# TripAdvisor Review Intelligence and Hotel Reputation Monitor (`scrapemint/tripadvisor-review-intelligence`) Actor
For hotel operators, restaurant owners, and travel agencies. Pulls every TripAdvisor review for any hotel, attraction, or restaurant with rating, text, trip type, traveler origin, stay date, and owner responses. Track property sentiment and benchmark competitors without a reputation subscription.
- **URL**: https://apify.com/scrapemint/tripadvisor-review-intelligence.md
- **Developed by:** [Kennedy Mutisya](https://apify.com/scrapemint) (community)
- **Categories:** Travel, E-commerce
- **Stats:** 2 total users, 1 monthly users, 0.0% 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 Review Data and Hotel Reputation Monitoring Tool
Export every TripAdvisor review for any hotel, restaurant, or attraction into a clean spreadsheet or JSON file. Get star ratings, full review text, trip type, traveler origin, stay dates, owner responses, and aggregate property ratings for your property and every competing destination.
Built for hotel operators, restaurant owners, travel agencies, and STR managers who need TripAdvisor review data without paying for a hospitality reputation subscription.
---
### Who uses this and why
```mermaid
flowchart TD
A[Hotel Operators] -->|Catch sentiment dips
before revenue drops| D[TripAdvisor
Review Data]
B[Restaurant Owners] -->|See what rivals are
praised and hated for| D
C[Travel Agencies] -->|Pre vet properties
before packaging trips| D
R[STR Managers] -->|Benchmark listings
across every city| D
D --> E[Weekly sentiment report]
D --> F[Competitor gap analysis]
D --> G[Guest complaint triage]
````
| Role | What this gives you |
|---|---|
| **Hotel operator** | Weekly review volume, star trends, stay date ranges, owner reply coverage |
| **Restaurant owner** | Side by side sentiment vs direct local competitors |
| **Travel agency** | Pre trip due diligence on every property in a package |
| **STR manager** | Benchmark your listing against every vacation rental in the area |
| **BI analyst** | Clean JSON or CSV ready for dashboards and sentiment models |
***
### How it works
```mermaid
flowchart LR
A[TripAdvisor
location URL] --> B[Load review pages]
B --> C[Parse schema.org
metadata]
C --> D[Expand truncated
review bodies]
D --> E[Walk review cards
across pagination]
E --> F[Normalize fields]
F --> G[(JSON, CSV, or Excel)]
```
The actor visits each TripAdvisor location page, reads the schema.org metadata TripAdvisor ships for aggregate ratings, expands every truncated review body, and walks through all reviews 10 at a time. Residential proxies keep you past the Cloudflare gate. Same data TripAdvisor shows in its own UI, delivered as a clean dataset.
***
### What one review record looks like
```json
{
"reviewId": "987654321",
"locationName": "The Pierre, A Taj Hotel, New York",
"locationType": "LodgingBusiness",
"locationAggregateRating": 4.5,
"locationReviewCount": 2168,
"locationCity": "New York City",
"locationCountry": "US",
"rating": 5,
"title": "Flawless anniversary stay",
"text": "Stayed in a corner suite overlooking Central Park for our 10 year anniversary. Doorman remembered my name by the second day. Bar downstairs is worth the price of the room alone...",
"reviewerName": "MarissaK",
"reviewerLocation": "Chicago, Illinois",
"writtenDate": "Written April 8, 2026",
"stayDate": "Date of stay: March 2026",
"tripType": "Traveled as a couple",
"language": "en",
"helpfulVotes": 4,
"hasOwnerResponse": true,
"ownerResponseText": "Dear Marissa, thank you for choosing The Pierre for such a special occasion...",
"ownerResponseDate": "Responded April 10, 2026"
}
```
Every review comes back with: star rating (1 to 5), title, full text, reviewer name and home location, written date, stay date, trip type (family, couple, business, solo, friends), helpful vote count, and the full owner response with its own timestamp. Plus the property name, type (hotel, restaurant, attraction), aggregate rating, city, and country on every record so you can group in any spreadsheet.
