# TripAdvisor Property Rank & Competitor Benchmark Tracker (`scrapemint/tripadvisor-property-rank-tracker`) Actor
For hotel operators, restaurant owners, and travel agencies. Tracks daily rank, rating drift, review volume, owner response rate, Travelers' Choice status, claim status, price tier, and amenities for any TripAdvisor hotel, restaurant, or attraction. One row per property. Pay per snapshot.
- **URL**: https://apify.com/scrapemint/tripadvisor-property-rank-tracker.md
- **Developed by:** [Kennedy Mutisya](https://apify.com/scrapemint) (community)
- **Categories:** Automation, Travel, E-commerce
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet
## Pricing
Pay per usage
This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use 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
## TripAdvisor Property Rank Tracker — Hotel & Restaurant Competitor Benchmark
Track daily TripAdvisor rank, rating drift, review volume, and owner response rate for any hotel, restaurant, or attraction. One row per property per run. No reputation SaaS subscription. No rank tracker seat. Pay per snapshot.
**Built for** hotel general managers, restaurant owners, travel agencies, short term rental managers, and BI analysts who want a clean structured feed of TripAdvisor property signals for daily competitor benchmarking, revenue management, and reputation monitoring.
**Keywords this actor ranks for:** tripadvisor rank tracker, tripadvisor api, tripadvisor scraper, hotel rank tracker, hotel competitor benchmark, restaurant rank monitor, tripadvisor hotel ranking, tripadvisor rating tracker, hotel reputation api, certificate of excellence tracker, travelers choice tracker, tripadvisor competitor analysis, hospitality rank monitoring tool.
---
### Why this actor
| Other rank trackers | **This actor** |
|---|---|
| $300 per month per seat | Pay per property snapshot |
| Hotels only | Hotels, restaurants, and attractions |
| Weekly refresh | On demand or daily schedule |
| Rank only | Rank, rating histogram, response rate, badges, claim status, amenities, hotel class |
| English only | Pulls from any TripAdvisor regional domain |
---
### How it works
```mermaid
flowchart LR
A[Property URLs
or destination listing] --> B[Load page
residential proxy]
B --> C[Parse JSON LD
name rating reviews price]
B --> D[Scrape rank text
'#3 of 1,234 hotels in Paris']
B --> E[Sample N reviews
compute response rate]
C --> F[One row per property]
D --> F
E --> F
F --> G[(JSON CSV Excel API)]
````
Two ways in. Paste property URLs to snapshot specific hotels, restaurants, or attractions. Or paste a destination listing URL (Hotels-, Restaurants-, Attractions-) and the actor sweeps the top N properties for that destination so you can run a daily competitor scan in one job.
***
### What you get per row
```mermaid
flowchart LR
R[Property row] --> R1[Identity
id name type url]
R --> R2[Address + geo
locality region country]
R --> R3[Rank
position total percentile]
R --> R4[Rating
overall reviews histogram]
R --> R5[Badges
travelers choice cert claimed]
R --> R6[Owner engagement
response rate sampled]
R --> R7[Property class
price tier amenities]
```
Every snapshot ships clean numeric fields buyers can chart immediately. No string parsing on your side.
***
### Quick start
**Daily competitor sweep for a city's top 25 hotels**
```json
{
"destinationUrls": [
"https://www.tripadvisor.com/Hotels-g60763-New_York_City_New_York-Hotels.html"
],
"maxPerDestination": 25,
"responseRateSampleSize": 30
}
```
**Snapshot a specific property and three rivals**
```json
{
"targetUrls": [
"https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Pierre_A_Taj_Hotel.html",
"https://www.tripadvisor.com/Hotel_Review-g60763-d99352-Reviews-The_Plaza_Hotel.html",
"https://www.tripadvisor.com/Hotel_Review-g60763-d99355-Reviews-The_Carlyle_A_Rosewood_Hotel.html"
],
"responseRateSampleSize": 30
}
```
**Restaurant district benchmark (top 50)**
```json
{
"destinationUrls": [
"https://www.tripadvisor.com/Restaurants-g187147-Paris_Ile_de_France.html"
],
"maxPerDestination": 50,
"responseRateSampleSize": 0
}
```
**Travel agency due diligence on 10 properties**
```json
{
"targetUrls": [
"https://www.tripadvisor.com/Hotel_Review-g60763-d93589-..."
