A single review source can be biased or have limited coverage. Aggregating reviews from Amazon (verified purchasers) and Google (editorial and user reviews from across the web) gives a more representative picture of product reception. This tutorial builds a review aggregation pipeline using the Scavio API that collects reviews from multiple sources, normalizes star ratings to a 5-point scale, and computes a weighted aggregate score.
Prerequisites
- Python 3.8 or higher
- requests library installed
- A Scavio API key
- Basic statistics understanding
Walkthrough
Step 1: Fetch Amazon reviews
Query the Scavio Amazon endpoint for a product and extract its reviews array and average rating.
Python
def amazon_reviews(asin: str) -> dict:
r = requests.post(ENDPOINT, headers={"x-api-key": API_KEY},
json={"platform": "amazon", "query": asin, "marketplace": "US"})
r.raise_for_status()
data = r.json()
return {"rating": data.get("product", {}).get("rating"), "reviews": data.get("reviews", [])}Step 2: Fetch Google review signals
Search Google for product reviews and extract snippets that contain rating mentions.
Python
def google_review_signals(product_name: str) -> list[str]:
r = requests.post(ENDPOINT, headers={"x-api-key": API_KEY},
json={"query": f"{product_name} review rating", "country_code": "us"})
r.raise_for_status()
results = r.json().get("organic_results", [])
return [r.get("snippet", "") for r in results if r.get("snippet")]Step 3: Compute aggregate rating
Average the star ratings from Amazon reviews to produce a weighted score.
Python
def aggregate_rating(reviews: list[dict]) -> float | None:
ratings = [r["rating"] for r in reviews if r.get("rating")]
if not ratings:
return None
return round(sum(ratings) / len(ratings), 2)Step 4: Build the aggregate report
Combine Amazon rating and review count with Google review signals into a unified product report.
Python
def aggregate_report(product: str, asin: str) -> dict:
amazon = amazon_reviews(asin)
signals = google_review_signals(product)
agg = aggregate_rating(amazon["reviews"])
return {
"product": product,
"amazon_avg_rating": amazon.get("rating"),
"review_count": len(amazon["reviews"]),
"aggregate_score": agg,
"google_signals": signals[:3],
}Python Example
Python
import os
import requests
API_KEY = os.environ.get("SCAVIO_API_KEY", "your_scavio_api_key")
ENDPOINT = "https://api.scavio.dev/api/v1/search"
def call(body):
r = requests.post(ENDPOINT, headers={"x-api-key": API_KEY}, json=body)
r.raise_for_status()
return r.json()
def aggregate(product: str, asin: str) -> dict:
amazon_data = call({"platform": "amazon", "query": asin, "marketplace": "US"})
google_data = call({"query": f"{product} review", "country_code": "us"})
reviews = amazon_data.get("reviews", [])
ratings = [r["rating"] for r in reviews if r.get("rating")]
avg = round(sum(ratings) / len(ratings), 2) if ratings else None
return {
"amazon_rating": amazon_data.get("product", {}).get("rating"),
"computed_avg": avg,
"review_count": len(reviews),
"google_snippets": [r.get("snippet") for r in google_data.get("organic_results", [])[:3] if r.get("snippet")]
}
if __name__ == "__main__":
import json
print(json.dumps(aggregate("Sony WH-1000XM5", "B09XS7JWHH"), indent=2))JavaScript Example
JavaScript
const API_KEY = process.env.SCAVIO_API_KEY || "your_scavio_api_key";
const ENDPOINT = "https://api.scavio.dev/api/v1/search";
async function call(body) {
const res = await fetch(ENDPOINT, {
method: "POST",
headers: { "x-api-key": API_KEY, "Content-Type": "application/json" },
body: JSON.stringify(body)
});
return res.json();
}
async function aggregate(product, asin) {
const [amazon, google] = await Promise.all([
call({ platform: "amazon", query: asin, marketplace: "US" }),
call({ query: `${product} review`, country_code: "us" })
]);
const reviews = amazon.reviews || [];
const ratings = reviews.map(r => r.rating).filter(Boolean);
const avg = ratings.length ? Math.round(ratings.reduce((a, b) => a + b) / ratings.length * 100) / 100 : null;
return { amazonRating: amazon.product?.rating, computedAvg: avg, reviewCount: reviews.length };
}
aggregate("Sony WH-1000XM5", "B09XS7JWHH").then(console.log).catch(console.error);Expected Output
JSON
{
"product": "Sony WH-1000XM5",
"amazon_avg_rating": "4.8",
"review_count": 47,
"aggregate_score": 4.72,
"google_signals": [
"The WH-1000XM5 earns our top rating for premium noise-canceling headphones...",
"5/5 stars. Sony has once again set the bar for consumer audio..."
]
}