***
### Quick start
Export 200 recent reviews for a single hotel:
```bash
curl -X POST "https://api.apify.com/v2/acts/scrapemint~tripadvisor-review-intelligence/run-sync-get-dataset-items?token=YOUR_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"locationUrl": "https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Pierre.html",
"maxReviews": 200,
"sortBy": "NEWEST_FIRST"
}'
```
Compare your hotel against 2 competitors in one run, filtering for complaints only:
```json
{
"locationUrls": [
{ "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Pierre.html" },
{ "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d93361-Reviews-The_Plaza.html" },
{ "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d93541-Reviews-The_Carlyle.html" }
],
"maxReviews": 500,
"filterByRating": ["1", "2"]
}
```
***
### Inputs
| Field | Type | Default | What it does |
|---|---|---|---|
| `locationUrls` | array | `[]` | TripAdvisor review URLs. Hotels, attractions, or restaurants. Add several to compare in one run. |
| `locationUrl` | string | `null` | Single URL shortcut. Used when `locationUrls` is empty. |
| `maxReviews` | integer | `500` | Hard cap per location. Controls cost. |
| `sortBy` | string | `NEWEST_FIRST` | `NEWEST_FIRST` or `MOST_HELPFUL` |
| `filterByRating` | array | `[]` | Ratings to keep (e.g. `["1","2"]` for complaint analysis). Empty = all. |
| `language` | string | `""` | Filter by language code (`en`, `es`, `fr`, `de`, `it`). Empty = all. |
***
### Pricing
Pay per review. Free tier lets you check the data before spending anything.
| Tier | Price | Best for |
|---|---|---|
| Free | First 100 reviews per run | Verifying the output format |
| Standard | $0.006 per review | Ongoing monitoring and competitor benchmarking |
```mermaid
flowchart LR
A[Run the actor] --> B{First 100
reviews}
B -->|Free| C[Verify output]
C --> D{Need more?}
D -->|Yes| E[$0.006 per review
after the first 100]
D -->|No| F[Done, $0 spent]
```
***
### How this beats the alternatives
| Method | Cost for 5,000 reviews across 5 hotels | Data depth | Time |
|---|---|---|---|
| Read TripAdvisor manually | 20 to 30 analyst hours | Spreadsheet notes | Days |
| Hospitality reputation SaaS | $400 to $1,200 per month per property | Aggregated dashboards | Subscription locked |
| **This actor** | **$29.40 once** | Full reviews, traveler data, responses, timestamps | Minutes |
***
### Compare destinations in one run
```mermaid
flowchart LR
A[Your property URL] --> X[Actor]
B[Competitor 1 URL] --> X
C[Competitor 2 URL] --> X
X --> D[(Unified review
dataset)]
D --> E[Sort by locationName
in spreadsheet]
E --> F[Head to head
sentiment report]
```
Every record carries the `locationName`, `locationCity`, and `locationAggregateRating` fields, so you can group results in any spreadsheet or BI tool in seconds.
