Amazon Bestseller Radar — BSR Movers, New Entries & Price Delta

Most bestseller scrapers hand you a list. This one hands you what changed: run it on up to 10 Amazon Best Sellers categories at once and get, next to the current ranking (top 30, plus ranks 51–80 at depth 2), the movement since your previous run — new entries, climbers, fallers and drop-outs, each with rank deltas, prices and demand signals, plus a per-category volatility score. One flat price per category — never per product. Schedule it daily or weekly and wire the dataset straight into n8n, Make, Zapier, Google Sheets, Slack alerts or AI agents (Claude, ChatGPT and any LLM workflow via Apify's API and MCP).

The radar computes movement from your own run history — not from Amazon's Movers & Shakers page, which shows only Amazon's fixed 24-hour window. Your watchlist compares any two of your runs, at any cadence you choose: daily, weekly, monthly. Every run deepens a history that no fresh scrape can reproduce.

What changed since your last run (the product)

Set a watchlistId and every run answers the only question that matters: what moved?

"movement": {
  "new_entries":  [{ "asin": "B0FN4NH4K8", "rank_after": 12 }],
  "climbers":     [{ "asin": "B00NTCH52W", "rank_before": 28, "rank_after": 9,  "delta": 19,  "price_change": -0.50 }],
  "fallers":      [{ "asin": "B07BGLT25K", "rank_before": 4,  "rank_after": 22, "delta": -18, "price_change": 0.32 }],
  "dropped_out":  [{ "asin": "B0C2CY22B8", "rank_before": 30 }],
  "vs_run": "2026-07-20T06:00:00Z"
}

• Positive delta = moved up the list. A climb from 28 to 9 is +19; a slide from 4 to 22 is -18.
• price_change rides along on every mover, so you see whether a climb came with a price cut.
• The first run of a watchlist is the baseline: full ranking delivered, movement empty by definition, flagged baseline: true — never a silent empty result. From run 2 onward, movement flows.
• If a run was taken differently from the previous one (different depth, different data path), the row says not_comparable_reason instead of inventing movement. Reporting nothing honest beats reporting fake movement.

Ranking with demand signals

Every category row carries the ordered ranking — rank is Amazon's own badge number, read off the page:

{ "rank": 1, "asin": "B079VP6DH5", "title": "Bounty Paper Towels Quick Size...",
  "brand": "Bounty", "price": 45.73, "stars": 4.8, "reviews": 234786,
  "bought_last_month": 100000, "is_amazon_choice": true, "is_best_seller": false }

• Price, stars and review counts come with every ranked product.
• Demand signals (bought_last_month, Amazon's Choice / Best Seller badges) are attached to the top 10 of each category — the zone worth acting on. So "new entry at rank 12" arrives with purchase context, not as a bare ASIN.
• brand is inferred from product titles (Amazon states no brand on Best Sellers pages); brand_source tells you which rule produced it, so an inferred brand is never dressed up as a stated fact.

Volatility score — which categories are in play

Each row ends with a summary built for choosing where to compete:

"summary": { "volatility_score": 4.8, "new_entry_count": 3,
             "avg_price_top10": 21.40, "price_movement_top10": -0.6 }

volatility_score is the mean absolute rank change across products present in both runs. A category at 0.5 is frozen; a category at 6+ is in play. Combined with avg_price_top10 and its movement, it is a shortlist machine for product research: scan 10 categories weekly, read one number per category, dig into the two that moved.

Pricing — flat per category, not per product

You pay per category scanned, after results are delivered:

Event	Price (Store FREE tier)	What it covers
Actor start	$0.05 per run	validation + cache lookup
Category scan	$0.05 per category × depth (down to $0.032 on higher Store tiers)	ranking + demand signals + movement + volatility summary

Depth 1 (top 30) = 1 scan per category; depth 2 (top 30 + ranks 51–80) = 2 scans. There is no per-row fee. Raw per-item scrapers charge $0.005–0.006 per product, which makes one top-100 category cost $0.30–0.59 per run — this radar delivers the same category with the movement layer included for $0.05–0.10.

Worked examples (FREE-tier prices — paid Store tiers are cheaper):

Setup	Monthly cost
5 categories, daily, depth 2	≈ $16.50/mo
10 categories, weekly, depth 2	≈ $4.55/mo
1 hobby category, weekly, top 30	≈ $0.45/mo

Never billed: categories that failed upstream, repeat runs served from the 24-hour cache, and empty results. Start free: every account gets a 1-category preview per run (top 30) at no feature cost, and Apify's free $5 platform credit covers roughly 50 category scans — enough to watch one category daily for a month before paying anything.

