ProvenExpert Reviews Scraper

What does ProvenExpert Reviews Scraper do?

ProvenExpert Reviews Scraper extracts public review profile data from ProvenExpert profile pages.

It saves company profile details, aggregate rating signals, recommendation rates, public categories, and the latest visible customer reviews.

Use it to monitor reputation, benchmark service providers, and export review evidence into spreadsheets, BI tools, or CRMs.

Who is it for?

🏢 Reputation agencies tracking client review profiles.

📈 SEO teams collecting social proof for local landing pages.

🛒 Ecommerce and service teams comparing review quality across providers.

🧑‍💼 Sales teams qualifying companies by public customer satisfaction.

🧪 Analysts building review-platform datasets for market research.

Why use this ProvenExpert scraper?

It uses the public profile page and does not require a ProvenExpert account.

It runs as an Apify Actor, so you can schedule it, call it from an API, or connect it to integrations.

It exports clean rows instead of forcing you to copy review snippets manually.

What data can you extract?

The dataset includes profile identity, aggregate metrics, reviewer details, review ratings, review text, and source URLs.

Profile summary rows use type = profile.

Review rows use type = review.

Data table

| Field | Description |

| --- | --- |

| type | profile or review row type |

| profileUrl | Canonical ProvenExpert profile URL |

| profileName | Public company or profile name |

| averageRating | Aggregate rating value |

| reviewCount | Public review count from structured data |

| recommendationRate | Recommendation percentage when available |

| reviewerName | Reviewer display name |

| reviewDate | Review publication date |

| reviewRating | Rating for the individual review |

| reviewBody | Review text |

| categories | Public tags and competencies |

How much does it cost to scrape ProvenExpert reviews?

The actor uses pay-per-event pricing.

A small start charge covers the run setup.

Each saved dataset item is charged as one result.

Keep the default prefill small while testing, then scale profiles once you verify the output matches your needs.

How to use ProvenExpert Reviews Scraper

1. Open the actor on Apify.

2. Paste one or more ProvenExpert profile URLs.

3. Optionally add profile slugs such as provenexpert-com.

4. Set the maximum number of reviews per profile.

5. Start the run and download the dataset as JSON, CSV, Excel, or via API.

Input

The main input is startUrls.

You can also use profileSlugs with the locale field.

Example input:

{

  "startUrls": [{ "url": "https://www.provenexpert.com/en-us/provenexpert-com/" }],

  "maxReviewsPerProfile": 20,

  "includeProfileSummary": true

}

Output

Example output item:

{

  "type": "review",

  "profileName": "ProvenExpert.com",

  "averageRating": 4.43,

  "reviewerName": "Anonymously",

  "reviewRating": 5,

  "reviewBody": "Helpful support and fast response.",

  "profileUrl": "https://www.provenexpert.com/en-us/provenexpert-com/"

}

Tips for best results

✅ Use full public profile URLs when possible.

✅ Keep includeProfileSummary enabled if you need aggregate metrics.

✅ Run the actor on a schedule to watch rating changes over time.

✅ Export CSV for quick stakeholder reports.

✅ Use slugs when your upstream system stores only profile identifiers.

Integrations

Connect the actor to Google Sheets for weekly review monitoring.

Send new review rows to Slack using an Apify integration webhook.

Load results into a CRM to enrich lead records with public reputation data.

Store historical datasets in S3 or BigQuery for long-term trend analysis.

API usage

Node.js

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });

const run = await client.actor("automation-lab/provenexpert-reviews-scraper").call({

  startUrls: [{ url: "https://www.provenexpert.com/en-us/provenexpert-com/" }],

  maxReviewsPerProfile: 20

});

console.log(run.defaultDatasetId);

Python

from apify_client import ApifyClient

client = ApifyClient("<APIFY_TOKEN>")

run = client.actor("automation-lab/provenexpert-reviews-scraper").call(run_input={

    "startUrls": [{"url": "https://www.provenexpert.com/en-us/provenexpert-com/"}],

    "maxReviewsPerProfile": 20,

})

print(run["defaultDatasetId"])

cURL

curl -X POST "https://api.apify.com/v2/acts/automation-lab~provenexpert-reviews-scraper/runs?token=$APIFY_TOKEN" \

