Amazon Seller Analyzer — Sales & Revenue Estimates

Amazon Seller Analyzer estimates competitor sales, revenue, product leaders, and visible strategy changes from one seller profile.

Analyze an Amazon seller →

Amazon seller research with visible assumptions

Use Amazon Seller Analyzer for a bounded public catalogue observation and explicit sales/revenue scenarios. An agency can prepare a competitor worksheet, a sourcing team can inspect a seller's observed product mix, and an analyst can compare repeat observations. It does not access the seller's accounting, orders or private Seller Central metrics.

Research task	Inspect	Keep separate
Understand an observed catalogue sample	productsAnalyzed, ASINs, prices and catalogue coverage	The sample and the seller's entire business
Review modeled demand	Low/expected/high units and signals	Public rank/badge evidence and model assumptions
Examine seller attribution	sellerAttribution, Buy Box/offer evidence	Listing demand and the target seller's unknown actual order share
Track a repeat workflow	Strategy rows, baseline status and workflowId	Newly observed products and verified real-world launches
Export a report	rowType, sellerId, marketplace, currency and missing estimates	Free summary/change rows and paid product analyses

Start with one seller and a small product/page bound. Unknown modeling inputs remain null; a useful paid product observation can still have no supported revenue estimate. A large product cap is not evidence that the seller's full catalogue was collected.

What is Amazon Seller Analyzer?

Amazon Seller Analyzer turns public Amazon seller information into a structured competitor-intelligence report. Add a seller ID or profile URL to estimate daily, monthly, and annual unit sales and revenue, see which products may drive the business, and monitor observable changes between runs.

The Actor is designed for Amazon sellers, agencies, wholesalers, aggregators, researchers, and sourcing teams. It supports fast bulk seller analysis with no Amazon login, cookies, Seller Central access, or third-party API key required.

You receive:

• estimated seller sales for a day, month, and year;
• estimated revenue with low, expected, and high scenarios;
• product-level sales and revenue attribution;
• price, availability, Best Sellers Rank, Prime, coupon, offer, and Buy Box signals when publicly visible;
• seller profile and catalog coverage information;
• strategy-change events on recurring runs;
• structured JSON records ready for CSV, Excel, API, Make, n8n, or a data warehouse.

What can you use it for?

Use case	Business question
Competitor benchmarking	How large might this seller be?
Product research	Which listings appear to generate the most demand?
Wholesale research	How much listing demand may belong to the target seller?
Seller due diligence	Is the visible catalog large and commercially active?
Portfolio monitoring	What changed in price, availability, rank, promotions, or seller position?
Reporting and automation	How can I feed Amazon competitor data into my existing workflow?

How to analyze an Amazon seller

1. Open the Actor and paste an Amazon seller ID or seller profile URL.
2. Choose the matching Amazon marketplace.
3. For your first run, set Products per seller to 5 (the default) or 2 for a smaller check.
4. Run the Actor and open the Analysis results output.
5. Review the seller_summary row first, then compare the related product rows.
6. Schedule repeated runs with Track changes enabled to detect observable strategy changes.

Example input

{
  "sellerIds": ["A294P4X9EWVXLJ"],
  "marketplace": "us",
  "maxProductsPerSeller": 10,
  "includeOffers": true,
  "trackStrategy": true
}

You can provide multiple seller IDs or URLs in one run. Each seller is analyzed independently in the selected marketplace.

Input options

Field	Type	Default	Description
sellerUrls	array	—	Amazon seller profile URLs containing a seller ID.
sellerIds	array	—	Amazon merchant IDs. Use this when you already know the seller ID.
marketplace	string	us	Marketplace used for catalog discovery, prices, and currency.
maxProductsPerSeller	integer	5	Maximum products per seller, from 1 to 10000. Page/time/spending limits can return a smaller sample.
includeOffers	boolean	true	Inspect public offer and Buy Box information for better seller attribution.
trackStrategy	boolean	true	Compare observable signals with the previous successful run.
maxConcurrency	integer	2	Parallel product processing (1–4).
startPage, startOffset	integer	1, 0	Resume using a seller's nextInput from SUMMARY. Ordering can change between observations.
maxPages	integer	20	Source page bound per seller; reaching a limit is partial coverage.
snapshotStoreId	string	—	Optional monitoring store in your own account, accessible to this run.
workflowId	string	default	Separate independent monitoring baselines.
proxyConfiguration	object	Apify Residential	Proxy configuration used for marketplace requests.