],
"extractAmenities": true,
"extractRatingHistogram": true
}
```
***
### Sample output
```json
{
"id": "d93589",
"url": "https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Pierre_A_Taj_Hotel.html",
"type": "hotel",
"name": "The Pierre, A Taj Hotel",
"address": {
"locality": "New York City",
"region": "New York",
"country": "United States",
"latitude": 40.7659,
"longitude": -73.9710
},
"destination": { "id": "g60763", "name": "New York City", "category": "hotels" },
"rank": { "position": 41, "totalInCategory": 504, "percentile": 91.87, "raw": "#41 of 504 hotels in New York City" },
"rating": {
"overall": 4.5,
"reviewCount": 2371,
"histogram": { "5": 1602, "4": 521, "3": 124, "2": 71, "1": 53 }
},
"badges": {
"travelersChoice": true,
"travelersChoiceYear": 2026,
"certificateOfExcellence": false,
"ownerClaimed": true
},
"ownerEngagement": { "sampleSize": 30, "respondedTo": 24, "responseRatePercent": 80.0 },
"priceTier": "$$$$",
"hotelClass": 5,
"amenities": ["Free WiFi", "Pool", "Spa", "Pet friendly", "Restaurant", "Concierge"],
"scrapedAt": "2026-04-25T15:30:00.000Z"
}
```
***
### Who uses this
| Role | Use case |
|---|---|
| Hotel general manager | Spot rank slips before they hit revenue. Watch competitor rating drift weekly. |
| Restaurant owner | See response rate gap vs the top 10 local rivals. Alert when a competitor wins Travelers' Choice. |
| Travel agency | Pre vet 50 properties at once for trip packaging. Filter by claim status, response rate, and rating. |
| STR manager | Benchmark your listing against every vacation rental in the area. |
| Reputation SaaS | Drop a paid SaaS subscription. Run this on a schedule and pipe to your own dashboard. |
| BI analyst | Clean JSON or CSV ready for Looker, Metabase, or Snowflake. |
***
### Input reference
| Field | Type | What it does |
|---|---|---|
| `targetUrls` | string\[] | Property URLs to snapshot. One row per URL. |
| `destinationUrls` | string\[] | Destination listing URLs to sweep top N from. |
| `maxPerDestination` | integer | Cap properties processed per destination. Default 25. |
| `responseRateSampleSize` | integer | Reviews sampled per property to compute owner response rate. 0 to skip. |
| `extractAmenities` | boolean | Pull amenity and feature flags. Default true. |
| `extractRatingHistogram` | boolean | Capture review counts by star tier. Default true. |
| `concurrency` | integer | Properties processed in parallel. Two to four is safe. |
| `proxyConfiguration` | object | Apify proxy. Residential is required. |
***
### API call
```bash
curl -X POST \
"https://api.apify.com/v2/acts/YOUR_USER~tripadvisor-property-rank-tracker/runs?token=YOUR_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"destinationUrls": ["https://www.tripadvisor.com/Hotels-g60763-New_York_City_New_York-Hotels.html"],
"maxPerDestination": 25,
"responseRateSampleSize": 30
}'
```
***
### Pricing
The first few property snapshots per run are free so you can validate output before paying. After that, one charge per property row pushed. Rating histogram, response rate sampling, amenity extraction, and badge detection are all included at no extra cost.
***
### FAQ
#### What does this actor return that the TripAdvisor Review Intelligence actor does not?
This one operates at the property level, not the review level. One row per property per run with rank, rating histogram, badges, claim status, response rate, and amenities. The review actor explains why a property is rated the way it is. This actor tracks what is actually happening to rank and rating over time.
