monitoring and support triage. - Keep batches bounded: Use
maxReviewsPerCompanyto avoid one company consuming the full run. - Expect public-page limits: The Actor only exports data publicly visible on SmartCustomer review pages.
Limits and caveats
- Public data only. No login, private account data or guaranteed complete archive.
- Filters can return no matches. Check the target page and relax star-rating or verified-only filters when appropriate. Legitimate empty results succeed.
- Partial results are possible. Missing business metadata does not prevent available reviews from being saved. Failed sources are reported in
RUN_SUMMARY. If all sources fail, the run fails. - Optional fields vary. Location, responses, media counts and verification markers depend on what the source provides.
- Connection settings. Direct access is the default. The existing proxy setting can explicitly select managed Apify Proxy for the whole run. It is not an automatic fallback. Custom proxy URLs are not used by this Actor.
Automation and integrations
Save your settings for next time
Once you have an input that works for you, save it as an Apify task. This keeps your settings together so you can use them again without filling in the form from scratch.
Run on a schedule
Need fresh results regularly? You can schedule the Actor or a saved task to run at a time that suits you.
Each scheduled run collects the data again. If you want to compare results or highlight changes, add that step in your own workflow.
Send results to your other tools
Use n8n, Make or Zapier to connect this scraper to the rest of your workflow. For example, you could pass its results to an AI assistant or add records to a spreadsheet. Follow the Apify integration guides for your chosen tool.
For a custom connection, an Apify webhook can notify your app when a run finishes or fails. Your app can then fetch the results or handle the failure.
API usage
Want to collect this data from your own app or automation? The examples below send input to the scraper and show how to collect its results.
The Node.js and Python examples wait for the run to finish before reading its results. The cURL example starts the run and returns its details. Wait for that run to finish, then use its defaultDatasetId to fetch the results.
For setup instructions, see Apify's JavaScript client guide, Python client guide and Actor runs API reference.
cURL
curl -X POST "https://api.apify.com/v2/acts/fetch_cat~smartcustomer-reviews-scraper/runs" \-H "Authorization: Bearer $APIFY_TOKEN" \-H 'Content-Type: application/json' \-d '{"companies":["etsy.com"],"maxItems":10}'
Node.js
import { ApifyClient } from 'apify-client';const client = new ApifyClient({ token: process.env.APIFY_TOKEN });const run = await client.actor('fetch_cat/smartcustomer-reviews-scraper').call({companies: ['etsy.com'],maxItems: 10});const { items } = await client.dataset(run.defaultDatasetId).listItems();console.log(items);
Python
from apify_client import ApifyClientimport osclient = ApifyClient(os.environ['APIFY_TOKEN'])run = client.actor('fetch_cat/smartcustomer-reviews-scraper').call(run_input={'companies': ['etsy.com'],'maxItems': 10,})items = client.dataset(run['defaultDatasetId']).list_items().itemsprint(items)
MCP and AI agents
You can ask your AI assistant to collect data with SmartCustomer Reviews Scraper and help you work with the results. The scraper returns the data, and your assistant can then summarize it, compare records or prepare notes.
Connect your assistant through the Apify MCP server. MCP gives your assistant a way to find this scraper, run it and read the results. Follow the official setup and sign-in guide for your app.
Easier setup with an Apify plugin
If you use a supported coding assistant, the official Apify plugin can set up the connection for you. It connects your assistant to Apify and includes instructions for common tasks. Follow the guide for your particular app.
Use Apify AI in Console
Prefer to keep everything in Apify? Open Apify AI in Console and ask it to find Fetch Cat's SmartCustomer Reviews Scraper. You can describe the data you want and ask questions about the results.
Apify AI is currently in beta. It asks for confirmation before starting an Actor, and normal run charges apply.
Choose your assistant
- Claude and Claude Code (Anthropic): Apify setup guide.
- ChatGPT and Codex (OpenAI): Apify setup guides.
- Grok Bot (xAI): Apify plugin guide.
- Gemini CLI (Google): MCP server setup guide. Use the server URL below with the HTTP configuration supported by Gemini CLI.