At least one valid value in sellerUrls or sellerIds is required.

At most20 seller targets per input are accepted. Only HTTPS Amazon seller/catalog URLs in the selected marketplace are accepted; credential-bearing or other-domain URLs are rejected. Duplicate IDs and URLs are merged. Unsupported marketplaces are rejected rather than silently analyzed as US.

Supported Amazon marketplaces

Input	Marketplace	Currency
us	United States	USD
uk	United Kingdom	GBP
de, fr, es, it	Germany, France, Spain, Italy	EUR
ca	Canada	CAD
mx	Mexico	MXN
in	India	INR

Amazon seller revenue data

Reports describe the observed product sample, not the seller's complete business turnover. catalogCoverageComplete requires a confirmed terminal catalog page without product/page/time/spending truncation. estimateCoverageComplete indicates how many observed products support seller-revenue modeling; it is independent of catalog completeness.

estimated* values are null when demand, price or target-seller attribution is unknown. A partial visible offer list cannot prove that a seller is absent or exclusive. sellerAttribution distinguishes an observed Buy Box, an observed offer, and unverified; estimateStatus explains missing modeling inputs. priceSource identifies product-page prices versus a catalog fallback. identityVerified records whether the page exposed the expected ASIN marker. Missing coupon or Prime evidence is null, rather than a confirmed absence. Purchase badges and Buy Box evidence are scoped to the primary product; related recommendations do not provide its demand or seller identity.

Demand ranges use supported public rank/category signals and purchased-count badges where available. Unmapped categories and isolated subcategory ranks are not extrapolated using a generic rank curve; a purchase badge can still support a scenario. A purchased-count badge gives a listing-level lower threshold; the upper scenario is an assumption, not an Amazon-reported sales ceiling. Seller share is a heuristic from observed Buy Box/offers or accumulated observations, not the actual fraction of orders. Confidence and coverage scores indicate available signals, not independently calibrated accuracy. One representative child per known parent ASIN is retained; its estimate is not the total of all variations.

Monthly revenue = modeled product units × modeled seller share × observed listing price. Revenue is gross merchandise value before fees, shipping, returns or tax. Daily values divide a30-day month; annual values multiply the monthly scenario by12, without seasonality or a historical-sales claim. Monetary and unit outputs are rounded separately, so multiplying rounded seller units by price can differ slightly from the revenue scenario.

The default Dataset uses three rowType values:

rowType	What it contains
seller_summary	Seller-level headline estimates, ranges, catalog coverage, and profile data.
product	Listing data and the estimated portion attributed to the target seller.
strategy_action	A detected difference from the seller's previous observation.

Important seller summary fields:

Field	Meaning
estimatedSalesDaily	Expected units sold per day across analyzed products.
estimatedSalesMonthly	Expected units sold per 30-day month.
estimatedSalesAnnual	Monthly estimate projected across 12 months.
estimatedRevenueDaily	Expected daily gross merchandise revenue in local currency.
estimatedRevenueMonthly	Expected monthly gross merchandise revenue.
estimatedRevenueAnnual	Monthly estimate projected across 12 months.
estimatedRevenueMonthlyLow / High	Lower and upper monthly scenarios.
productsAnalyzed	Number of unique products included in the estimate.
dataCoverageScore	Relative completeness of observable signals, from 0 to 100.