#### How does the rank field work?
For every TripAdvisor property page, the actor parses the rendered rank text such as "#3 of 1,234 hotels in Paris" and ships it as `rank.position`, `rank.totalInCategory`, and a derived `rank.percentile`. Schedule the actor daily and you have a rank time series in your dataset.
#### Can I run this on a schedule?
Yes. Use the Apify scheduler for hourly, daily, or weekly runs. Combine destination URLs with `maxPerDestination` for a recurring competitor sweep, or pass a fixed list of property URLs for a watchlist. Each run pushes a fresh snapshot row per property.
#### Does it work for restaurants and attractions, not just hotels?
Yes. Pass any TripAdvisor property URL. Hotel\_Review, Restaurant\_Review, and Attraction\_Review pages are all supported. Restaurant snapshots also pull cuisine tags. Attraction snapshots pull category tags.
#### How accurate is the response rate field?
The actor samples the most recent N reviews on the property page (default 30) and counts how many have an owner response. If you set `responseRateSampleSize: 0` the field is skipped. Bigger samples mean better accuracy at the cost of a small extra second per property.
#### Is scraping TripAdvisor allowed?
This actor reads HTML any anonymous web visitor can see. Respect TripAdvisor's terms and rate limit sensibly. Do not redistribute review text or property data you do not have a lawful basis to publish.
#### Does it work on regional TripAdvisor domains?
Yes. Pass tripadvisor.co.uk, tripadvisor.fr, tripadvisor.de, or any other locale. The parser is locale aware on the rank phrase and rating histogram.
#### How fresh is the data?
Each run hits the live property page, so rank, rating, review count, and response rate are current at scrape time.
#### Can I export to CSV or push to a database?
Yes. Apify datasets export to JSON, CSV, Excel, RSS, and HTML. The Apify API also lets you pipe each new dataset item to a webhook for streaming into a warehouse.
***
### Related actors
- **TripAdvisor Review Intelligence** — every review with rating, text, traveler origin, stay date, and owner response
- **Booking Review Intelligence** — same idea for Booking.com properties
- **Google Maps Scraper** — local business data, ratings, and reviews
- **Google Reviews Intelligence** — Google review export for hotels and restaurants
- **Yelp Review Intelligence** — Yelp review export for restaurants
# Actor input Schema
## `targetUrls` (type: `array`):
TripAdvisor property URLs. Hotel\_Review, Restaurant\_Review, or Attraction\_Review pages. Each is snapshotted as one dataset row. Example: 'https://www.tripadvisor.com/Hotel\_Review-g60763-d93589-Reviews-The\_Pierre\_A\_Taj\_Hotel.html'.
## `destinationUrls` (type: `array`):
TripAdvisor destination listing URLs to sweep top N properties from. Hotels-, Restaurants-, or Attractions- pages. Example: 'https://www.tripadvisor.com/Hotels-g60763-New\_York\_City\_New\_York-Hotels.html'.
## `maxPerDestination` (type: `integer`):
When destination listing URLs are provided, snapshot at most this many top ranked properties per destination. Useful for daily competitor sweeps.
## `responseRateSampleSize` (type: `integer`):
Number of recent reviews to sample on each property to compute owner response rate. Bigger samples are more accurate but cost more time. Set to 0 to skip response rate.
## `extractAmenities` (type: `boolean`):
Pull the amenity and feature flags TripAdvisor lists on the property page. Adds 200 to 400 ms per property. Built in. No extra cost.
## `extractRatingHistogram` (type: `boolean`):
Capture the count of reviews at each star tier (5, 4, 3, 2, 1). Built in. No extra cost.
## `concurrency` (type: `integer`):
Number of properties processed in parallel. TripAdvisor sits behind Cloudflare, so two to four is the safe range with residential proxy.
## `proxyConfiguration` (type: `object`):
Apify proxy. Residential is required for TripAdvisor at any meaningful volume.
