# Amazon Book & T-Shirt Niche Analyzer (`vncntlabs/amazon-book-tshirt-niche-analyzer`) Actor

Amazon niche research for low-content books, Kindle and print-on-demand t-shirts. One keyword in, one report out: Amazon search volume, top-20 price and review spread, Best Sellers Rank, publish dates, self-publisher share and a USPTO trademark screen. Pay per niche.

- **URL**: https://apify.com/vncntlabs/amazon-book-tshirt-niche-analyzer.md
- **Developed by:** [VNCNT Labs](https://apify.com/vncntlabs) (community)
- **Categories:** E-commerce, AI, SEO tools
- **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$150.00 / 1,000 niche reports

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Amazon Book & T-Shirt Niche Analyzer: BSR, Reviews & Search Volume

Give it a niche keyword and get back **one Amazon niche report**: how often shoppers search it on Amazon, how many
products compete, the **price, rating and review spread of the top 20 results**, the **Best Sellers Rank** of the top
products, how old they are, how many are **self-published**, a **USPTO trademark screen** of the phrase, and plain
**demand / competition labels** with the numbers behind them. Built for self-publishers of low-content books (for
example on Kindle Direct Publishing), Kindle authors and print-on-demand t-shirt sellers (for example on Merch by
Amazon), and for AI assistants (MCP). **Pay per niche.** Failed niches are never charged.

### What's in each report

- **Amazon search volume**: monthly searches for the phrase on Amazon (US, UK, DE, FR, IT, ES, CA, AU, IN, MX, NL)
- **Market size**: total results Amazon reports for the search, sponsored products on page 1
- **Top 20 results**: median / min / max price, average rating, median and max reviews, share with under 100 and under 20 reviews, "bought in past month" figures Amazon shows, Best Seller and Amazon's Choice badges
- **Top product pages** (10 by default, up to 20): main-category Best Sellers Rank (median, best, how many under 100,000), sub-category ranks, publication / first-available date (median age, new in the last 90 and 365 days), publisher (self-published share for books), median page count
- **Trademark screen**: the niche phrase checked against live USPTO marks in the classes for your product type (books IC 016/009, shirts IC 025), with risk level and flagged phrases
- **Signals**: `demand` (strong / moderate / weak) from median Best Sellers Rank and `competition` (low / medium / high) from median reviews, each with its basis spelled out
- **Products list**: rank, ASIN, title, link, price, rating, reviews, BSR, sub-category ranks, author / brand, publisher and date for the top 20

### Use cases

- **Low-content book research**: compare journals, planners and logbooks before you design one
- **Print-on-demand t-shirts**: check how crowded a t-shirt phrase is and whether it's trademarked
- **Kindle niches**: see how established the top books are and how many are self-published
- **AI agents**: one call gives Claude or ChatGPT the numbers to rank a list of niche ideas

### Input

| Field | What it does |
| --- | --- |
| `niches` | One report per niche keyword (up to 50 per run) |
| `productType` | `paperback` (Books department, default), `kindle` (Kindle Store), `t-shirt` (adds "t-shirt" to the search) or `any` |
| `marketplace` | Amazon store: US (default), GB, DE, FR, IT, ES, CA, AU, IN, MX, JP, NL |
| `productsToAnalyze` | Product pages read per niche, 3-20 (default 10). Same price for any value |
| `trademarkCheck` | USPTO screen of the niche phrase (default on) |

```json
{ "niches": ["gardening journal", "dog mom"], "productType": "paperback", "marketplace": "US" }
```

### Output (one row per niche)

```json
{
  "type": "niche", "niche": "gardening journal", "status": "ok", "amazonSearchVolume": 224, "totalResults": 55304,
  "signals": { "demand": "moderate", "competition": "medium", "selfPublishedShare": 0.4, "newcomerShare365d": 0.2 },
  "searchStats": { "priceMedian": 9.99, "reviewsMedian": 120, "shareUnder100Reviews": 0.45, "sponsoredOnPage": 12 },
  "productStats": { "bsrCategory": "Books", "bsrMedian": 180000, "bsrBest": 61631, "pagesMedian": 120 },
  "trademark": { "risk": "none", "classesChecked": ["016", "009"] },
  "products": [ { "rank": 1, "asin": "1441332782", "title": "The Gardener's Logbook", "bestSellersRank": 61631 } ]
}
```

Values above are illustrative of the shape; every run returns live numbers. Rows with `status` `partial`, `error` or
`no_results` are not charged. A run summary (cost, timing, warnings) is saved as `OUTPUT` in the key-value store.