Example seller summary output

{
  "rowType": "seller_summary",
  "sellerId": "A294P4X9EWVXLJ",
  "sellerName": "AnkerDirect",
  "marketplace": "us",
  "currency": "USD",
  "productsAnalyzed": 2,
  "estimatedSalesDaily": 3.9,
  "estimatedSalesMonthly": 117,
  "estimatedSalesAnnual": 1404,
  "estimatedRevenueDaily": 62.36,
  "estimatedRevenueMonthly": 1870.83,
  "estimatedRevenueAnnual": 22449.96,
  "estimatedRevenueMonthlyLow": 505.53,
  "estimatedRevenueMonthlyHigh": 8278.67,
  "dataCoverageScore": 78
}

The values above illustrate the output format from a limited test. They are not a claim about the seller's current or actual revenue.

Track visible Amazon competitor strategy

Use the same marketplace, seller and workflowId for comparable observations. An optional snapshotStoreId must be yours and accessible to the run; otherwise the named store is scoped to your workflow. Monitoring state advances only after successful report delivery. Partial scans retain previously observed products and suppress removal events. Unknown stock, coupon or Buy Box observations do not create loss/restock/removal events. PRODUCT_LAUNCHED means newly observed in this workflow, rather than a verified real-world launch. Check baseline/load/save status in SUMMARY and ERRORS.

Keep Track changes enabled and run the same seller and marketplace repeatedly. From the second successful observation onward, the Actor can report changes such as:

• products appearing in or disappearing from the visible catalog;
• price increases and decreases;
• coupon or promotion changes;
• availability changes;
• Best Sellers Rank movement;
• Buy Box or seller-position changes.

Use a daily schedule for closely watched competitors or a weekly schedule for broader portfolio research. A change event describes a public marketplace observation; it does not reveal a seller's private business decision.

How much does an Amazon seller analysis cost?

This Amazon Seller Analyzer uses transparent pay per event (PPE) pricing. Product analysis costs up to $5 per 1,000 successfully analyzed products, with lower prices for paid Apify plans, plus a $0.01-per-GB Actor start charge (minimum one event):

Apify plan	Per product	Per 1,000 products
FREE	$0.005	$5.00
BRONZE	$0.004	$4.00
SILVER	$0.0035	$3.50
GOLD	$0.003	$3.00
PLATINUM	$0.0025	$2.50
DIAMOND	$0.002	$2.00

The Actor start costs $0.01 per GB, minimum one event. The examples below assume no more than 1 GB. Seller summaries and detected strategy events are free.

Estimated Actor event charges:

Products analyzed	FREE	BRONZE	DIAMOND
10	$0.06	$0.05	$0.03
50	$0.26	$0.21	$0.11
100	$0.51	$0.41	$0.21
500	$2.51	$2.01	$1.01

User pays platform usage costs: Yes. Apify platform usage is charged separately to the user. This can include compute, storage, data transfer, and residential proxy traffic according to the user's Apify plan. Actual total cost depends on the marketplace, catalog size, public page availability, and run configuration. Start with 10 products to measure cost and coverage before increasing the limit.

API and integrations

For AI agents, discover apivault_labs/amazon-seller-revenue-strategy-analyzer through Apify MCP. Start with {"sellerIds":["A294P4X9EWVXLJ"],"marketplace":"us","maxProductsPerSeller":2,"trackStrategy":false}. Poll the returned run, then read its default Dataset and SUMMARY/ERRORS records with the returned storage IDs.

SUMMARY.status is succeeded, partial, empty or failed. A bounded sample can complete its Actor run with a partial summary; this does not indicate complete catalog coverage. Seller entries provide nextInput for page/offset continuation and the observed page count. Use the returned input for a bounded follow-up, preserving your workflow and monitoring store. Amazon's ordering is live and can change; continuation does not freeze or guarantee a full catalog.

Count only product rows as paid product analyses; seller_summary and strategy_action rows are uncharged. Missing estimates must remain unknown in downstream reports. Current-run spending limits account for startup events and the effective product price before collection. ERRORS contains safe retry guidance. Failed listings have no product event, but startup and platform usage can still apply.

