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Date

May 2026

Amazon Niche Finder v4.0

A powerful Python tool to discover profitable, low-competition niches on Amazon through intelligent multi-level exploration, comprehensive product analysis, and smart scoring algorithms. Perfect for authors, sellers, and entrepreneurs looking to identify underserved market opportunities.

What's New in v4.0

Full Research Pipeline (--research): The recommended new mode — one seed keyword in, a ranked shortlist of niche opportunities out. Each opportunity includes a profitability rationale and pre-grouped keyword clusters ready for listing optimisation.
Profitability Rationale: Every winning niche now comes with plain-English strengths and weaknesses backed by specific metrics so you know why a niche was chosen.
Keyword Clustering: SEO keywords are now grouped into five semantic clusters — title, bullets, long_tail, question, and backend — mapped directly to Amazon listing slots.
Opportunity Score: A new balanced ranking signal (_calculate_opportunity_score) used by the research pipeline that weights free-signal demand estimates and competitor weakness more heavily than the classic overall score.
Playwright Browser Fallback: Selenium has been replaced with Playwright (supports Brave, Chrome, or bundled Chromium). Configure the browser path with the PLAYWRIGHT_BROWSER_PATH environment variable.
BSR Filtering (--bsr-min / --bsr-max): Filter niches by product Best Sellers Rank range to target specific sales velocity bands.
Updated Demand Confidence Levels: Simplified to low, medium, and high based on the number of available free signals.
Research CSV / JSON Exports: The --research mode produces its own export format with rank, verdict, opportunity score, BSR range, profitability rationale, and keyword clusters.
Shared Cache Architecture: The research pipeline reuses a single SEOKeywordResearch instance for both niche discovery and keyword generation, eliminating redundant HTTP requests.

Key Features

Intelligent Exploration

Recursive Keyword Discovery: Explores keywords 2-3 levels deep automatically
Smart Pruning: Skips unpromising paths to save time
Deduplication: Never explores the same keyword twice
Progress Indicators: See exactly what's being explored in real-time

Full Research Pipeline

Candidate Generation: Builds a rich candidate set from direct autocomplete, alphabet expansion (a–z), modifier prefixes/suffixes, second-hop title-word expansions, and optional trend-derived seeds
Opportunity Ranking: Ranks all discovered niches by a balanced opportunity score and selects the top winners
Profitability Rationale: Generates metric-backed strengths and weaknesses for every winning niche
Keyword Clustering: Groups SEO keywords into title, bullets, long_tail, question, and backend clusters
End-to-End in One Command: python main.py --research --seed "your keyword" replaces running niche finder + SEO keywords separately

Comprehensive Analysis

Competition Score: Analyzes result counts with smart weighting (sweet spot: 100-2000 results)
Price Analysis: Average price, price range, and revenue potential scoring
Demand Indicators: Review counts, bestseller badges, and customer engagement
Product Quality: Average ratings and review distribution
BSR Tracking: Best Sellers Rank per product, with average and range
Specificity Score: Rewards longer, more specific keywords (better niches)

Advanced Scoring Algorithm

Each niche gets a weighted overall score (0-100) based on:

30% Competition (lower is better, but not too low)
20% Competitor Strength (weaker competitors = better opportunity)
20% Price/Revenue Potential (higher is better)
15% Demand Indicators (moderate is best)
15% Specificity (more specific = better niche)

The research pipeline uses a separate Opportunity Score with different weights:

25% Demand Estimate Score (free-signal demand)
20% Competition
20% Competitor Strength
15% Price
10% Specificity
10% Trend

Competitor Strength Analysis

Analyzes the actual competitors in each niche:

Brand Detection: Identifies Amazon-owned brands and major established brands
Market Concentration: Determines if market is monopolized, concentrated, or diverse
Barrier to Entry: Calculates how hard it is to compete (low/medium/high/very_high)
Competitor Reviews: Tracks average review counts to gauge competition strength
Small Seller Count: Identifies niches with many small independent sellers
Opportunity Level: Rates opportunity as excellent/good/moderate/poor

Multi-Category Support

Search across 10+ Amazon categories:

Books (books)
Home & Garden (home)
Kitchen (kitchen)
Toys & Games (toys)
Sports & Outdoors (sports)
Electronics (electronics)
Beauty & Personal Care (beauty)
Pet Supplies (pet)
Office Products (office)
Arts & Crafts (arts)
All Departments (all)

Professional Exports

CSV Export: Spreadsheet-ready data for both classic niche mode and research mode
JSON Export: Structured data with full metadata including keyword clusters
Comprehensive Reports: Detailed text reports with ranked recommendations and profitability rationale

Trend Hunting & Validation

Amazon Movers & Shakers: Discover trending products automatically
Google Trends Integration: Validate keywords against Google Trends data
Trend Direction Detection: Identifies rising, falling, stable, or unknown trends
Trend Boosting: Enriches niche scores based on trend momentum
Auto-Trends Analysis: Automatically discover trending keywords and run full niche analysis on each
Supported Trend Categories: Books, T-shirts, Merchandise (apparel category)

Installation

# Clone the repository
git clone https://github.com/mdnaimur0/amazon-niche-finder.git
cd amazon-niche-finder

# Install dependencies using uv
uv sync

After installing, run the Playwright browser installer once to get the bundled Chromium (only needed if you plan to use --browser-fallback without a local Brave/Chrome):

uv run playwright install chromium

To use your own Brave or Chrome binary instead, set the environment variable before running:

set PLAYWRIGHT_BROWSER_PATH=C:\Program Files\BraveSoftware\Brave-Browser\Application\brave.exe

Usage

Basic Usage

Search for niches in the books category:

uv run main.py --seed "coloring book for"

Recommended: Full Research Pipeline

The --research flag is the most powerful mode. It runs the complete pipeline from a single seed — candidate generation, niche analysis, opportunity ranking, profitability rationale, and keyword clustering — in one command:

# Full research pipeline (recommended)
uv run main.py --research --seed "muslim prayer tracker" --category books

# Research with Google Trends enrichment
uv run main.py --research --seed "yoga journal" --category books --use-trends

# Research with BSR filtering (target products ranked #1,000–#50,000)
uv run main.py --research --seed "coffee mug" --category kitchen --bsr-min 1000 --bsr-max 50000

# Research with custom limits
uv run main.py --research --seed "desk planner" --category office --max-niches 10 --keywords-per-niche 40

# Export research report
uv run main.py --research --seed "dog toy" --category pet --export-csv research.csv --export-json research.json

Advanced Usage Examples

Classic niche discovery:

# Kitchen products with price filtering
uv run main.py --seed "coffee mug" --category kitchen --min-price 15 --max-price 50

# Sports equipment with deeper exploration
uv run main.py --seed "yoga mat" "resistance bands" --category sports --depth 3

# Pet products with custom threshold
uv run main.py --seed "dog toy" --category pet --threshold 5000

# Filter by Best Sellers Rank
uv run main.py --seed "notebook" --category office --bsr-max 100000

Export results for analysis:

# Export to CSV
uv run main.py --seed "planner" --category office --export-csv results.csv

# Export to JSON with full metadata
uv run main.py --seed "skin care" --category beauty --export-json results.json

# Both formats
uv run main.py --seed "puzzle" --category toys --export-csv niches.csv --export-json niches.json

Generate Amazon listing SEO keywords:

uv run main.py --seo-keywords "muslim prayer tracker" --category books --limit 50

# Export ranked keywords and grouped listing recommendations
uv run main.py --seo-keywords "desk planner" --category office --limit 50 --export-csv seo.csv --export-json seo.json

Discover and analyze trending keywords:

# Discover trending products from Amazon Movers & Shakers (books category)
uv run main.py --trend-hunt

# Discover trends in a specific category
uv run main.py --trend-hunt tshirts
uv run main.py --trend-hunt merch

# Validate seed keywords with Google Trends and boost niche scores
uv run main.py --seed "coloring book for" --trend-boost

# Auto-discover trending keywords and run full niche analysis on each
uv run main.py --auto-trends

# Auto-trends with custom limit and category
uv run main.py --auto-trends tshirts --limit 5
uv run main.py --auto-trends books --limit 10

Customize scoring and filtering:

# Show top 30 niches with score ≥ 50
uv run main.py --seed "sticker" --min-score 50 --top 30

# Explore 3 levels deep with lower competition threshold
uv run main.py --seed "notebook" --depth 3 --threshold 1000

# Slow down requests and stop after 2 blocked/failed keywords
uv run main.py --seed "planner" --min-delay 4 --max-delay 9 --max-block-failures 2

# Enable Playwright browser rendering fallback for pages requests cannot parse
uv run main.py --seed "coffee mug" --category kitchen --browser-fallback

Command-Line Options

Full Research Pipeline Options

Option	Description	Default
`--research`	Run the full research pipeline: one seed → ranked niches with rationale + keyword clusters	Disabled
`--max-niches`	Maximum number of niche opportunities to return in research mode	`5`
`--keywords-per-niche`	Number of SEO keywords to generate per winning niche	`30`
`--candidate-budget`	Maximum candidate keywords to explore in research mode	`60`
`--use-trends`	Enrich research results with Google Trends data	Disabled
`--min-opportunity-score`	Minimum opportunity score threshold for research mode	`40`

Trend Hunter Options

Option	Description	Default
`--trend-hunt`	Discover trending products from Amazon Movers & Shakers (optional category: books, tshirts, merch)	Disabled
`--trend-boost`	Validate seed keywords with Google Trends and boost niche scores	Disabled
`--auto-trends`	Auto-discover trending keywords then run full niche analysis on each (optional category: books, tshirts, merch)	Disabled

Niche Discovery Options

Option	Description	Default
`--seed`	Seed keyword(s) to explore (can provide multiple)	`"coloring book for"`
`--category`	Amazon category (books, kitchen, sports, etc.)	`books`
`--depth`	Exploration depth (1-5 levels)	`2`
`--threshold`	Max results for low competition	`2000`
`--min-price`	Minimum average price filter	`0`
`--max-price`	Maximum average price filter	`unlimited`
`--bsr-min`	Minimum Best Sellers Rank bound — skip niches where all BSRs are below this	None
`--bsr-max`	Maximum Best Sellers Rank bound — skip niches where all BSRs are above this	None
`--min-score`	Minimum overall score to display	`60`
`--top`	Number of top niches to show	`20`

SEO & Analysis Options

Option	Description	Default
`--seo-keywords`	Generate Amazon listing keyword recommendations for one niche	None
`--limit`	Number of trending keywords to analyze with `--auto-trends` or SEO keywords to return	`3`
`--export-csv`	Export to CSV file	None
`--export-json`	Export to JSON file	None

Request & Rendering Options

Option	Description	Default
`--browser-fallback`	Enable Playwright rendering fallback after request parse failures	Disabled
`--no-browser-fallback`	Force requests-only mode	Default
`--min-delay`	Minimum delay between requests (seconds)	`2`
`--max-delay`	Maximum delay between requests (seconds)	`7`
`--request-timeout`	HTTP/browser page-load timeout in seconds	`10`
`--max-block-failures`	Stop after consecutive blocked/failed keyword attempts	`3`
`--max-retries`	Request retry attempts per keyword	`3`

Example Output

Classic Niche Discovery Mode

================================================================================
🎯 Amazon Niche Finder v2.0
================================================================================
Category: kitchen
Exploration Depth: 2 levels
Competition Threshold: 2,000 results
Price Range: $15.00 - $50.00
================================================================================

🔍 Exploring: coffee mug (depth 1/2)
  🟢 Score: 78.5 | Results: 1,247 | Price: $18.99 | Reviews: 156 | Est. Searches: 4,200/mo
  ↳ Exploring: coffee mug with lid (depth 2/2)
    🟢 Score: 82.3 | Results: 892 | Price: $22.50 | Reviews: 203 | Est. Searches: 3,600/mo
  ↳ Exploring: insulated coffee mug (depth 2/2)
    🟡 Score: 71.2 | Results: 3,421 | Price: $24.99 | Reviews: 412 | Est. Searches: 5,100/mo
  ...

