Vitacost Product Reviews Scraper

Extract public Vitacost product reviews into structured JSON, CSV, Excel, or API-ready datasets.

Turn product pages into rows containing review text, star ratings, buyer verification, dates, helpful votes, media, replies, transparency signals, and product-level rating summaries.

Use the actor for supplement sentiment research, quality monitoring, competitive intelligence, voice-of-customer analysis, and recurring review alerts.

What does Vitacost Product Reviews Scraper do?

The actor accepts Vitacost product URLs or numeric product IDs.

It resolves each product, reads its public review summary, follows all required review pages, and saves one row per review.

Each row is self-contained and includes:

• ⭐ Star rating and review title
• 💬 Plain text and original HTML body
• 👤 Public reviewer name and review date
• ✅ Verified-buyer and anonymous-reviewer flags
• 👍 Helpful and unhelpful vote counts
• 🖼️ Public review pictures and videos
• 🏷️ Syndication source and transparency badges
• 📝 Recommendation answers and merchant replies
• 📦 Product ID, name, URL, and image
• 📊 Average rating, review count, and star histogram

Who is it for?

Supplement and CPG brands

Track customer language around efficacy, taste, packaging, dosage, delivery, and repeat purchase intent.

Marketplace sellers

Compare customer feedback across competing products before choosing inventory, positioning, or bundles.

Consumer-insights teams

Build review corpora for topic modeling, sentiment classification, complaint taxonomy, and trend analysis.

Agencies

Create recurring client reports without copying review pages manually.

Product and quality teams

Monitor newest low-star feedback for emerging defects, packaging failures, or expectation gaps.

Why use this Vitacost review extractor?

Manual review collection is slow and difficult to reproduce.

This actor provides stable review UUIDs for deduplication and repeat monitoring.

It uses public structured review data instead of brittle visual page automation.

Benefits include:

• Fast HTTP-only extraction
• No Vitacost login required
• URL and product-ID inputs
• Automatic pagination
• Stable review UUID deduplication
• Rating and verified-buyer filters
• Predictable per-review pricing
• Apify datasets, webhooks, schedules, API, and integrations

What data can you extract?

Field	Description
reviewId	Stable public review UUID
title	Review headline
body	Clean plain-text review
bodyHtml	Original public review HTML
rating	One-to-five star score
reviewerName	Public display name
reviewDate	ISO review timestamp
verifiedBuyer	Verified-purchase marker
anonymousReviewer	Anonymous reviewer marker
source	Syndicated source when disclosed
transparencyBadges	Public provenance labels
recommendation	Recommendation answer when present
customAnswers	Other public review-form answers
reply	Merchant reply when present
helpfulVotes	Helpful vote count
unhelpfulVotes	Unhelpful vote count
pictures	Public review image URLs
videos	Public review video identifiers
productId	Vitacost/Judge.me product ID
productName	Product title
productUrl	Canonical product URL when available
productImageUrl	Main product image
averageRating	Current product average
reviewCount	Current public review count
ratingHistogram	Counts and percentages by star
scrapedAt	UTC extraction time

How to scrape Vitacost reviews

1. Open the actor in Apify Console.
2. Add one or more Vitacost product URLs.
3. Optionally add numeric product IDs.
4. Set the maximum reviews per product.
5. Choose rating or verified-buyer filters.
6. Select newest, highest-rating, or lowest-rating order.
7. Click Start.
8. Export the dataset as JSON, CSV, Excel, XML, or RSS.

A prefilled run collects only 10 reviews, making the first test quick and inexpensive.

Input

{
  "startUrls": [
    {
      "url": "https://www.vitacost.com/products/vitacost-vitamin-d3-mini-gels-125-mcg-5-000-iu-365-softgels-158727"
    }
  ],
  "maxReviewsPerProduct": 100,
  "ratings": [1, 2, 3, 4, 5],
  "verifiedOnly": false,
  "sortBy": "newest"
}

You may combine URLs and IDs in one run.

Supported URLs must begin with https://www.vitacost.com/products/.

Invalid domains and non-product paths fail closed.

Input options

Vitacost product URLs

Use current product-detail URLs copied from Vitacost.

Tracking query parameters and fragments are removed automatically.

Product IDs

Use 8–20 digit product IDs when you already have catalog identifiers.

The actor verifies that the response product ID matches the requested ID.

Maximum reviews per product

Set a separate cap for each supplied product.

Use 10–50 for quick research and a larger limit for full-history analysis.

Ratings

Keep any combination of one through five stars.

Leave the list empty to collect all ratings.

Verified buyers only

Enable this option to retain reviews carrying a public verified-purchase marker.

Review order

Choose newest first for monitoring, highest first for advocacy research, or lowest first for issue discovery.

Output example

{
  "reviewId": "2cd2ec3f-55c7-4426-a24d-f4dabc59c8df",
  "title": "A must Vit",
  "body": "Everyone needs a good D3...",
  "rating": 5,
  "reviewerName": "Manaman850",
  "reviewDate": "2025-12-18T09:07:21.000Z",
  "verifiedBuyer": false,
  "recommendation": "Yes",
  "helpfulVotes": 0,
  "productId": "10390054928699",
  "productName": "Vitacost, Vitamin D3 Mini Gels, 125 mcg (5,000 IU), 365 Softgels",
  "averageRating": 4.84,
  "reviewCount": 425
}

Fields remain typed and stable across URL and ID inputs.

How much does it cost to scrape Vitacost product reviews?

This actor uses pay-per-event pricing.

A small one-time start charge covers run initialization.

You then pay only for review rows saved to the dataset.

The current base prices are $0.005 per run start and $0.000047578 per review on the Bronze tier, with lower per-review prices on larger Apify plans.

The input cap gives you direct control over total spend.