***
### Use case flows
```mermaid
flowchart TD
subgraph Inputs
A[Location URLs]
end
subgraph Actor
B[Pull reviews]
end
subgraph Outputs
C[JSON / CSV / Excel]
end
subgraph Workflows
D[Weekly GM report]
E[Competitor gap analysis]
F[Front desk complaint triage]
G[Marketing copy mining]
end
A --> B --> C
C --> D
C --> E
C --> F
C --> G
```
- **Weekly GM report:** cron this actor, diff the latest run, email the GM when 1 or 2 star volume spikes
- **Competitor gap analysis:** pull your property plus 3 rivals, sort by stars, show ownership what guests praise next door
- **Front desk complaint triage:** feed 1 and 2 star reviews into your PMS so CS sees complaints before they escalate
- **Marketing copy mining:** grep 5 star reviews for the exact phrases guests use, reuse them in booking page copy
***
### Related tools in the review intelligence suite
```mermaid
flowchart LR
A[Booking Review
Intelligence] --> C[(Unified review
dataset)]
B[Trustpilot Brand
Reputation] --> C
T[TripAdvisor Review
Intelligence] --> C
C --> D[Cross platform
reputation report]
```
- [**Booking Review Intelligence**](https://apify.com/scrapemint/booking-review-intelligence): hotel and STR reviews with sentiment, category scores, traveler type, and management replies
- [**Trustpilot Brand Reputation**](https://apify.com/scrapemint/trustpilot-brand-reputation): e-commerce and service business reviews with trust scores, consumer country, and verification status
- **More review sources on the roadmap:** Google Reviews, Yelp, OpenTable
***
### Frequently asked questions
**How do I download TripAdvisor reviews to a CSV file?**
Run this actor with a TripAdvisor location URL and your chosen cap. Export the dataset as CSV from the Apify console or pull it via the API. Works for any hotel, restaurant, or attraction with a public TripAdvisor page.
**How do I monitor my property reputation on TripAdvisor without paying for a SaaS subscription?**
Schedule this actor weekly against your TripAdvisor URL. Export the latest reviews and compare against last week in your own spreadsheet. A few dollars per run replaces a $400+ monthly hospitality reputation subscription.
**Can I compare multiple hotels on TripAdvisor in one run?**
Yes. Pass every URL in the `locationUrls` array. Every review record includes `locationName`, `locationCity`, and `locationAggregateRating`, so you can group and compare in any tool.
**How do I analyze only negative TripAdvisor reviews?**
Set `filterByRating` to `["1", "2"]` to pull just 1 and 2 star reviews. Most complaint analysis workflows use this filter.
**What data does this return for each TripAdvisor review?**
Rating (1 to 5), title, full review text, reviewer name, reviewer home location, written date, stay date, trip type, helpful votes, language, and the full owner response with its timestamp. Plus property name, type, aggregate rating, city, and country on every record.
**Does this work for restaurants and attractions too?**
Yes. Any TripAdvisor URL with `Hotel_Review`, `Restaurant_Review`, or `Attraction_Review` in the path works.
**Does this work across international TripAdvisor domains?**
Yes. Works for tripadvisor.com, tripadvisor.co.uk, tripadvisor.de, tripadvisor.fr, and other locales. Just paste the location URL.
**How many reviews can I pull from one location?**
Up to the full review history. Use `maxReviews` to set a cap. Properties with thousands of reviews take several minutes to finish.
**How fresh is the data?**
Live at query time. Every run pulls straight from TripAdvisor. No cached snapshots.
**What format is the output?**
JSON, CSV, or Excel. Download from the Apify dataset or pull via API.
**Why does this need residential proxies?**
TripAdvisor fronts every page with Cloudflare. Datacenter proxies get blocked within a few requests. Residential proxies keep runs clean. The actor ships with residential proxy defaults.
# Actor input Schema
## `locationUrls` (type: `array`):
One or more TripAdvisor hotel, attraction, or restaurant review URLs. Example: https://www.tripadvisor.com/Hotel\_Review-g60763-d93589-Reviews-The\_Pierre\_A\_Taj\_Hotel-New\_York.html
## `locationUrl` (type: `string`):
Single TripAdvisor URL. Used only if locationUrls is empty.
## `maxReviews` (type: `integer`):
Hard cap per location. Prevents runaway charges on properties with thousands of reviews.
## `sortBy` (type: `string`):
Review sort order.
## `filterByRating` (type: `array`):
Only return reviews with these star ratings. Valid values: 1, 2, 3, 4, 5. Leave empty for all ratings.
## `language` (type: `string`):
Only return reviews in this language. Leave empty for all languages. Example: en, es, fr, de, it
## `proxyConfiguration` (type: `object`):
Apify proxy settings. Residential proxies recommended for TripAdvisor.