How it compares

• Jungle Scout ($49–129/mo), Helium 10 ($99+/mo), AMZScout ($45+/mo) — seat-based suites. If all you need is "what moved in my categories this week", a scheduled radar at a few dollars a month answers it without the seat.
• Keepa (€19/mo) — excellent per-product BSR history; no category-level "what changed since my last check" layer. Many users run both: Keepa for product deep-dives, the radar for category-level triage.
• Amazon's own Movers & Shakers page — a fixed 24-hour window, Amazon's choice of products. The radar measures your categories over your cadence, and keeps history.
• Per-item bestseller scrapers — a list, priced per row. No memory, no deltas, and a top-100 dump costs 3–6× more per run than a category here.

Use with AI agents & LLM workflows

The dataset is plain JSON, which makes the radar a natural sensor for automation:

• n8n / Make / Zapier: schedule the Actor → trigger on new dataset items → push "3 new entries in Health & Household today" into Slack, Teams or Google Sheets.
• AI agents: connect through Apify's MCP server and let a Claude- or GPT-based agent run scans on demand and read movement directly.
• LLM summaries: pipe the movement object into a prompt like "Summarize today's category changes and pick 3 products worth investigating" — the object is small, structured and delta-only, so it fits comfortably in any context window.

How movement is measured (honest scope)

• Coverage: a static scan of a Best Sellers page yields Amazon's top 30; page 2 carries ranks 51–80. Amazon only serves ranks 31–50 and 81–100 to a scrolling browser, so no scheduled tool can see them — this one does not pretend to. Ranks shown are Amazon's own badge numbers, and new_entries / dropped_out mean "entered / left the observed window".
• Cadence: Amazon refreshes Best Sellers roughly hourly. Scanning more often than daily mostly measures that hourly jitter — the radar is built and priced for daily or weekly tracking. In release testing, two scans of the same category taken minutes apart agreed within 0–3 rank positions across the full observed set.
• Baseline: movement needs two points. Your first run of a watchlist stores the baseline and says so; it is billed, because the ranking it delivers and stores is the answer your next run is measured against.
• Reliability: if the primary data path fails twice in a row, the run completes on an independent fallback path — those rows are flagged source: "fallback" and carry ranks only, with price fields null (never a fake zero).
• Marketplace: amazon.com (US) in this version. Other marketplaces are planned.

Input

{
  "categories": ["https://www.amazon.com/Best-Sellers-Health-Household/zgbs/hpc/"],
  "depth": 2,
  "watchlistId": "my-radar",
  "enrichDemand": true
}

Paste full Best Sellers URLs (they contain /zgbs/). Duplicates and paste variants of the same category are merged before anything is charged. Invalid entries are rejected up front — a malformed request never costs money.

Field	Type	Default	What it does
categories	array	— (required)	Full Amazon Best Sellers category URLs, up to 10 per run
depth	1–2	2	1 = top 30 · 2 = top 30 + ranks 51–80 (2× category-scan events)
watchlistId	string	—	Any label; runs sharing it are compared → movement. One per niche/client
enrichDemand	boolean	true	Demand signals (bought-last-month, badges) for each category's top 10
marketplace	com	com	amazon.com (US) in this version
bypassRunCache	boolean	false	Force a fresh scan inside the 24-hour cache window (this charges)

Quick start

Console: paste one or more Best Sellers URLs into Categories, set a Watchlist ID, click Start. The first run stores your baseline; from the second run the Movement view shows what changed.

Schedule it (this is where the radar earns its name): Apify Console → Schedules → attach this Actor, cron 0 6 * * * for daily at 06:00 or 0 6 * * 1 for weekly on Mondays. Keep the same input — same watchlist, same categories, same depth — so every scheduled run extends one clean history. Results land in the run's dataset, downloadable as JSON/CSV/Excel or served over the API.

API:

curl -X POST "https://api.apify.com/v2/acts/<ACTOR_ID>/runs?token=<YOUR_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"categories": ["https://www.amazon.com/Best-Sellers-Health-Household/zgbs/hpc/"],
       "depth": 2, "watchlistId": "my-radar"}'

Then read the dataset: GET https://api.apify.com/v2/datasets/<DATASET_ID>/items — one JSON object per category, ready for a spreadsheet, a dashboard or an LLM prompt.

Output reference

One dataset row per category per run:

Field	What it is
category, category_url	Human-readable name (from the page itself) and the canonical URL
run_at	ISO timestamp of this scan
ranking[]	Ordered products: rank (Amazon's badge number), asin, title, brand + brand_source, price, stars, reviews, url; top 10 add bought_last_month, is_amazon_choice, is_best_seller
movement	new_entries / climbers / fallers / dropped_out (+ vs_run) — only when watchlistId is set
baseline	true on the first run of a watchlist (movement empty by definition)
not_comparable_reason	Present instead of movement when this run was taken differently than the last (depth_changed, source_changed)
summary	volatility_score, new_entry_count, avg_price_top10, price_movement_top10
source	primary (full rows) or fallback (rank-only; price fields null)
depth_pages, results_scanned, parse_confidence	Scan telemetry — parse_confidence below 1.0 signals a page-layout change

Null means unobserved, never zero: a fallback-sourced price is null, a product with no rating shows stars: null, and price_change only appears when both runs actually carried a price.

