# HubSpot App Marketplace Intelligence (`quanmatrix/hubspot-app-marketplace-intelligence`) Actor

Use this Actor to analyze hubspot app marketplace and return decision-ready structured signals. Analyze HubSpot App Marketplace datasets to detect growth, pricing drift, rating changes, adoption momentum, new entrants and competitive opportunity.

- **URL**: https://apify.com/quanmatrix/hubspot-app-marketplace-intelligence.md
- **Developed by:** [Rafael Barreto Haddad](https://apify.com/quanmatrix) (community)
- **Categories:** Lead generation, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $8.40 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

## HubSpot App Marketplace Intelligence

Use this Actor to analyze hubspot app marketplace and return decision-ready structured signals. It is designed for repeatable human, API, Apify AI, and MCP-driven workflows.

Analyze HubSpot App Marketplace datasets to detect growth, pricing drift, rating changes, adoption momentum, new entrants and competitive opportunity.

### Why use this Actor

HubSpot Marketplace pages answer what exists right now, but vendor and integration research also needs publisher and contact coverage. Product, strategy and competitive-intelligence teams usually need a different question answered: what changed, what is accelerating, which competitors are gaining adoption, where pricing is moving, and which categories deserve attention. This Actor turns recurring HubSpot App Marketplace exports into a stable decision layer. It can use inline rows or Apify Datasets, so teams can pair it with an existing scraper, their own data collection, or scheduled snapshots without rebuilding the analysis workflow.

### Key features

- Compare current and previous marketplace snapshots.
- Detect new and removed listings, pricing changes and rating drift.
- Measure adoption and review growth when those fields are present upstream.
- Rank leading listings using normalized adoption, review and rating signals.
- Produce a deterministic `marketMomentumScore` and a machine-friendly `agentAction`.
- Compare publisher concentration and category cohorts, and count vendor-lead records when public contact fields are supplied.
- Work with supplied datasets instead of requiring credentials or private marketplace access.

The Actor deliberately separates collection from intelligence. That reduces proxy cost, avoids unnecessary anti-bot coupling, and lets the same analysis run on different upstream collectors as the ecosystem changes.

### Input

Provide `currentItems` directly or select a `currentDatasetId`. For longitudinal analysis also provide `previousItems` or `previousDatasetId`. Common fields such as title/name, publisher/vendor, price, rating, reviews, users/installs/downloads, rank and URL are normalized automatically. Missing optional metrics do not cause the run to fail.

### Output

Each run writes one decision-ready report containing listing counts, entrant/removal counts, price-change count, rating changes, adoption growth, review growth, a market momentum score, top listings, new listings and the recommended `agentAction`. The report is also stored in the `MARKET_INTELLIGENCE` key-value record.

### Example

Use a weekly snapshot from HubSpot App Marketplace as `currentDatasetId` and the prior week's dataset as `previousDatasetId`. The Actor can then identify new entrants, price moves, rating deterioration, adoption acceleration and category leaders without manually comparing exports.

### Use cases

Developers can monitor competitors before shipping a new product. Product managers can watch pricing and category crowding. Agencies can benchmark client ecosystems. Investors and analysts can detect adoption shifts across software marketplaces. QuantMatrix-style product factories can use the score as one input when deciding which niches deserve further research.

### Pricing

This Actor uses pay-per-event pricing. The base price is **USD 0.0120 per decision-ready intelligence report**. Billing is attached to the primary result rather than every raw source row, keeping the commercial unit aligned with user value. Apify subscription tiers may receive lower effective event prices.

### Limitations

The Actor analyzes public-data exports supplied by the user or another Apify Actor. It does not unlock private seller analytics, bypass authentication, or guarantee that every upstream marketplace exposes installs, sales, ratings or price. When an upstream scraper changes its field names, the generic normalizer covers common aliases but specialized mapping can still be useful. Decisions should use the score as structured evidence, not as a substitute for domain judgment.

### Automation pattern

Schedule the upstream collector, save each run as a dated Dataset, then run this Actor with the newest and previous Dataset IDs. Store the resulting score and action in a dashboard, webhook, workflow or downstream agent. That creates recurring marketplace intelligence while keeping collection, analysis and action independently replaceable.

# Changelog

This Actor's version history is a separate document: https://apify.com/quanmatrix/hubspot-app-marketplace-intelligence/changelog.md

# Actor input Schema

## `currentItems` (type: `array`):

Current normalized or raw marketplace listing rows.

## `currentDatasetId` (type: `string`):

Optional Dataset ID used when currentItems is not supplied.

## `previousItems` (type: `array`):

Optional previous marketplace snapshot.

## `previousDatasetId` (type: `string`):

Optional previous Dataset ID.

## `maxItems` (type: `integer`):

Maximum rows loaded from an Apify Dataset.

## `mcpConnectors` (type: `array`):

Optional MCP connectors authorized in your Apify account. Use them to send or write this Actor result to tools such as Slack, Notion, GitHub, Sentry, Supabase, or another compatible MCP service.

## `mcpToolName` (type: `string`):

Optional exact MCP tool name. Leave blank to let the selected MCP action preset discover a compatible tool automatically.

## `mcpToolArguments` (type: `object`):

JSON object passed to the selected MCP tool. String values may use {{actor\_title}}, {{result\_summary}}, or {{result\_json}} placeholders.

## `mcpFailOnError` (type: `boolean`):

When enabled, an MCP delivery error fails the Actor run. Disabled by default so data extraction and intelligence results remain available even if the external destination is unavailable.

## `mcpActionPreset` (type: `string`):

Choose a safe action pattern. AUTO\_SAFE\_WRITE discovers a compatible non-destructive write tool automatically; use a specific preset for Slack, GitHub, Notion, or database delivery.

## Actor input object example

```json
{
  "currentItems": [
    {
      "id": "a",
      "name": "Alpha App",
      "publisher": "Vendor A",
      "category": "Productivity",
      "price": 9,
      "rating": 4.6,
      "reviews": 120,
      "users": 5000,
      "rank": 4
    },
    {
      "id": "b",
      "name": "Beta Tool",
      "publisher": "Vendor B",
      "category": "Analytics",
      "price": 15,
      "rating": 4.3,
      "reviews": 75,
      "users": 2300,
      "rank": 12
    }
  ],
  "maxItems": 20000,
  "mcpToolName": "",
  "mcpToolArguments": {},
  "mcpFailOnError": false,
  "mcpActionPreset": "AUTO_SAFE_WRITE"
}
```

# Actor output Schema

## `dataset` (type: `string`):

No description

## `report` (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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("quanmatrix/hubspot-app-marketplace-intelligence").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("quanmatrix/hubspot-app-marketplace-intelligence").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 '{}' |
apify call quanmatrix/hubspot-app-marketplace-intelligence --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,quanmatrix/hubspot-app-marketplace-intelligence"
        }
    }
}
```

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/th1RBj4XpdcxyUcPZ/builds/fAaGuGahwlB1nJv71/openapi.json