📚 Amazon KDP Book Niche Analyzer: Real BSR and Competition Data

Spot a winnable KDP niche before you write a single page Research Kindle Store keywords in bulk and see real Best Sellers Rank, pricing, and review evidence for every competing book, not just a star rating.

📊 Real sales-rank evidence See genuine Best Sellers Rank data neither rival KDP tool reports.

🛡️ Scores that refuse to guess Opportunity scores stay hidden until there is enough evidence to trust them.

📚 Full competitor profile Page count, publisher, and publish date show exactly who you would be up against.

🔔 Scheduled niche monitoring Re-check a niche automatically and see what changed since the last look.

Compare Kindle niches before you spend time writing, designing, or publishing. Built for KDP self-publishers, low-content publishers, coaches, and book-market researchers who want a repeatable research file instead of dozens of browser tabs.

💡 Why use it

Manual niche checks make it hard to compare ideas fairly. One search result page may look promising until you inspect the competing books, their BSR, price points, and age.

This actor puts comparable public evidence beside each keyword. It helps you shortlist niches, review direct competitors, and save a baseline for later checks. The scores explain what they used. They do not pretend to know exact sales or search volume.

🧭 How it works

STEP 1 Add your niche ideas Enter Kindle keywords or paste direct book links for known competitors.

STEP 2 Set your research depth Choose how many books and autocomplete suggestions to inspect per keyword.

STEP 3 Compare and decide Review ranked book evidence and niche summaries, then schedule repeat checks on niches worth watching.

The actor researches the US Kindle Store. It does not require a Kindle or Amazon account.

📥 Input

Field	Type	Required	Description
Keywords	array of strings	No*	One or more Kindle niche phrases to compare, such as gratitude journal or meal planner for women.
Direct book URLs	array of URLs	No*	Kindle book pages to inspect when you already know the competing titles.
Include autocomplete suggestions	boolean	No	Collect public Kindle search suggestions for each keyword.
Analyze autocomplete suggestions	boolean	No	Run the same niche analysis for collected suggestions, subject to the suggestion limit.
Max suggestions per keyword	integer	No	Maximum autocomplete suggestions retained for each supplied keyword.
Monitor changes	boolean	No	Compare later scheduled runs with the saved baseline and return detected changes.
Max books per keyword	integer	No	Maximum Kindle books analyzed for each keyword or suggestion.
Proxy configuration	object	No	US Apify datacenter traffic is enforced for reliable USD Kindle pricing and predictable run costs.

*Provide at least one keyword or one direct book URL. Use direct URLs for a focused competitor review. Use keywords when you want an organic niche comparison. In the Console, clear the example keyword when you want a direct-URL-only run.

📤 Output

Each run writes one analyzed book record per successful book-keyword observation to the default dataset. These rows are the exportable evidence and the only records included in the published per-book event contract. Niche summaries make comparisons easier and are available in the named niche-summaries dataset and the NICHE_SUMMARY / NICHE_SUMMARIES key-value-store records.

Autocomplete suggestions are discovery ideas, not reported search demand. Organic rank means a book's position in the collected Kindle search results. It is not an Amazon bestseller rank.

Use the default dataset for direct competitor review and a CSV of the evidence. Use the named niche-summary output for a compact comparison shortlist without separating it from the book evidence used to create it.

primaryOutput: "NICHES" is deprecated for legacy API callers. New Console inputs do not expose it, and future releases treat book records as the default dataset output in every workflow.

With monitoring enabled, later scheduled runs compare visible public data with the stored baseline. Monitoring starts when you run it. It does not create historical data from before the first run.

📊 Data table

Field	Type	Description
recordType	string	Identifies the analyzed BOOK record in the default dataset. Niche summaries use the supporting named dataset.
marketplace	string	Marketplace scope for the collected record.
sourceMode	string	Shows whether the record came from a keyword search or direct book page.
keyword	string	The supplied keyword tied to the record.
searchPage	integer	Kindle search results page used for discovery.
title	string	Public Kindle book title, when the record is a book.
author	string	Public author or contributor name, when shown.
asin	string	Amazon Standard Identification Number for a book, when shown.
detailUrl	URL	Public Kindle book page used for the evidence.
organicPosition	integer	Position in the collected Kindle search results for the analyzed keyword.
bsrOverall	integer	Visible Best Sellers Rank in the Kindle Store. A lower number indicates a stronger visible rank.
bsrOverallCategory	string	Kindle Store category paired with the overall BSR.
bsrCategoryRank	integer	Visible rank in the book's top listed category.
bsrCategoryName	string	Name of the book's top listed category.
categoryRanks	array of strings	Visible category ranks shown for the book.
categoryRankDetails	array of objects	Structured category rank details shown for the book.
format	string	Edition format shown on the Kindle book page.
price	number	Public listed price when available.
currency	string	Currency displayed with the listed price.
listPrice	number	Public list price when available.
discountPercent	number	Visible percentage discount when available.
rating	number	Public average customer rating when available.
ratingCount	integer	Public rating count when available.
ratingStatus	string	Availability status of the public rating signal.
reviewCount	integer	Public review count when available.
pageCount	integer	Page count when shown on the book page.
publisher	string	Public publisher name when shown.
publisherType	string	Publisher classification when available.
publishDate	string	Public publication date, when available.
publicationAgeDays	integer	Age in days calculated from the visible publication date.
language	string	Book language when shown.
coverImageUrl	URL	Public cover image link when available.
description	string	Public book description when available.
booksAnalyzed	integer	Number of books included in a niche summary.
medianBsrOverall	number	Median visible Kindle Store BSR in the niche sample.
medianPrice	number	Median observed price in the niche sample.
medianRatingCount	number	Median observed rating count in the niche sample.
lowReviewShare	number	Share of observed books with 20 or fewer ratings.
authorityBookShare	number	Share of observed books with at least 1,000 ratings.
recentBookShare	number	Share of observed books published within the previous 365 days.
independentPublisherShare	number	Share of classified books identified as independently published.
scoreComponents	object	Demand, review-ease, and competition-ease components behind the opportunity score.
opportunityScore	integer	Combined comparison signal when the sample has sufficient evidence. It is not a sales or search-volume estimate.
opportunityLabel	string	Plain-language interpretation of the opportunity score.
confidence	integer	Confidence based on sample size and BSR and rating-count coverage.
scoreFormula	string	Exact formula used for the niche score.
warnings	array of strings	Evidence, crawl-coverage, or collection warnings.
autocompleteSuggestions	array of strings	Collected public Kindle autocomplete suggestions for a seed keyword.
monitoring	object	Baseline status and detected summary changes from a scheduled run.
scrapedAt	string	Time the public evidence was collected.