Run the Actor from the Apify API:

curl "https://api.apify.com/v2/acts/apivault_labs~amazon-seller-revenue-strategy-analyzer/runs" \
  -X POST \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "sellerIds": ["A294P4X9EWVXLJ"],
    "marketplace": "us",
    "maxProductsPerSeller": 10
  }'

After the run finishes, use the run's default Dataset URL to retrieve JSON, CSV, Excel, XML, or HTML. You can also connect the Actor to schedules, webhooks, Make, Zapier, n8n, Google Sheets, or your own application.

Accuracy and responsible use

Amazon does not publish a competitor's private Seller Central sales or accounting data. Therefore, this Actor provides model-based estimates from publicly observable marketplace signals, not audited figures or guaranteed actual sales.

For responsible interpretation:

• use low, expected, and high scenarios instead of relying on one number;
• compare sellers using the same marketplace and similar product limits;
• check dataCoverageScore and productsAnalyzed before drawing conclusions;
• treat annual figures as projections, not historical financial statements;
• do not use the results as the sole basis for investment, credit, legal, or acquisition decisions.

Results may vary because Amazon pages, rankings, offers, availability, and visible catalogs change over time. Use the Actor in accordance with applicable laws, Amazon's terms, and Apify's policies.

Troubleshooting

The Actor found no analyzable products

Confirm that the seller ID belongs to the selected marketplace. Some profiles do not expose a public catalog, and some products may be unavailable at the time of the run.

Revenue looks lower than total listing demand

Amazon listings can have multiple sellers. Product demand and the portion attributed to the target seller are different measurements.

No strategy changes were returned

The first successful tracked run creates a baseline. Changes can appear only after a later run observes a difference for the same seller and marketplace.

The run is slow or incomplete

Keep a small product limit and inspect SUMMARY/ERRORS before deciding whether a resolved transient failure can be retried. Do not repeat a known source denial unchanged. Public marketplace pages can respond differently across marketplaces and times.

FAQ

Are the sales and revenue figures exact?

No. Exact competitor sales are private. The Actor returns transparent estimate ranges and coverage indicators to make uncertainty visible.

Does it require an Amazon login or API key?

No. You only need an Amazon seller ID or seller profile URL.

Can I analyze several sellers at once?

Yes. Add multiple IDs or URLs. The selected product limit applies to each seller.

Can I export the results?

Yes. Apify Datasets support JSON, CSV, Excel, XML, and HTML exports as well as API access.

Where can I report an issue?

Open the Issues tab on the Actor page and include the marketplace, seller ID, and run ID. Do not post API tokens or private credentials.

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Bounded Amazon seller-analysis examples

Use a seller that operates in the selected marketplace. The merchant ID in these examples is a recorded public sample, not a claim about its current catalogue size or actual revenue. Monitoring is disabled for first checks so they do not modify an existing observation baseline.

Inspect one seller product without tracking changes

{
  "sellerIds": [
    "A294P4X9EWVXLJ"
  ],
  "marketplace": "us",
  "maxProductsPerSeller": 1,
  "maxPages": 1,
  "maxConcurrency": 1,
  "includeOffers": true,
  "trackStrategy": false
}

This is a narrow product/attribution check. Read product and seller_summary rows separately, plus SUMMARY/ERRORS. A one-product limit intentionally leaves catalogue completeness unresolved.

Use an explicit seller-profile URL

{
  "sellerUrls": [
    "https://www.amazon.com/sp?seller=A294P4X9EWVXLJ"
  ],
  "marketplace": "us",
  "maxProductsPerSeller": 2,
  "maxPages": 1,
  "maxConcurrency": 1,
  "includeOffers": false,
  "trackStrategy": false
}

Without optional offer inspection, seller-share attribution can be less supported or unknown. Do not replace a null seller-revenue estimate with all of the listing’s modeled revenue.

Create a separate monitoring baseline

{
  "sellerIds": [
    "A294P4X9EWVXLJ"
  ],
  "marketplace": "us",
  "maxProductsPerSeller": 2,
  "maxPages": 1,
  "maxConcurrency": 1,
  "trackStrategy": true,
  "workflowId": "seller-research-example"
}

This writes state for the named workflow. Use your own workflowId for a real monitor; do not reuse another team’s baseline accidentally. A first observation establishes context rather than proving a product launch or a strategy change.