Apify shows an estimated and final charge for each run.

Review monitoring workflow

Schedule the actor daily or weekly with sortBy set to newest.

Store previously seen reviewId values in your database.

On each run:

1. Fetch the newest reviews.
2. Ignore UUIDs already stored.
3. Alert on new one- or two-star reviews.
4. Route high-priority complaints to quality or support teams.
5. Aggregate repeated themes in your BI system.

Sentiment analysis workflow

Export title, body, rating, and recommendation to your NLP pipeline.

Use rating as a weak supervision label.

Group sentiment by product, date, source, or verified-buyer status.

The transparencyBadges and source fields help distinguish syndicated feedback from direct submissions.

Competitor research workflow

Run the same review cap for multiple products.

Compare:

• Average rating and review volume
• Star-rating distributions
• Common complaint phrases
• Recommendation rates
• Helpful negative reviews
• New feedback velocity
• Syndicated-review provenance

Repeat on a schedule to detect product launches or quality shifts.

Integrations

Google Sheets

Use Apify's Google Sheets integration to append review rows to a shared research workbook.

Slack and email

Trigger a webhook when a run finishes, then alert on new low-star UUIDs.

Make and Zapier

Connect dataset items to CRM, support, reporting, or content-classification workflows.

BigQuery and data warehouses

Load normalized review rows for time-series and cross-product analysis.

Webhooks

Send run completion events to your API and fetch the default dataset by run ID.

Run from the Apify API with JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('automation-lab/vitacost-product-reviews-scraper').call({
  startUrls: [{ url: 'https://www.vitacost.com/products/vitacost-vitamin-d3-mini-gels-125-mcg-5-000-iu-365-softgels-158727' }],
  maxReviewsPerProduct: 50,
  sortBy: 'newest'
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Run from the Apify API with Python

from apify_client import ApifyClient

client = ApifyClient('YOUR_APIFY_TOKEN')
run = client.actor('automation-lab/vitacost-product-reviews-scraper').call(run_input={
    'productIds': ['10390054928699'],
    'maxReviewsPerProduct': 50,
    'verifiedOnly': True,
})
items = client.dataset(run['defaultDatasetId']).list_items().items
print(items)

Run with cURL

curl -X POST \
  "https://api.apify.com/v2/acts/automation-lab~vitacost-product-reviews-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"productIds":["10390054928699"],"maxReviewsPerProduct":20}'

Poll the returned run ID or use an Apify webhook for completion.

Use with Apify MCP

Connect AI assistants through Apify MCP.

Claude Code setup

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

Example prompt:

Extract the newest 30 reviews for this Vitacost product and summarize repeated quality complaints with source review UUIDs.

Claude Desktop setup

Add the following remote MCP server configuration:

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

Example prompt:

Compare one-star and five-star themes for product ID 10390054928699 and return a concise evidence table.

Cursor setup

Open Settings → Tools & MCP, add a remote MCP server, and use the same JSON configuration and URL above.

VS Code setup

Open the MCP server settings for your AI extension and add the same apify remote server URL shown above.

Tips for reliable results

• Use canonical Vitacost product-detail URLs.
• Start with 10 reviews before scaling a workflow.
• Use product IDs when your catalog already stores them.
• Keep stable reviewId values for incremental monitoring.
• Filter after a broad test if you are unsure whether verified reviews exist.
• Use newest-first order for scheduled jobs.
• Keep the product URL alongside exported rows for traceability.

Troubleshooting

Why did my run return no matching reviews?

Your rating or verified-buyer filters may exclude every available review.

Relax the filters and rerun with a low cap to inspect the current product mix.

Why was my URL rejected?

The actor accepts only HTTPS product-detail URLs on www.vitacost.com.

Collection pages, search pages, other domains, and malformed URLs are rejected to prevent wrong-scope output.

Why is a product URL missing for an ID lookup?

A no-review product may not expose a canonical path in the public review response.

Rows with reviews normally include a public relative product path that the actor converts to an absolute URL.

Can I scrape every review?

Yes. Set maxReviewsPerProduct above the product's public review count, up to the input maximum.

Data quality and limitations

The actor extracts publicly visible review data supplied by Vitacost's review widget.

Optional fields may be null or empty when a reviewer did not provide them.

Verified-buyer and transparency fields reproduce public labels; they are not independent identity verification.

Review counts and averages reflect the source at extraction time.

Vitacost or its review provider may change public fields without notice.

Is it legal to scrape Vitacost reviews?

The actor accesses public product-review information without logging in.

Your use must comply with applicable laws, contracts, privacy obligations, and Vitacost's terms.

Avoid collecting more data than needed.

Do not use public reviewer information for harassment, sensitive profiling, or unsolicited contact.

Consult legal counsel for regulated or high-risk use cases.

FAQ

Does it require a Vitacost account?

No. The supported review surface is public.

Does it use a browser?

No. It uses lightweight HTTP extraction for lower cost and faster startup.

Can it scrape multiple products?

Yes. Supply multiple URLs, IDs, or both.

Are duplicate reviews removed?

Yes. Stable review UUIDs are deduplicated across the run.

Can I export CSV or Excel?

Yes. Use the dataset export controls or dataset API.

Can I filter by date?

Date filtering is not a current input. Use newest-first order and filter reviewDate in your downstream workflow.

Can I collect product questions?

No. This actor intentionally emits one entity type: product reviews.

Related scrapers

Combine this actor with other automation-lab actors for broader commerce research.

• Amazon Reviews Scraper
• Walmart Reviews Scraper
• Chewy Product Reviews Scraper
• Costco Product Reviews Scraper

Support

If a valid Vitacost product stops returning public reviews, open an issue from the actor page.

Include the product URL, input, run ID, expected behavior, and observed result.

These details make source changes faster to reproduce and fix.