### How the labels work

| Label | Basis | Thresholds |
| --- | --- | --- |
| `demand` | median main-category Best Sellers Rank of the analyzed products | Paperback: strong < 50,000 ≤ moderate < 300,000 ≤ weak. Kindle: 30,000 / 200,000. T-shirts: 100,000 / 1,000,000 |
| `competition` | median review count of the top 20 organic results | low < 50 ≤ medium < 300 ≤ high |

The labels are a starting point, not a forecast. **We don't estimate sales or royalties**: Amazon doesn't publish
them, and BSR-to-sales formulas vary widely, so you get the measured numbers instead.

### Pricing

**$0.15 per niche report** (pay per event, no start fee). A niche is charged only when the Amazon search, the search
volume lookup and most product pages came back. Searches with no results are not charged.

- 1 niche = $0.15. 50 niches = $7.50.
- Apify free plan: up to 2 niches per run.
- Your run's maximum charge is respected: the run stops before going over it.

### Use from AI agents (MCP)

Add this Actor to Claude, Cursor or any MCP client through Apify's hosted MCP server:
`https://mcp.apify.com/?tools=vncntlabs/amazon-book-tshirt-niche-analyzer`. Ask for example: *"Compare these 5 journal niches on
Amazon and tell me which has the least competition."* A run takes about 3-5 minutes.

### FAQ

**Where does the data come from?** Amazon search results, product pages and Amazon search volumes come through
DataForSEO's licensed APIs. This Actor doesn't scrape Amazon or log in anywhere. Trademark data comes from the USPTO's
public bulk files.

**How fresh is it?** Search results and product pages are read live in each run. Search volumes are monthly averages.

**Why do some products have no BSR or date?** Amazon doesn't show them on every product page, and now and then a product
page returns no data. The report says how many pages were read.

**Is the trademark screen legal advice?** No. It flags live USPTO marks that match words in your niche phrase. Check
anything flagged with the USPTO or a lawyer before you publish.

**Is this affiliated with Amazon?** No. VNCNT Labs is not affiliated with, endorsed or sponsored by Amazon. Amazon,
Kindle, Kindle Direct Publishing (KDP) and Merch by Amazon are trademarks of Amazon.com, Inc. or its affiliates, named
here only to describe what the tool helps with.

### Related tools by VNCNT Labs

- [POD Trademark Checker](https://apify.com/vncntlabs/pod-trademark-checker) to screen whole listings
- [Keyword Search Volume](https://apify.com/vncntlabs/keyword-search-volume) for Google and Amazon volumes in bulk
- [Amazon Product Scraper](https://apify.com/vncntlabs/amazon-product-scraper) for full product data

Questions or a missing field? Open an issue on the Actor's page or write to hello@vncntlabs.com.

# Actor input Schema

## `niches` (type: `array`):

One report per niche, e.g. 'gardening journal', 'dog mom', 'nurse planner'. Up to 50 per run.

## `productType` (type: `string`):

paperback = Amazon Books department (low-content books, journals, planners); kindle = Kindle Store; t-shirt = adds 't-shirt' to the search (print on demand); any = all departments.

## `marketplace` (type: `string`):

Amazon store to analyze. Search volume is available for US, GB, DE, FR, IT, ES, CA, AU, IN, MX and NL.

## `productsToAnalyze` (type: `integer`):

How many of the top organic results get a product-page read (Best Sellers Rank, publish date, publisher, pages). Same price for any value.

## `trademarkCheck` (type: `boolean`):

Screens the niche phrase against live USPTO marks in the classes that matter for the product type (books: IC 016/009, shirts: IC 025). A screen, not legal advice.

## Actor input object example

```json
{
  "niches": [
    "gardening journal"
  ],
  "productType": "paperback",
  "marketplace": "US",
  "productsToAnalyze": 10,
  "trademarkCheck": true
}
```

# Actor output Schema

## `niches` (type: `string`):

No description

## `summary` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "niches": [
        "gardening journal"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("vncntlabs/amazon-book-tshirt-niche-analyzer").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "niches": ["gardening journal"] }

# Run the Actor and wait for it to finish
run = client.actor("vncntlabs/amazon-book-tshirt-niche-analyzer").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "niches": [
    "gardening journal"
  ]
}' |
apify call vncntlabs/amazon-book-tshirt-niche-analyzer --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,vncntlabs/amazon-book-tshirt-niche-analyzer"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/KZ3PtCSZ2pbnq4fIg/builds/b6jiAyGexB8NFYnSZ/openapi.json