🏆 TOP 12 NICHES (Ranked by Overall Score)

🥇 #1: personalized coffee mug for mom
   ────────────────────────────────────────────────────────────────────────────
   Overall Score: 86.7/100
   Competition: 567 results (score: 95.0)
   Price: $26.50 avg (range: $18.99-$34.99) (score: 80.0)
   Demand: 178 avg reviews (score: 80.0)
   Rating: 4.6/5.0 stars
   🏆 2 bestseller(s) in results
   Avg BSR: #42,318 (range #12,500-#98,700)
   Specificity: 87.5 (more specific = better niche)
   🟢 Competitor Strength: 78.5/100 (GOOD opportunity)
      ✅ Small Sellers: 15/20 products
      Market: Diverse
      Barrier to Entry: Low
      Top Brands: CustomGifts, PersonalCreations, GiftPro
      Avg Competitor Reviews: 145
   Depth: Level 2
   Parent: coffee mug for mom

Full Research Pipeline Mode

================================================================================
🔬 FULL RESEARCH REPORT
================================================================================
Seed keyword  : muslim prayer tracker
Category      : books
Generated at  : 2024-11-15T14:32:08
Duration      : 183.4s
Keywords explored : 48
Products analysed : 312
Niches found      : 5
================================================================================

🥇  #1: muslim prayer habit tracker journal
   ────────────────────────────────────────────────────────────────────────────
   🟢 Opportunity: STRONG (score: 74.2/100)
   Overall score: 81.5 | Results: 643 | Est. searches: 2,400/mo (medium confidence)
   Price: $12.99 avg ($8.99–$18.99)
   Avg reviews: 87
   Avg BSR: #38,204 (range #12,000-#89,500)
   🟡 Competitors: GOOD (72/100) | barrier: low

   ✅ Strengths:
      • Moderate search demand: ~2,400 estimated monthly searches.
      • Low competition: only 643 search results — easy to rank.
      • Acceptable price point: $12.99 average.
      • Low barrier to entry: avg competitor reviews 87, 14/18 small sellers.
      • Diverse market: no single brand dominates, easier to gain shelf space.
      • Well-targeted niche: keyword specificity score 72/100.

   🔑 Keyword Clusters:
      [title] muslim prayer tracker, islamic prayer journal, prayer habit tracker (+2 more)
      [bullets] daily prayer log book, salah tracker notebook, namaz journal (+8 more)
      [long_tail] muslim prayer habit tracker for adults, islamic daily prayer planner journal (+12 more)
      [backend] ramadan, salah, dua, quran, ummah (+18 more)

Understanding the Scores

Overall Score (0-100)

The composite score that ranks niche quality in classic mode:

80-100: Excellent opportunity - low competition, good demand, strong revenue potential
60-79: Good opportunity - worth investigating further
40-59: Moderate opportunity - might work with the right strategy
0-39: Weak opportunity - probably too competitive or low demand

Opportunity Score (Research Mode)

The primary ranking signal used by the --research pipeline. It weights free-signal demand estimates and competitor weakness more heavily than the classic overall score:

70-100: Strong opportunity — prioritize these
50-69: Moderate — worth investigating
40-49: Borderline — included only if better options are unavailable
<40: Filtered out by default (see --min-opportunity-score)

Competition Score

90-100: Sweet spot (100-1000 results) - low competition with proven demand
70-89: Acceptable (1000-5000 results) - competitive but manageable
50-69: High competition (5000-10000 results) - challenging
0-49: Very high competition (>10000 results) - difficult to rank

Price Score

Higher prices generally mean better revenue potential:

100: $50+ average price
95: $30-50 average price
80: $20-30 average price
60: $10-20 average price
30: <$10 average price

Demand Score

Based on review counts and bestseller badges:

90-100: Strong proven demand (200-500 reviews, bestsellers present)
70-89: Good demand (50-200 reviews)
50-69: Moderate demand (10-50 reviews)
20-49: Low demand (<10 reviews or no data)

Estimated Monthly Searches

The estimated_monthly_searches field is a directional estimate, not an exact Amazon visitor or search-volume count. It combines free signals such as Amazon autocomplete expansion, result count, average reviews, bestseller badges, sponsored results, the internal demand score, and Google Trends when available. Use it to compare keywords relative to each other, then validate manually before making product decisions.

