# KDP Market Intel Scraper – Kindle Category Rank & Pricing (`conceivable_extension/kdp-market-intel-scraper`) Actor

Track Amazon KDP category best-seller rank within Kindle Store subcategories, Kindle Unlimited enrollment, and pricing bands — the fields general Amazon scrapers miss. Built for self-publishers and KDP authors monitoring their own catalog and competitor pricing.

- **URL**: https://apify.com/conceivable\_extension/kdp-market-intel-scraper.md
- **Developed by:** [joseph fadero](https://apify.com/conceivable_extension) (community)
- **Categories:** Integrations, Automation, E-commerce
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $5.00 / 1,000 category result fulls

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?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## KDP Market Intel Scraper – Kindle Category Rank, KU Status & Pricing

**Track what general Amazon scrapers miss: Kindle Store category best-seller rank, Kindle Unlimited enrollment, and KDP-relevant pricing bands.**

Amazon KDP has no dedicated Apify actor. General Amazon product scrapers (price, rating, review count) don't surface the fields self-publishers actually need: where a title ranks *within its Kindle Store subcategory*, whether it's enrolled in Kindle Unlimited, and keyword-to-listing competitiveness.

### Who it's for

- Self-publishers tracking where their own titles rank across categories
- Publishers scouting pricing gaps in a target category before launch
- KDP authors monitoring competitor pricing and KU status

### Modes

| Mode | Input | What you get |
|---|---|---|
| `category_snapshot` | `categoryUrls` | Full ranked list (up to 100) for a Kindle bestseller category page — rank, title, author, price, KU flag |
| `keyword_search` | `keywords` | Kindle Store search results for a keyword, in relevance order |
| `asin_lookup` | `asins` | Full single-title detail: category breadcrumb, subcategory rank, publication date, print length |

### Field availability by mode

Amazon splits this data across three different page types, so not every field is populated by every mode. This is a deliberate trade-off, not a bug — visiting a full product page per title would multiply run time and cost 10-20x for a 100-item category scan.

| Field | category\_snapshot | keyword\_search | asin\_lookup |
|---|---|---|---|
| `categoryRank` | ✅ Amazon's rank badge | ⚠️ search-result position (not an Amazon BSR) | ✅ subcategory BSR |
| `categoryPath` | ✅ page breadcrumb (same for all items) | ❌ not shown on search cards | ✅ full breadcrumb |
| `estimatedMonthlySalesRank` | ❌ | ❌ | ✅ store-wide Kindle BSR number |
| `publicationDate`, `pageCountOrLength` | ❌ | ❌ | ✅ |
| `price`, `reviewCount`, `reviewAverage`, `isKindleUnlimited` | ✅ | ✅ | ✅ |

`estimatedMonthlySalesRank` is Amazon's own store-wide "Bestsellers Rank" number pulled from the detail page — not a modeled sales-volume estimate. No sales curve is fabricated; the field name mirrors the PRD spec but the value is the real BSR figure Amazon publishes.

### Input schema

```json
{
  "mode": "category_snapshot",
  "categoryUrls": ["https://www.amazon.co.uk/gp/bestsellers/digital-text/..."],
  "marketplace": "amazon.co.uk",
  "maxResultsPerCategory": 100
}
```

See `.actor/input_schema.json` for the full field list (all three modes share one input object; only the mode-relevant array is required).

### Output schema

```json
{
  "asin": "string",
  "title": "string | null",
  "author": "string | null",
  "categoryPath": ["Kindle Store", "..."],
  "categoryRank": "number | null",
  "price": "number | null",
  "currency": "string",
  "isKindleUnlimited": "boolean",
  "estimatedMonthlySalesRank": "number | null",
  "reviewCount": "number | null",
  "reviewAverage": "number | null",
  "publicationDate": "string | null",
  "pageCountOrLength": "string | null",
  "scrapedAt": "ISO timestamp",
  "status": "success | failed",
  "errorMessage": "string | null"
}
```

### Pricing

| Event | Price |
|---|---|
| Run started | £0.05 |
| Item scraped | £0.004 |
| Item failed | £0.001 |

Matches the portfolio's Section 1 (run-started) convention from Actor 12 (Amazon Seller Intelligence).

### Setup note

No API keys required. Residential proxy strongly recommended — Amazon's bot detection is aggressive on datacenter IPs, same as Actor 12.

**Before production use:** the bestseller-grid and search-result selectors in `src/scraper/kdpCategoryScraper.ts` and `src/scraper/kdpSearchScraper.ts` were written against Amazon's documented DOM patterns but not verified against live pages from this environment (no network access at build time). Per the build PRD's Definition of Done, run against 3 real KDP categories and manually verify rank/price/KU accuracy for ~20 known titles before relying on this in production — tune the selector fallback lists in those two files if Amazon's markup has drifted.

### Related actor

[Amazon Seller Intelligence](../Amazon%20Seller%20Intelligence/amazon-seller-intelligence) — this actor extends its Playwright scraping core (currency resolution, price parsing, bot-detection handling) for Kindle-specific fields.

### n8n integration

- **Workflow A (trigger):** scheduled daily/weekly run against Northbridge Press's own category list, writing to a tracking sheet.
- **Workflow B (processing):** alert (Slack/email) when a tracked title drops out of the top 100 in its category, or a competitor undercuts price by >15%.

# Actor input Schema

## `mode` (type: `string`):

category\_snapshot: rank list for given Kindle bestseller category URLs. keyword\_search: search the Kindle Store by keyword. asin\_lookup: full detail (incl. publication date & page count) for specific ASINs.

## `categoryUrls` (type: `array`):

Amazon Kindle Store bestseller category URLs, e.g. https://www.amazon.co.uk/gp/bestsellers/digital-text/... Required when mode is category\_snapshot.

## `keywords` (type: `array`):

Search terms to look up in the Kindle Store, e.g. 'cottagecore journal'. Required when mode is keyword\_search.

## `asins` (type: `array`):

Specific Kindle ASINs to look up in full detail. Required when mode is asin\_lookup.

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

Which Amazon marketplace's Kindle Store to scrape.

## `maxResultsPerCategory` (type: `integer`):

Cap on how many ranked items to return per category or keyword search. Amazon bestseller lists top out around 100.

## `proxyConfiguration` (type: `object`):

Residential proxy strongly recommended for Amazon. Use Apify Residential proxies.

## Actor input object example

```json
{
  "mode": "category_snapshot",
  "categoryUrls": [
    "https://www.amazon.co.uk/gp/bestsellers/digital-text/"
  ],
  "marketplace": "amazon.co.uk",
  "maxResultsPerCategory": 100
}
```

# Actor output Schema

## `resultsDatasetUrl` (type: `string`):

Kindle Store category rank, Kindle Unlimited enrollment status, and pricing data for the tracked titles or categories, produced by this run.

# 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 = {
    "categoryUrls": [
        "https://www.amazon.co.uk/gp/bestsellers/digital-text/"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("conceivable_extension/kdp-market-intel-scraper").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 = { "categoryUrls": ["https://www.amazon.co.uk/gp/bestsellers/digital-text/"] }

# Run the Actor and wait for it to finish
run = client.actor("conceivable_extension/kdp-market-intel-scraper").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 '{
  "categoryUrls": [
    "https://www.amazon.co.uk/gp/bestsellers/digital-text/"
  ]
}' |
apify call conceivable_extension/kdp-market-intel-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,conceivable_extension/kdp-market-intel-scraper"
        }
    }
}

```

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/quiO1rZa4rTwW5jaT/builds/OxjhhfJ6cy7si8cio/openapi.json