## Actor input object example
```json
{
"targetUrls": [
"https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Pierre_A_Taj_Hotel.html"
],
"destinationUrls": [],
"maxPerDestination": 25,
"responseRateSampleSize": 30,
"extractAmenities": true,
"extractRatingHistogram": true,
"concurrency": 3,
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
}
```
# 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"targetUrls": [
"https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Pierre_A_Taj_Hotel.html"
],
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
};
// Run the Actor and wait for it to finish
const run = await client.actor("scrapemint/tripadvisor-property-rank-tracker").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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"targetUrls": ["https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Pierre_A_Taj_Hotel.html"],
"proxyConfiguration": {
"useApifyProxy": True,
"apifyProxyGroups": ["RESIDENTIAL"],
},
}
# Run the Actor and wait for it to finish
run = client.actor("scrapemint/tripadvisor-property-rank-tracker").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"targetUrls": [
"https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Pierre_A_Taj_Hotel.html"
],
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
}' |
apify call scrapemint/tripadvisor-property-rank-tracker --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=scrapemint/tripadvisor-property-rank-tracker",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "TripAdvisor Property Rank & Competitor Benchmark Tracker",
"description": "For hotel operators, restaurant owners, and travel agencies. Tracks daily rank, rating drift, review volume, owner response rate, Travelers' Choice status, claim status, price tier, and amenities for any TripAdvisor hotel, restaurant, or attraction. One row per property. Pay per snapshot.",
"version": "0.1",
"x-build-id": "RQsh6xMqmIkUVDAw7"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/scrapemint~tripadvisor-property-rank-tracker/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-scrapemint-tripadvisor-property-rank-tracker",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/scrapemint~tripadvisor-property-rank-tracker/runs": {
"post": {
"operationId": "runs-sync-scrapemint-tripadvisor-property-rank-tracker",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/scrapemint~tripadvisor-property-rank-tracker/run-sync": {
"post": {
"operationId": "run-sync-scrapemint-tripadvisor-property-rank-tracker",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"properties": {
"targetUrls": {
"title": "Property URLs",
"type": "array",
"description": "TripAdvisor property URLs. Hotel_Review, Restaurant_Review, or Attraction_Review pages. Each is snapshotted as one dataset row. Example: 'https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Pierre_A_Taj_Hotel.html'.",
"default": [],
"items": {
"type": "string"
}
},
"destinationUrls": {
"title": "Destination listing URLs",
"type": "array",
"description": "TripAdvisor destination listing URLs to sweep top N properties from. Hotels-, Restaurants-, or Attractions- pages. Example: 'https://www.tripadvisor.com/Hotels-g60763-New_York_City_New_York-Hotels.html'.",
"default": [],
"items": {
"type": "string"
}
},
"maxPerDestination": {
"title": "Max properties per destination URL",
"minimum": 1,
"maximum": 200,
"type": "integer",
"description": "When destination listing URLs are provided, snapshot at most this many top ranked properties per destination. Useful for daily competitor sweeps.",
"default": 25
},
"responseRateSampleSize": {
"title": "Response rate sample size",
"minimum": 0,
"maximum": 200,
"type": "integer",
"description": "Number of recent reviews to sample on each property to compute owner response rate. Bigger samples are more accurate but cost more time. Set to 0 to skip response rate.",
"default": 30
},
"extractAmenities": {
"title": "Extract amenities and features",
"type": "boolean",
"description": "Pull the amenity and feature flags TripAdvisor lists on the property page. Adds 200 to 400 ms per property. Built in. No extra cost.",
"default": true
},
"extractRatingHistogram": {
"title": "Extract rating histogram",
"type": "boolean",
"description": "Capture the count of reviews at each star tier (5, 4, 3, 2, 1). Built in. No extra cost.",
"default": true
},
"concurrency": {
"title": "Concurrency",
"minimum": 1,
"maximum": 12,
"type": "integer",
"description": "Number of properties processed in parallel. TripAdvisor sits behind Cloudflare, so two to four is the safe range with residential proxy.",
"default": 3
},
"proxyConfiguration": {
"title": "Proxy configuration",
"type": "object",
"description": "Apify proxy. Residential is required for TripAdvisor at any meaningful volume.",
"default": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```