Connect just this scraper
To keep your setup focused on this scraper, add this server configuration to a compatible MCP client:
{"mcpServers": {"apify": {"url": "https://mcp.apify.com?tools=fetch_cat/smartcustomer-reviews-scraper"}}}
Sign in to Apify when your client asks. If your client uses a Bearer token instead, follow its setup guide and keep the token in its secure configuration. Configuration formats vary by app, so use the linked guide if your client needs a different format.
Use Apify's general server
Already connected to the general Apify MCP server at https://mcp.apify.com? You can use it to find this scraper without adding another server. Ask your assistant to use SmartCustomer Reviews Scraper by Fetch Cat, or give it the identifier fetch_cat/smartcustomer-reviews-scraper.
Your assistant can check the available settings and retrieve the results from the returned run. If the run is still working, it should follow that run rather than start it again. Both connection options use Apify's hosted service.
Example requests
- “Use Fetch Cat’s SmartCustomer Reviews Scraper to collect up to 5 one- or two-star Etsy reviews with a five-review company cap and direct access. Keep source links, titles, dates and public text for my complaint summary without claiming complete sentiment coverage.”
- “Collect up to 3 public reviews each for Etsy and eBay with a six-row total cap, business context on and reviewer details off. Keep companies separate and report source failures rather than assuming equal samples.”
- “Retrieve up to 5 public reviews from https://www.sitejabber.com/reviews/etsy.com with a five-review company cap and direct access. Keep normalized review links, ratings and dates without private access or automatically creating monitoring alerts.”
Normal Apify charges apply. Check the live Pricing tab before asking your assistant to run a larger batch.
Pay with x402
If your AI agent has a funded wallet, it can pay for Apify usage through x402. This experimental option lets an agent use Apify without a conventional account.
Apify AGI provides a prepaid API token with a spending cap after payment. Your agent can use that token to run this scraper through the Apify API or an authenticated MCP connection.
Some MCP setups also support paying for each request directly. That is a different payment option, so check the official guide for its availability.
Follow the official guide for wallet setup, supported payment options and current terms. Apify handles the payments. Keep wallet keys and payment tokens in your agent's secure configuration.
Other ways for agents to pay
Apify also supports MPP for prepaid access through AGI and Skyfire for eligible Actors. If your agent already uses one of these, see the agentic payment guide to choose the right setup.
FAQ
Can I use old Sitejabber links?
Yes. Supply the legacy company-review URL in startUrls, or enter the company domain in companies.
Can I export to CSV or use this as an API alternative?
Yes. Export the dataset in Console or retrieve it through the Apify API. This is an independent scraper, not an official SmartCustomer API.
Can I keep only negative reviews?
Use ratings: [1, 2]. Filters apply to the available reviews and can produce an empty result.
Why are some fields null?
Some public details are absent from the source. Disabling optional business or reviewer information also leaves those fields empty.
Can I use it with an AI assistant?
Use Apify’s hosted MCP setup above. The scraper collects records, and your assistant can analyze them afterward.
Related Actors
- Google Maps Reviews Scraper for local business reviews.
- Trustpilot Reviews Scraper for Trustpilot reputation monitoring.
- Google Play Reviews Scraper for mobile app reviews.
- Facebook Reviews Scraper for public Facebook recommendation data.
- Booking Reviews Scraper for hotel and accommodation reviews.
Support and feedback
For custom additions or integrations, email hello@fetchcat.dev.
Found an error or have a feature request? Open an issue with the run URL, a non-sensitive input example and what you expected.
Need help sharing it? See Apify’s guide to sharing a run when reporting an issue. Sharing a run can give the developer access to its input, logs and results, so use a run that contains no sensitive data. Please leave out API tokens, passwords, cookies, private documents and personal data. Use a public sample URL or a redacted example instead.
Tried this scraper? We'd love to hear how it worked for you. Leave a review to help others choose the right tool and help us improve it. Your feedback means a lot to us.
Made with care for curious people, AI agents and the possibilities in data. ♥