Related export fields:

estimated_monthly_searches: Directional monthly search volume estimate
demand_estimate_score: Confidence score (0-100) for the estimate
demand_estimate_confidence: Confidence level (low, medium, high) based on signal availability
trend_score: Google Trends-derived score (when using --trend-boost, --auto-trends, or --use-trends)
trend_direction: rising, falling, stable, or unknown

Specificity Score

Longer, more specific keywords are better niches:

Higher word count = more specific = less competition
Longer character count = more detailed = better targeting

Competitor Strength Score

Analyzes who you're actually competing against (0-100, higher = weaker competition):

80-100: Mostly small sellers with low reviews — excellent opportunity
60-79: Mix of small/medium sellers — good opportunity
40-59: Some major brands present — moderate difficulty
0-39: Dominated by Amazon/major brands — very difficult

Factors analyzed:

Amazon-owned brands (Amazon Basics, Solimo, etc.) — major penalty
Major established brands (Nike, Sony, KitchenAid, etc.) — moderate penalty
Average competitor reviews (higher = harder to compete)
Market concentration (monopolized vs diverse)
Small seller presence (more small sellers = better opportunity)

Best Sellers Rank (BSR)

Products with a lower BSR number sell more units per day. The tool tracks:

avg_bsr: Average BSR across analyzed products in the niche
bsr_range: Lowest (best) and highest (worst) BSR seen in results

Use --bsr-max to exclude high-BSR (slow-moving) niches, or --bsr-min to avoid ultra-competitive products ranked in the top hundreds.

Profitability Rationale (Research Mode)

Each NicheOpportunity in --research mode includes a ProfitabilityRationale with:

Strengths: Concrete, metric-backed sentences explaining positive signals
Weaknesses: Concrete sentences describing risks or barriers
Verdict: strong, moderate, or weak
Opportunity Score: 0-100 composite used for ranking

How It Works

Full Research Pipeline (`--research`)

Candidate Generation: Builds a deduplicated keyword candidate list from:
- Direct autocomplete for the seed
- Alphabet expansion (seed + a–z)
- Modifier prefix/suffix expansions (best, top, for, gift, etc.)
- Second-hop title-word expansions from top suggestions
- Trend-derived seeds (when --use-trends is enabled)
Niche Analysis: Scores each candidate using analyze_niche (same engine as classic mode)
Trend Enrichment: Attaches Google Trends direction and score when --use-trends is set
Opportunity Ranking: Sorts all niches by opportunity score and selects top --max-niches winners
Keyword Research: Generates --keywords-per-niche SEO keywords for each winner and clusters them into listing slots
Rationale Generation: Produces plain-English profitability explanations for every winner
Report Assembly: Combines everything into a ResearchReport and prints/exports it

Standard Niche Discovery

Seed Exploration: Starts with your seed keyword(s)
Suggestion Gathering: Fetches Amazon autocomplete suggestions
Product Analysis: Scrapes search results to extract:
- Result counts
- Product prices
- Review counts and ratings
- Bestseller badges
- Sponsored ads
- Best Sellers Rank (BSR)
Scoring: Calculates comprehensive scores for each niche
Recursive Exploration: Uses promising keywords as new seeds
Block Handling: Detects CAPTCHA, robot-check, 429, suspicious redirects, and invalid result pages
Reporting: Ranks and presents the best opportunities, including partial results when collection stops early

Trend Hunting

Movers & Shakers Discovery: Scrapes Amazon's Movers & Shakers page for rapidly rising products
Keyword Extraction: Converts product titles into searchable keywords
Google Trends Validation: Optional validation against Google Trends to detect momentum
Trend Direction Detection: Identifies if keywords are rising, falling, stable, or unknown
Trend Scoring: Converts Google Trends momentum into a niche score boost
Full Analysis: Can run complete niche analysis on each discovered trend (--auto-trends)

Tips for Finding Great Niches

Use --research for the Best Results: One seed keyword → ranked niches with rationale and keyword packs in a single run
Start Broad, Go Deep: Use general seed keywords and let the tool find specific sub-niches
Multiple Seeds: In classic mode, provide 2-3 related seeds for better coverage
Right Depth: Depth 2 is usually optimal; depth 3 for thorough exploration
Price Matters: Use --min-price to filter out low-margin products
Use BSR Filtering: --bsr-max 200000 removes niches with very slow-selling products
Trust the Score: Niches scoring 75+ (overall) or 60+ (opportunity) are usually worth investigating
Validate Manually: Always check top results on Amazon to confirm opportunity
Check Trends: Use --use-trends (in research mode) or --trend-boost to verify search momentum
Analyze Competition: Look at top competitors' reviews to find improvement opportunities