Keep a bounded catalogue sample

{
  "sellerIds": [
    "A294P4X9EWVXLJ"
  ],
  "marketplace": "us",
  "maxProductsPerSeller": 3,
  "maxPages": 2,
  "maxConcurrency": 1,
  "trackStrategy": false
}

Product/page caps and the run budget can all limit output. For continuation use the actual seller nextInput returned by SUMMARY, preserving selector and monitoring scope. Do not invent page/offset values and call that verified pagination.

Compare products and sellers without hiding uncertainty

Use comparable marketplaces, currencies, time windows and product limits. A small sample can favor the products first exposed by the public catalogue order. catalogCoverageComplete and estimateCoverageComplete answer different questions: seeing the source end does not make every product modelable, and modelable sampled products do not establish catalogue exhaustion.

Keep priceSource, identityVerified, sellerAttribution, estimateStatus and warnings alongside numeric estimates. A purchase badge is a listing-level observation; a modeled seller share is not a measured fraction of orders. The observed Buy Box or a partial offer list can support a scenario without establishing exclusive ownership of listing demand. Unknown coupon/Prime evidence must remain distinct from an explicit absence.

If annual and daily values are included, preserve their projection basis. A 30-day monthly scenario multiplied by 12 does not become trailing-twelve-month audited revenue. Gross merchandise revenue is before fees, tax, refunds and operating expenses; it is not profit or cash flow. Scores describe the available evidence and assumptions rather than calibrated forecast accuracy.

For monitoring, use a store your run can access and retain comparable workflow inputs. Partial scans preserve earlier observations and suppress unsupported removal events. If state cannot be loaded/saved, inspect errors before interpreting an empty change list. Newly observed ASINs can reflect discovery order or a wider sample rather than a seller's new business decision.

Amazon seller analyzer questions

Do you know actual sales or seller turnover? No. Competitor orders and accounting are private. The Actor provides signal-based scenarios over the observed sample, with nulls where evidence is insufficient. Neither a complete-looking summary nor a high coverage score verifies actual revenue.

What is charged in a mixed Dataset? Paid product-analysis events correspond to successfully analyzed product rows. seller_summary and strategy_action rows are free. The active startup event is $0.01 per GB, with a one-event minimum. At 512 MB, one BRONZE product has $0.014 in events ($0.01 startup + $0.004 product), before separate platform/proxy usage. At 2 GB startup is $0.02, not the same per-run amount.

Can I analyze a full catalogue with maxProductsPerSeller=10000? That is an input ceiling. Page/time/budget limits and source access can return a partial sample. Read nextInput and stop reasons; it is not a throughput guarantee or an accounting reconciliation.

Does a missing estimate mean no sales? No. Missing demand, price or seller-attribution evidence can make the estimate null even when product identity and other useful fields are available. Preserve that distinction in spreadsheets and AI-generated comparisons.

Can I compare two sellers in different currencies directly? Keep currency and marketplace, and perform an explicit dated conversion in your own analysis if needed. The Actor does not make unequal catalogue samples or different-market products automatically comparable.

What should an agent report after a run? The actual paid product count, free summary/change counts, source/estimate coverage, costs, missing inputs and continuation status. Poll the returned run ID and use its actual storage IDs; avoid starting duplicate jobs while waiting.

n8n and developer integrations

Use this Actor in your automation or application with the existing community integrations below. An Apify account and API token are required; Actor and platform charges follow the current pricing.

• n8n community node: n8n-nodes-apivault-amazon-seller-analyzer. Install package name n8n-nodes-apivault-amazon-seller-analyzer in a self-hosted n8n instance that permits community packages.
• n8n source and usage: GitHub.
• Python client and examples: GitHub.
• n8n source and usage: GitHub.

These are community packages. Publication on npm does not establish n8n verification or availability in n8n Cloud. Review the linked package README for supported inputs and setup.