## Actor input object example
```json
{
"locationUrls": [
{
"url": "https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Pierre_A_Taj_Hotel_New_York-New_York_City_New_York.html"
}
],
"maxReviews": 500,
"sortBy": "NEWEST_FIRST",
"filterByRating": [],
"language": "",
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
],
"apifyProxyCountry": "US"
}
}
```
# 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 = {
"locationUrls": [
{
"url": "https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Pierre_A_Taj_Hotel_New_York-New_York_City_New_York.html"
}
],
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
],
"apifyProxyCountry": "US"
}
};
// Run the Actor and wait for it to finish
const run = await client.actor("scrapemint/tripadvisor-review-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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"locationUrls": [{ "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Pierre_A_Taj_Hotel_New_York-New_York_City_New_York.html" }],
"proxyConfiguration": {
"useApifyProxy": True,
"apifyProxyGroups": ["RESIDENTIAL"],
"apifyProxyCountry": "US",
},
}
# Run the Actor and wait for it to finish
run = client.actor("scrapemint/tripadvisor-review-intelligence").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 '{
"locationUrls": [
{
"url": "https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Pierre_A_Taj_Hotel_New_York-New_York_City_New_York.html"
}
],
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
],
"apifyProxyCountry": "US"
}
}' |
apify call scrapemint/tripadvisor-review-intelligence --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=scrapemint/tripadvisor-review-intelligence",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "TripAdvisor Review Intelligence and Hotel Reputation Monitor",
"description": "For hotel operators, restaurant owners, and travel agencies. Pulls every TripAdvisor review for any hotel, attraction, or restaurant with rating, text, trip type, traveler origin, stay date, and owner responses. Track property sentiment and benchmark competitors without a reputation subscription.",
"version": "0.1",
"x-build-id": "6JuqFIuhjDNLH5fyv"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/scrapemint~tripadvisor-review-intelligence/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-scrapemint-tripadvisor-review-intelligence",
"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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/scrapemint~tripadvisor-review-intelligence/runs": {
"post": {
"operationId": "runs-sync-scrapemint-tripadvisor-review-intelligence",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/scrapemint~tripadvisor-review-intelligence/run-sync": {
"post": {
"operationId": "run-sync-scrapemint-tripadvisor-review-intelligence",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"locationUrls": {
"title": "TripAdvisor location URLs",
"type": "array",
"description": "One or more TripAdvisor hotel, attraction, or restaurant review URLs. Example: https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Pierre_A_Taj_Hotel-New_York.html",
"items": {
"type": "object",
"required": [
"url"
],
"properties": {
"url": {
"type": "string",
"title": "URL of a web page",
"format": "uri"
}
}
}
},
"locationUrl": {
"title": "Single location URL (alternative)",
"type": "string",
"description": "Single TripAdvisor URL. Used only if locationUrls is empty."
},
"maxReviews": {
"title": "Maximum reviews per location",
"minimum": 1,
"maximum": 10000,
"type": "integer",
"description": "Hard cap per location. Prevents runaway charges on properties with thousands of reviews.",
"default": 500
},
"sortBy": {
"title": "Sort reviews by",
"enum": [
"NEWEST_FIRST",
"MOST_HELPFUL"
],
"type": "string",
"description": "Review sort order.",
"default": "NEWEST_FIRST"
},
"filterByRating": {
"title": "Filter by rating",
"type": "array",
"description": "Only return reviews with these star ratings. Valid values: 1, 2, 3, 4, 5. Leave empty for all ratings.",
"default": [],
"items": {
"type": "string"
}
},
"language": {
"title": "Language filter",
"type": "string",
"description": "Only return reviews in this language. Leave empty for all languages. Example: en, es, fr, de, it",
"default": ""
},
"proxyConfiguration": {
"title": "Proxy configuration",
"type": "object",
"description": "Apify proxy settings. Residential proxies recommended for TripAdvisor."
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```