  -H "Content-Type: application/json" \

  -d '{"startUrls":[{"url":"https://www.provenexpert.com/en-us/provenexpert-com/"}],"maxReviewsPerProfile":20,"includeProfileSummary":true}'

MCP usage

Use Apify MCP to call this actor from AI tools such as Claude Code, Claude Desktop, Cursor, and VS Code. The scoped MCP server URL is:

https://mcp.apify.com/?tools=automation-lab/provenexpert-reviews-scraper

Claude Code MCP setup

Add the actor as a scoped HTTP MCP tool from your terminal:

$claude mcp add apify-provenexpert-reviews --transport http "https://mcp.apify.com/?tools=automation-lab/provenexpert-reviews-scraper"

Then ask Claude Code to run the scraper with a profile URL or slug.

Claude Desktop MCP setup

Add this server to your Claude Desktop MCP configuration:

{
  "mcpServers": {
    "apify-provenexpert-reviews": {
      "url": "https://mcp.apify.com/?tools=automation-lab/provenexpert-reviews-scraper"
    }
  }
}

Cursor MCP setup

Add the same HTTP server to your Cursor MCP settings:

{
  "mcpServers": {
    "apify-provenexpert-reviews": {
      "url": "https://mcp.apify.com/?tools=automation-lab/provenexpert-reviews-scraper"
    }
  }
}

VS Code MCP setup

Add this server to .vscode/mcp.json or your user MCP configuration:

{
  "servers": {
    "apify-provenexpert-reviews": {
      "url": "https://mcp.apify.com/?tools=automation-lab/provenexpert-reviews-scraper"
    }
  }
}

Example prompt: "Scrape this ProvenExpert profile and summarize the latest negative review themes."

Example prompt: "Run the ProvenExpert Reviews Scraper weekly and compare aggregate rating changes."

Scheduling

Apify schedules let you run this scraper daily, weekly, or monthly.

For reputation monitoring, a weekly schedule is usually enough.

For launch campaigns or customer support incidents, run it daily until the review flow stabilizes.

Quality and limitations

The actor extracts public data visible in the ProvenExpert profile HTML.

It does not access private dashboards, hidden review moderation data, or account-only analytics.

Public profile pages may expose only the latest visible reviews in structured data.

Troubleshooting

The run saved only a profile row. Check that the public profile page currently exposes reviews in JSON-LD and that maxReviewsPerProfile is above 0.

The URL failed. Confirm the profile is public and reachable in a browser without login.

I need more history. Use multiple public profile URLs or run the actor regularly to build a historical archive over time.

Legality

This actor is designed for public ProvenExpert profile pages.

Review your use case, local laws, and ProvenExpert terms before scraping at scale.

Do not use scraped personal data for spam, harassment, or decisions that require legal compliance review.

Related scrapers

You may also need related reputation and review actors on Apify:

• https://apify.com/automation-lab/google-maps-reviews-scraper

• https://apify.com/automation-lab/trustpilot-reviews-scraper

• https://apify.com/automation-lab/sitejabber-reviews-scraper

• https://apify.com/automation-lab/reviews-io-scraper

FAQ

Can I scrape any ProvenExpert page? The actor is intended for public profile pages.

Do I need proxies? The MVP uses direct HTTP requests and does not require browser automation.

Can I export Excel? Yes, Apify datasets support XLSX, CSV, JSON, XML, RSS, and API access.

Can I monitor many profiles? Yes, add multiple URLs or slugs to the input.

Does it include profile summary data? Yes, enable includeProfileSummary.

Support

If a public profile does not parse correctly, share the profile URL and a run ID.

Include whether you expected profile metrics, review rows, or both.

We can adjust the extractor when ProvenExpert changes public page markup.

Field notes

• profileUrl is the public page that produced the row; sourceUrl helps audit redirects or locale changes.
• profileSlug is parsed from the final URL path segment and is useful for joining data to internal lists.
• profileImage comes from structured data or OpenGraph metadata when the page exposes it.
• overallGradeText mirrors ProvenExpert wording when present, while averageRating stays numeric for sorting.
• ratingCount and reviewCount can differ because platforms may count ratings and written reviews separately.
• recommendationRate is parsed from public page metadata when available.
• categories combines public tags and competency labels and is saved as a list in the raw JSON item.
• telephone is included only when public structured data exposes it.
• language is parsed from the HTML language attribute.
• scrapedAt is generated by the actor at save time so scheduled exports can be compared over time.