Popular categories to start with

All verified live — paste any of these straight into the input:

Category	URL
Health & Household	https://www.amazon.com/Best-Sellers-Health-Household/zgbs/hpc/
Beauty & Personal Care	https://www.amazon.com/Best-Sellers-Beauty/zgbs/beauty/
Kitchen & Dining	https://www.amazon.com/Best-Sellers-Kitchen-Dining/zgbs/kitchen/
Home & Garden	https://www.amazon.com/Best-Sellers-Home-Kitchen/zgbs/home-garden/
Electronics	https://www.amazon.com/Best-Sellers-Electronics/zgbs/electronics/
Toys & Games	https://www.amazon.com/Best-Sellers-Toys-Games/zgbs/toys-and-games/
Pet Supplies	https://www.amazon.com/Best-Sellers-Pet-Supplies/zgbs/pet-supplies/
Sports & Outdoors	https://www.amazon.com/Best-Sellers-Sports-Outdoors/zgbs/sporting-goods/
Grocery & Gourmet Food	https://www.amazon.com/Best-Sellers-Grocery-Gourmet-Food/zgbs/grocery/
Baby	https://www.amazon.com/Best-Sellers-Baby/zgbs/baby-products/
Office Products	https://www.amazon.com/Best-Sellers-Office-Products/zgbs/office-products/
Automotive	https://www.amazon.com/Best-Sellers-Automotive/zgbs/automotive/
Video Games	https://www.amazon.com/Best-Sellers-Video-Games/zgbs/videogames/
Clothing, Shoes & Jewelry	https://www.amazon.com/Best-Sellers-Clothing-Shoes-Jewelry/zgbs/fashion/
Tools & Home Improvement	https://www.amazon.com/Best-Sellers-Tools-Home-Improvement/zgbs/hi/

Subcategories work the same way — navigate to any Best Sellers subcategory on Amazon (the URL keeps the /zgbs/ segment) and paste it. A niche subcategory usually gives a sharper signal than a giant root category: top-30 movement in Whey Protein Powders means more than rank 29→28 in all of Health & Household.

Who uses a bestseller radar

• FBA / private-label sellers — watch your own category daily: a new entry climbing with a price cut is tomorrow's competitor, visible on day one.
• Product researchers — scan 10 candidate niches weekly; let volatility_score and new_entry_count shortlist the two worth a deep dive.
• Brands & agencies — one watchlist per client; the movement object is the weekly report, ready for Slack or a slide.
• Arbitrage & wholesale — price_movement_top10 plus faller lists flag categories where prices are sliding before margins do.

FAQ

How is this different from Amazon's Movers & Shakers page? That page is Amazon's own fixed 24-hour snapshot of products Amazon picks. The radar diffs your chosen categories between your runs — any cadence, any category, with history that accumulates in your account.

Do I get the full top-100? No — and neither does any scheduled scraper, honestly labeled or not. Amazon lazy-loads ranks 31–50 and 81–100 in the browser. You get the top 30 (depth 1) plus ranks 51–80 (depth 2), under Amazon's own rank numbers.

How often should I run it? Daily or weekly. Amazon updates Best Sellers hourly, so sub-daily runs mostly measure noise — and identical runs within 24 hours are served from cache without charges anyway.

Does it track prices? Yes: every ranked product carries its current price, movers carry price_change, and each category summarizes avg_price_top10 and its movement.

Can I monitor several niches or clients separately? Yes — use a separate watchlistId per niche or client. Each keeps its own independent movement history.

Is this a Jungle Scout alternative? For category-trend watching, yes: a scheduled radar at a few dollars per month instead of a $49–129/mo seat. For full product research suites (keyword tools, supplier databases), those platforms do more — pair the radar with a keyword-research actor and you cover the research loop for a fraction of the price.

What happens on the very first run? You get the full ranking plus baseline: true and empty movement arrays. Movement appears from the second run of the same watchlist.

Legal & compliance

The Actor reads publicly visible Amazon Best Sellers listing pages: product titles, ranks, prices, ratings and badges. It does not log into any account, does not access private data, and collects no personal information. You are responsible for using the data in line with the laws and terms that apply to you.

Related actors

• Amazon Rank Tracker — a new product just entered your category's top 10? Track the keywords it ranks for — organic and sponsored positions, share of shelf, movement run over run.
• Amazon Keyword Research Tool — find and prioritize the search terms behind any niche you spot moving here, with Amazon search volume and reverse-ASIN lookup.
• Keyword Metrics Pro — Google + Bing volume, CPC and trends for the head terms of a category before you commit to it.

---

If the radar catches a mover you would have missed, a bookmark or an honest review helps other sellers find it.