Fields appear only when the Kindle Store publicly shows the value. Missing data is not replaced with guesses.

🧮 How the scores stay explainable

Scores are comparison aids, not verdicts. Every niche summary includes its component signals and score method.

• Demand is calculated from the median public Kindle Store BSR in the collected sample.
• Ease starts with the median rating count, then accounts for the share of books with 1,000 or more ratings.
• Confidence reflects sample size plus BSR and rating-count coverage. It does not raise or lower the opportunity score.

demandScore = clamp(round(100 - 25 × log10(max(medianBsr, 1000) / 1000)), 0, 100)

reviewEase = clamp(round(100 - 20 × log10(max(medianRatingCount, 1))), 0, 100)

competitionEaseScore = round(0.7 × reviewEase + 0.3 × (100 - authorityBookShare × 100))

opportunityScore = round(sqrt(demandScore × competitionEaseScore))

confidence = round(100 × min(1, booksAnalyzed / 16) × min(bsrCoverage, ratingCoverage))

The actor omits the opportunity score when evidence is insufficient. It needs at least five books, three visible BSR values, three rating counts, and confidence of 50 or higher.

Treat the result as a transparent prioritization signal. Read the book rows before committing to a niche.

💰 Pricing

This Actor uses pay per event pricing. A small flat fee applies once a run starts, including an empty run, plus a fee for each book-keyword observation successfully returned to the default dataset. Failed or unavailable book pages are never charged.

Paid plans on Bronze, Silver, Gold, Platinum, or Diamond tiers receive a lower per-book rate than the Free plan. Check the Store pricing panel on this Actor's page for the exact current rates.

A book found for more than one requested keyword is billed once per keyword, since each observation carries distinct organic-position evidence.

Niche summaries, monitoring comparisons, and autocomplete suggestion lists are supporting output. They are not separate billable events. Set a run charge cap when you need strict budget control.

⭐ Enjoying Amazon KDP Book Niche Analyzer: Real BSR and Competition Data?

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🛠️ Tips for stronger research

• Compare related, specific phrases instead of a single broad term. teacher gratitude journal is usually more useful than journal.
• Start with the named niche summaries, then inspect the default-dataset books behind the strongest and weakest signals.
• Use autocomplete to find phrasing shoppers may use, then analyze only the suggestions relevant to your publishing angle.
• Keep the same limits for each keyword when comparing niches. Uneven samples make scores less comparable.
• Schedule a monitoring run for a short list. It is useful for watching visible competition change before launch.

❓ FAQ

Does this report Kindle sales or keyword search volume?

No. It reports public Kindle Store evidence. BSR is a visible rank, not a sales figure. Autocomplete suggestions are ideas, not measured search volume.

Can I research several KDP niches in one run?

Yes. Add multiple keywords, then compare their supporting niche summaries alongside the default-dataset book evidence. Keep the same book limit for each keyword when you need a fair comparison.

Can I inspect a known competitor without searching for a keyword?

Yes. Add its direct Kindle book page. This is useful when a coach, client, or competitor list has already identified the titles to review.

What does organic position mean?

It is the book's visible position in the collected Kindle search results for a keyword. It is separate from Best Sellers Rank.

How does monitoring work?

Run the same input on a schedule with monitoring enabled. Later runs compare visible public fields with the baseline stored by earlier monitored runs.

Is this an official Amazon or KDP tool?

No. This independent tool uses publicly visible Kindle Store information. It is not affiliated with, endorsed by, or sponsored by Amazon, Kindle, or KDP. Amazon, Kindle, and KDP are trademarks of Amazon.com, Inc. or its affiliates.

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