Thingtesting Scraper - Brands, Reviews & Daily Changes

Scrape Thingtesting, the directory of roughly 39,000 emerging D2C consumer brands, into a structured, delta-aware daily feed. Every row carries the brand profile, founders, socials, competitors, aggregate consumer signal and individual reviews, with change annotations against your last snapshot so you only pay to enrich what actually moved.

Built for D2C investors tracking early deal flow, competitive-intelligence teams inside consumer brands, PR and affiliate agencies building prospect lists, and brand-strategy consultancies mapping category velocity.

Why use this Thingtesting scraper

D2C deal-flow monitoring. Sort by Created and watch new brand launches land the day they go public. Scouts and early-stage investors get a timestamped feed of newly indexed brands with founders, socials and initial review velocity attached.

Competitive intelligence. Every row includes the alternatives Thingtesting lists (nearest N named competitors plus the total size of the competitive set). Track how a category expands and spot emerging challengers before trade press does.

PR and affiliate prospecting. Filter by category, review velocity or ships-to region to build outbound lists of brands worth pitching. Founder names, social handles and websites are on every row.

Velocity and sentiment tracking. Review counts in the last 7, 30 and 90 days, incentivised-review share, share mentioning a downside, and 4-5 vs 1-2 star split give a per-brand velocity and polarisation signal you can trend week over week without re-enriching the whole catalogue.

How to use

1. Pick order and mode. Use Created + new-and-changed for daily deal-flow monitoring, or MostReviewed + all for a one-off snapshot of the biggest brands.
2. Turn on incremental snapshotting. Keep incremental: true and set stateStoreName to a named key-value store (the default unnamed store is wiped every run, breaking deltas).
3. Set your caps. maxBrands limits enriched rows written; maxScanned limits how deep the cheap list-walk goes. Keep maxScanned well above maxBrands.
4. Run it. Inspect the Dataset tab, pick a view, then schedule it daily from the Actor page's right rail.

How a run works

1. Scan, walks the brand list 20 records per request. The list payload already carries the review summary and product count, so change detection costs almost nothing.
2. Diff, compares each brand with the snapshot held in a NAMED key-value store and labels it: new, new_reviews, rating_change, catalog_change, marked_rip, revived or unchanged.
3. Enrich, fetches full profiles only for the brands you asked for (new, changed or all): company data, founders, socials, certificates, rating distribution, products, alternatives and individual reviews.

What you get per brand

• Identity and positioning: title, slug, Thingtesting URL, website, status, categories, description, brand story, AI review summary, image
• Company: founders, founder demographics, HQ location, dates founded / launched, certificates, ships-to, all social profiles
• Aggregate consumer signal: average rating, ratings count, would-recommend percent, full 1-5 rating distribution, 4-5 star share, 1-2 star share, polarisation index
• Catalogue: product count plus a sample of products with images and outbound links
• Competitive set: total number of alternatives Thingtesting lists, plus the nearest N named alternatives
• Review-level signal: reviews sampled, average stars of the sample, review counts in the last 7 / 30 / 90 days, newest review date, top review tags, incentivised share, share mentioning a downside, share with photos
• Individual reviews: stars, liked and disliked verbatims, tags, publish date, incentivised flag, helpful / clap / read / reply counts, photos, author username, author review count and level
• Change tracking: what changed, new reviews since last run, previous ratings count and rating, rating delta, previous product count, first seen, previously seen, days since last seen

Dataset views

Brands, Daily changes, Review signal, Review verbatims, Alternatives, All fields.

Set Also push reviews to their own dataset to additionally write one row per review into a named dataset, easier to load into a warehouse than nested arrays.

Recommended daily schedule input

{
  "mode": "new-and-changed",
  "order": "Created",
  "maxBrands": 500,
  "maxScanned": 2000,
  "stopAfterConsecutiveUnchanged": 60,
  "includeAlternatives": true,
  "includeReviews": true,
  "maxReviewsPerBrand": 20,
  "incremental": true,
  "stateStoreName": "thingtesting-scraper-state",
  "useApifyProxy": true
}

A day with no changes finishes in a few seconds and costs effectively nothing, because unchanged brands are never re-enriched.

Pricing / Cost estimation

Pay-per-event pricing:

• Actor start: $0.005 per run.
• Brand delivered: $0.002 per enriched brand pushed to the dataset.

No per-request or per-page charges. Costs come only from brands actually delivered.

• 500 brands (typical daily delta cap) is about $1.00 when fully filled, and effectively $0 on quiet days when unchanged brands are skipped.
• 2,000 brands is about $4.00.
• Full 39,000-brand catalogue scan is about $80 as a one-time cost. Subsequent incremental daily runs typically cost well under $1 because unchanged brands are skipped before enrichment.

The delta model is designed so the expensive first crawl only happens once. Every scheduled day after that only pays for real change.

Notes and limits

• The API sits behind Cloudflare. Keep Use Apify Proxy on; plain datacenter requests get HTTP 403.
• GraphQL introspection is disabled on the source, so the field list was reconstructed by probing. If Thingtesting changes its schema, a field may need updating.
• The brand list overlaps between pages; the Actor de-duplicates within a run.
• Incremental state MUST live in a named key-value store. The default store is recreated on every run.
• Keep detail concurrency modest (4 is the default) to stay polite to the source.

FAQ, disclaimers, support

Is scraping Thingtesting legal? This Actor reads only public brand and review pages, with no circumvention of access controls. You remain responsible for downstream compliance (data-protection law, terms of service of any tool you load this data into, and outbound-contact regulation such as CAN-SPAM or GDPR when using founder or brand contact fields).

Do I need a Thingtesting account? No. All data is scraped from public pages.

What if a field changes or stops returning data? Thingtesting occasionally restyles its GraphQL schema. Report broken fields via the Issues tab and they will be patched.

Custom solutions. For a different cadence, extra fields, private warehouse delivery or a custom competitive-set report for a specific category, reach out through the Issues tab. Custom builds on top of this scraper are available.