Whatnot Seller Reviews: How to Check a Whatnot Seller

A 4.9-star badge on Whatnot tells you very little before a $300 bid. Is it based on 40 reviews or 4,000? Are recent buyers complaining about slow shipping? Does the seller reply to problems or ignore them? Those answers are in the reviews, but scrolling through them in the app is slow and you can’t sort or filter.

This guide shows how to pull a seller’s reviews into a spreadsheet with the Whatnot Seller Review Scraper, what to look for, and when to use the full Whatnot Scraper instead.

What you get for each review

Each review becomes one flat row, which works well in Excel or Google Sheets:

Field	Meaning
sellerId, sellerUsername	Which seller the review belongs to
averageRating	The seller’s overall star rating
ratingOverall	This buyer’s overall rating
ratingShipping	This buyer’s shipping rating
overallReview	The review text
reviewedBy	The buyer’s username
reviewedOn	When the review was posted
sellerResponse	The seller’s reply, if any
fetchedAt	When you collected it

Sample record:

{
  "sellerId": "41626782",
  "sellerUsername": "club404",
  "averageRating": 5,
  "overallReview": "Achat nikel et envoie rapide. Une petite tâche sur la J4RM à l'arrivé mais rien de méchant et dû au transporteur...",
  "reviewedOn": "Sun, 17 May 2026 12:58:02 GMT",
  "ratingOverall": 5,
  "ratingShipping": 5,
  "reviewedBy": "lassyl",
  "sellerResponse": null,
  "fetchedAt": "2026-05-17T17:55:38.061Z"
}

Scrape a seller’s reviews in 3 minutes

1. Copy the seller’s username from their Whatnot profile, the part after whatnot.com/user/.
2. Open the Whatnot Seller Review Scraper and click Try for free.
3. Paste this input, replacing the usernames:

{
  "sellerUsernames": ["club404", "ah_sneakers"],
  "maxReviewsPerSeller": 200
}

4. Click Start. When it finishes, export the dataset as CSV or Excel.

If you have numeric IDs, use sellerUserIds instead. maxReviewsPerSeller defaults to 100. A couple of hundred recent reviews is enough to judge a seller, but raise it if you want their full history.

No Whatnot login is needed.

How to read the results

Once the reviews are in a sheet, five checks cover most of what matters:

1. Volume. Count rows per sellerUsername. A perfect score from 15 reviews tells you much less than 4.8 from 2,000.
2. Recent trend. Sort by reviewedOn and average ratingOverall for the last 30 to 50 reviews. A seller who was great last year and is slipping now is a real risk.
3. Shipping. Average ratingShipping separately. Shipping is the most common complaint on Whatnot and often drops before the overall score does.
4. Low-star text. Filter ratingOverall <= 3 and read every one. Look for repeated words such as “never arrived”, “damaged”, “not as described”, “wrong card”, “slow” or “no response”.
5. Seller replies. Check how many low-star reviews have a sellerResponse. A seller who replies calmly and offers a fix is usually safe. Silence or arguing with buyers is a warning sign.

One caveat applies to all of this: the reviews come from buyers who chose to leave one, so treat them as a sample rather than a complete record. A few repeated complaints on the same theme matter more than one angry outlier.

Check several sellers at once

Put every seller you’re considering in one run and build a quick comparison in Python:

import os
import pandas as pd
from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("epicscrapers/whatnot-seller-review-scraper").call(run_input={
    "sellerUsernames": ["club404", "ah_sneakers", "another_seller"],
    "maxReviewsPerSeller": 200,
})
df = pd.DataFrame(client.dataset(run["defaultDatasetId"]).iterate_items())

summary = df.groupby("sellerUsername").agg(
    reviews=("ratingOverall", "size"),
    avg_overall=("ratingOverall", "mean"),
    avg_shipping=("ratingShipping", "mean"),
    low_star=("ratingOverall", lambda r: (r <= 3).sum()),
    replied=("sellerResponse", lambda s: s.notna().sum()),
)
print(summary.sort_values("avg_overall", ascending=False))

Or with cURL, getting the rows back in a single call:

curl -X POST \
  "https://api.apify.com/v2/acts/epicscrapers~whatnot-seller-review-scraper/run-sync-get-dataset-items?token=$APIFY_TOKEN&format=csv" \
  -H "Content-Type: application/json" \
  -d '{"sellerUsernames":["club404"],"maxReviewsPerSeller":100}'

When to use the full Whatnot Scraper

Reviews tell you how buyers felt. If you also want the seller’s numbers, run the Whatnot Scraper in seller mode:

{
  "mode": "seller",
  "usernames": ["club404"],
  "includeProfile": true,
  "includeReviews": true,
  "includeShows": true,
  "includeShop": true,
  "showStatus": "upcoming",
  "maxReviews": 50,
  "maxShows": 10,
  "maxListings": 20
}

This returns one record per seller with profile metrics: followers, sold count, rating, review count, verification status and average shipping days. Upcoming shows, current shop listings and a review sample come back as nested arrays. A seller with 20,000 items sold, verification and a two-day average shipping time is a different risk from a new account with 30 sales.

As a rule, use the review scraper for review analysis in spreadsheets and the full scraper for a complete seller profile. The Whatnot scraper guide covers every mode.

Who uses this

• Buyers check a seller before a high-value bid or a big break.
• Sellers benchmark their shipping scores and review volume against competitors in their category.
• Breakers and wholesalers vet suppliers and partners before sending money.
• Analysts track how seller reputation changes across a category over time.

If you’re comparing sellers on price as well, pair this with Whatnot price tracking.

FAQ

How do I check if a Whatnot seller is legit?

Look at review volume, the trend in their recent ratings, the average shipping rating, what low-star reviews say, and whether the seller replies. Add sold count and verification status from seller mode. All of these come from public data you can export in minutes.

Can I see all reviews for a Whatnot seller?

Yes. Set maxReviewsPerSeller higher than the seller’s review count and the scraper pages through all of them.

Is it okay to scrape Whatnot reviews?

The scraper collects public reviews without logging in. Use them to evaluate sellers. Don’t use buyer usernames for contact lists or profiling, and follow Whatnot’s terms and privacy laws like GDPR. This isn’t legal advice.

Does Whatnot have a reviews API?

No public one. Exporting the reviews from public seller profiles is the practical way to get them.

Check your next seller

Paste the usernames, export the reviews and spend two minutes in a spreadsheet before you bid. Run the Whatnot Seller Review Scraper on Apify.