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Reviews API

Product & App Store Review Sentiment Analysis API

Customer review intelligence API for sentiment score, feature feedback, emotion tagging, and churn risk scoring.

POST https://rsflowhub.com/api/v1/ai/review-analyze
  • 3 credits per call
  • X-API-Key header
  • JSON in, JSON out
POST /api/v1/ai/review-analyze
{
    "review": "The food was absolutely delicious and the service was amazing! However, it was a bit overpriced.",
    "rating": 4,
    "context": "Italian restaurant in downtown New York"
}
200 OK response.json
{
    "result": {
        "sentiment": "mixed",
        "confidence": 0.88,
        "language": "en",
        "category": "product_quality",
        "emotions": [
            "satisfaction",
            "frustration"
        ],
        "key_topics": [
            "delivery",
            "build quality",
            "battery life"
        ],
        "positive_points": [
            "Fast delivery",
            "Great build quality"
        ],
        "negative_points": [
            "Short battery life"
        ],
        "pain_points": [
            "Battery does not last a full day"
        ],
        "suggestions": [
            "Improve battery capacity"
        ],
        "urgency": "medium",
        "attention_recommended": true
    }
}
Definition

What is the Product & App Store Review Sentiment Analysis API?

Product & App Store Review Sentiment Analysis API is a REST API on RSFlowHub for web, mobile and AI agent applications. Send a JSON request to POST /api/v1/ai/review-analyze with your API key; RSFlowHub runs it on a tuned AI model, falls back to a backup provider if needed, and returns a structured JSON result, usually within 1 to 3 seconds.

Category
Reviews
Endpoint
POST /api/v1/ai/review-analyze
Authentication
X-API-Key header
Price
3 credits per call
Rate limit
10 to 120 requests / minute by plan
Typical response
1 to 3 seconds
Format
JSON, UTF-8

Request parameters

Send these fields as a JSON body. An invalid or missing field returns a 422 error that names the field.

FieldTypeRequiredDescription
review string Required The customer review text (Max: 20,000 characters).
rating integer Optional Optional customer numeric rating (between 1 and 5).
language string Optional Optional review language identifier.
context string Optional Optional product, business, or category context.

Code examples

Copy, replace rfh_your_api_key with your key and run. Prefer a client library? See the official SDKs.

request.sh
curl -X POST "https://rsflowhub.com/api/v1/ai/review-analyze" \
  -H "Content-Type: application/json" \
  -H "X-API-Key: rfh_your_api_key" \
  -d '{"review":"The food was absolutely delicious and the service was amazing! However, it was a bit overpriced.","rating":4,"context":"Italian restaurant in downtown New York"}'

Response

Every RSFlowHub endpoint uses the same envelope, so one parser handles all of them. Failed calls are not charged.

response.json
{
    "success": true,
    "request_id": "req_3f9a2c7e-5b1d-4e8a-9c2f-7d6e1a0b4c8d",
    "data": {
        "result": {
            "sentiment": "mixed",
            "confidence": 0.88,
            "language": "en",
            "category": "product_quality",
            "emotions": [
                "satisfaction",
                "frustration"
            ],
            "key_topics": [
                "delivery",
                "build quality",
                "battery life"
            ],
            "positive_points": [
                "Fast delivery",
                "Great build quality"
            ],
            "negative_points": [
                "Short battery life"
            ],
            "pain_points": [
                "Battery does not last a full day"
            ],
            "suggestions": [
                "Improve battery capacity"
            ],
            "urgency": "medium",
            "attention_recommended": true
        }
    },
    "meta": {
        "version": "v1",
        "timestamp": "2026-10-05T09:30:00Z"
    }
}
Envelope fields
FieldTypeMeaning
successbooleantrue when the call worked, false on any error.
request_idstringUnique id for this call. Quote it when you contact support.
data.resultobjectThe result of this endpoint (see the example).
errorobjectOnly on failure: code, message and details per field.
metaobjectAPI version and server timestamp.

All error codes: Errors reference

Features

Feature & Topic Sentiment Breakdown

Categorizes review text into specific features (e.g. pricing, UI, customer support, build quality) with sentiment scores.

Star Rating vs Text Mismatch Detection

Flags reviews where positive text contradicts 1-star ratings or negative text accompanies 5-star ratings.

Emotion & Frustration Intensity

Measures customer emotional intensity, disappointment levels, and churn risk probability.

Cross-Platform E-Commerce Support

Tailored for Amazon, Google Maps, Apple App Store, Google Play Store, G2, and Trustpilot reviews.

Use cases

How teams use the Product & App Store Review Sentiment Analysis API in production.

Mobile App SaaS

App Store & Play Store Review Monitoring

Analyze daily mobile app store reviews to automatically flag software bugs, login crashes, and feature requests.

Input
The food was absolutely delicious and the service was amazing! However, it was a bit overpriced.
Output
{"overall_sentiment": "positive", "rating_match": true, "topics": {"food": "positive", "service": "positive", "price": "negative"}}

Improves app store rating and user retention.

E-Commerce Marketplace

Amazon & E-Commerce Defect Tracking

Detect recurring product defect complaints across thousands of Amazon and Shopify buyer reviews.

Input
Bought this last week. The zipper broke after 2 days. Very disappointed.
Output
{"overall_sentiment": "negative", "category": "product_defect", "aspect": "zipper"}

Identifies manufacturing defects before batch distribution.

Hospitality & Local SEO

Hotel & Local Business Review Analytics

Extract cleanliness, staff behavior, and location sentiment scores from Google Business reviews.

Input
Room was spotless and staff was super friendly! Will definitely visit again.
Output
{"overall_sentiment": "positive", "aspects": {"cleanliness": "positive", "staff": "positive"}}

Provides actionable operational intelligence for hotel managers.

Product & App Store Review Sentiment Analysis API vs building it yourself

The same job done three ways.

TopicRSFlowHub APIRaw LLM promptsRules / regex
Output Validated JSON fieldsFree text you have to parseFixed patterns only
Setup One POST request, no promptsWrite and maintain prompts and parsingWrite and maintain rule lists
Provider outage Automatic fallback to a backup modelYou build retries and a second vendorNot applicable
Pricing 3 credits per call, failed calls freePer token, per vendorYour own servers and upkeep
Understands context Yes, AI modelYes, AI modelNo, keywords only

Frequently asked questions

Which review platforms are supported?
The Review Analysis API natively supports review text from Google Maps/My Business, Amazon, Apple App Store, Google Play Store, Trustpilot, Yelp, and G2.
How does star rating mismatch detection work?
The API compares textual sentiment against the numeric star rating parameter to flag potential user entry errors (e.g., 1 star with glowing praise).
Can I pass product context for better accuracy?
Yes! Passing product context (e.g., "SaaS software", "Hotel") grounds aspect extraction to domain-specific features.
How fast is the Review Analysis API?
Review Analysis requests usually complete in 1 to 3 seconds, depending on input length and the AI model. Identical repeat requests are served from cache and return faster.
How many credits are deducted per request?
Review Analysis API calls consume 3 base credits per request.

Start using the Product & App Store Review Sentiment Analysis API

Free plan with 100 credits/month + 1,000 bonus credits when you sign in before 23 Nov. Test it in the playground first, no code needed.

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