Trend Hunting Tips

--trend-hunt: Quick discovery of what's trending on Amazon — great for brainstorming
--trend-boost: Validate your existing seed keywords against Google Trends to find rising opportunities
--auto-trends: Most powerful trend tool — automatically discovers 3-10 trending keywords and runs full analysis on each
--use-trends (research mode): Integrates trend enrichment directly into the research pipeline for seamless output
Trend Timing: Rising trends offer the best entry point — catch them early before competition saturates
Combine with Depth: Use --trend-hunt to discover seeds, then run with --depth 3 for deeper exploration
Monitor Seasonality: Google Trends data helps identify seasonal niches with predictable demand spikes

Limitations & Best Practices

Rate Limiting: Built-in conservative delays (2-7 seconds by default) reduce request pressure — be patient
Block-Aware Stopping: The tool stops after repeated blocked or failed keyword attempts and preserves partial results
Browser Fallback: The Playwright fallback renders real browser pages using your local Brave/Chrome or the bundled Chromium. It does not bypass CAPTCHA, rotate proxies, or use fingerprint-spoofing libraries. Set PLAYWRIGHT_BROWSER_PATH to point to your browser binary, or run uv run playwright install chromium to use the bundled version.
Result Count Cap: Amazon often shows "over 10,000" which caps accuracy
HTML Changes: Amazon occasionally changes their page structure
No Guarantee: Low competition doesn't guarantee sales — validate demand!
Scraping Ethics: Use responsibly and comply with Amazon's ToS
Research Mode — Single Seed: --research uses only the first --seed value; run separately for each seed

Troubleshooting

If you see repeated blocked or invalid responses, increase --min-delay and --max-delay, reduce --depth, or stop and try again later.
If product cards are missing because the page requires browser rendering, install Playwright (uv run playwright install chromium) and run with --browser-fallback.
If you're missing dependencies, run uv sync to install them.
If the Playwright fallback can't find your browser, set the PLAYWRIGHT_BROWSER_PATH environment variable to the full path of your Brave or Chrome executable.
Automated tests do not make live Amazon calls; run them with uv run pytest.

Requirements

Python 3.9+
requests
beautifulsoup4
urllib3
playwright (uv run playwright install chromium after uv sync)
pytrends
pytest (dev only)

License

This project is licensed under the MIT License — see the LICENSE file for details.

Disclaimer

This tool is for educational and research purposes only. Users are responsible for complying with Amazon's terms of service and implementing appropriate rate limiting. There is no guarantee that any discovered niche will be profitable. Always conduct thorough market research before making business decisions.

More projects

Amazon Niche Finder v4.0

What's New in v4.0

Key Features

Intelligent Exploration

Full Research Pipeline

Comprehensive Analysis

Advanced Scoring Algorithm

Competitor Strength Analysis

Multi-Category Support

Professional Exports

Trend Hunting & Validation

Installation

Usage

Basic Usage

Recommended: Full Research Pipeline

Advanced Usage Examples

Command-Line Options

Full Research Pipeline Options

Trend Hunter Options

Niche Discovery Options

SEO & Analysis Options

Request & Rendering Options

Example Output

Classic Niche Discovery Mode

Full Research Pipeline Mode

Understanding the Scores

Overall Score (0-100)

Opportunity Score (Research Mode)

Competition Score

Price Score

Demand Score

Estimated Monthly Searches

Specificity Score

Competitor Strength Score

Best Sellers Rank (BSR)

Profitability Rationale (Research Mode)

How It Works

Full Research Pipeline (--research)

Standard Niche Discovery

Trend Hunting

Tips for Finding Great Niches

Trend Hunting Tips

Limitations & Best Practices

Troubleshooting

Requirements

License

Disclaimer

More projects

Full Research Pipeline (`--research`)