Automatice la recopilación y el análisis de reseñas de marketing con n8n

import requests

PLATFORMS = ["google", "reddit", "youtube"]

def collect_brand_mentions(brand: str) -> dict:
    all_mentions = {}
    for platform in PLATFORMS:
        resp = requests.post(
            "https://api.scavio.dev/api/v1/search",
            headers={"x-api-key": SCAVIO_API_KEY, "Content-Type": "application/json"},
            json={
                "query": f"{brand} review feedback 2026",
                "platform": platform,
                "limit": 10
            }
        )
        results = resp.json().get("results", [])
        mentions = []
        for r in results:
            snippet = r.get("snippet", "")
            sentiment = "positive" if any(w in snippet.lower() for w in ["great", "love", "best", "recommend"]) else "neutral"
            if any(w in snippet.lower() for w in ["bad", "worst", "avoid", "terrible"]):
                sentiment = "negative"
            mentions.append({
                "title": r["title"],
                "url": r["link"],
                "snippet": snippet,
                "sentiment": sentiment
            })
        all_mentions[platform] = mentions
    return all_mentions

report = collect_brand_mentions("Scavio")
for platform, mentions in report.items():
    print(f"\n{platform.upper()} ({len(mentions)} mentions):")
    for m in mentions:
        print(f"  [{m['sentiment']}] {m['title']}")

const H = {'x-api-key': process.env.SCAVIO_API_KEY, 'Content-Type': 'application/json'};
fetch('https://api.scavio.dev/api/v1/search', {method: 'POST', headers: H, body: JSON.stringify({query: 'example', country_code: 'us'})}).then(r => r.json()).then(d => console.log(d.organic_results?.length + ' results'));