El monitoreo de comercio electrónico multiplataforma rastrea sus productos (o los de la competencia) en Amazon, Google Shopping y los resultados de búsqueda orgánicos simultáneamente. Esto es esencial para el cumplimiento de la paridad de precios, la detección de infracciones del MAP y la inteligencia competitiva. En lugar de crear raspadores separados por mercado, la API de Scavio maneja Amazon y Google Shopping a través de un punto final. Este tutorial crea un canal de monitoreo que verifica productos en todas las plataformas, detecta discrepancias de precios y genera alertas. Cada cheque de plataforma cuesta $0,005.
Requisitos previos
- Python 3.9+ instalado
- solicita biblioteca instalada
- Una clave API de Scavio de scavio.dev
- Nombres de productos o ASIN a monitorear
Guia paso a paso
Paso 1: Definir la lista de seguimiento de productos
Cree una lista estructurada de productos para monitorear con identificadores para cada plataforma. Incluya su MAP (precio mínimo anunciado) si corresponde.
Python
products = [
{
'name': 'Sony WH-1000XM5 Headphones',
'search_query': 'Sony WH-1000XM5',
'map_price': 299.99, # minimum advertised price
'brand': 'Sony'
},
{
'name': 'Apple AirPods Pro 2',
'search_query': 'Apple AirPods Pro 2nd generation',
'map_price': 249.00,
'brand': 'Apple'
},
{
'name': 'Bose QuietComfort Ultra',
'search_query': 'Bose QuietComfort Ultra headphones',
'map_price': 429.00,
'brand': 'Bose'
}
]
print(f'Monitoring {len(products)} products across 2 platforms')
print(f'Cost per full check: ${len(products) * 2 * 0.005:.2f}')Paso 2: Busca en Amazon y Google Shopping cada producto
Consulta ambas plataformas para cada producto y normaliza los resultados en un formato común con precio, vendedor, calificación y disponibilidad.
Python
import requests, os, re
API_KEY = os.environ['SCAVIO_API_KEY']
ENDPOINT = 'https://api.scavio.dev/api/v1/search'
def parse_price(p) -> float:
if not p: return 0.0
try: return float(re.sub(r'[^0-9.]', '', str(p)))
except: return 0.0
def check_amazon(query: str) -> list:
resp = requests.post(ENDPOINT,
headers={'x-api-key': API_KEY, 'Content-Type': 'application/json'},
json={'platform': 'amazon', 'query': query, 'marketplace': 'US'})
return [{'platform': 'amazon', 'title': p.get('title', ''),
'price': parse_price(p.get('price')), 'rating': p.get('rating', 0),
'reviews': p.get('reviews_count', 0), 'link': p.get('link', '')}
for p in resp.json().get('products', []) if parse_price(p.get('price')) > 0]
def check_google_shopping(query: str) -> list:
resp = requests.post(ENDPOINT,
headers={'x-api-key': API_KEY, 'Content-Type': 'application/json'},
json={'query': query, 'country_code': 'us', 'type': 'shopping'})
return [{'platform': 'google_shopping', 'title': p.get('title', ''),
'price': parse_price(p.get('price')), 'seller': p.get('source', ''),
'link': p.get('link', '')}
for p in resp.json().get('shopping_results', []) if parse_price(p.get('price')) > 0]Paso 3: Detectar infracciones del MAP y anomalías de precios
Compare los precios con el precio mínimo anunciado. Marque cualquier anuncio que se venda por debajo del MAP o que muestre un patrón de precios sospechoso.
Python
def check_map_violations(listings: list, map_price: float) -> list:
violations = []
for listing in listings:
if listing['price'] < map_price:
discount_pct = ((map_price - listing['price']) / map_price) * 100
violations.append({
'platform': listing['platform'],
'title': listing['title'][:60],
'price': listing['price'],
'map_price': map_price,
'discount': round(discount_pct, 1),
'link': listing['link']
})
return violations
def find_price_range(listings: list) -> dict:
prices = [l['price'] for l in listings if l['price'] > 0]
if not prices:
return {'min': 0, 'max': 0, 'spread': 0}
return {
'min': min(prices),
'max': max(prices),
'spread': round(max(prices) - min(prices), 2),
'avg': round(sum(prices) / len(prices), 2)
}Paso 4: Generar el informe multiplataforma
Combine datos de todas las plataformas en un informe unificado sobre el estado del producto con comparación de precios y alertas de infracción de MAP.
Python
import time
from datetime import date
def monitor_product(product: dict) -> dict:
query = product['search_query']
amazon = check_amazon(query)
google = check_google_shopping(query)
all_listings = amazon + google
violations = check_map_violations(all_listings, product['map_price'])
price_range = find_price_range(all_listings)
return {
'product': product['name'],
'map_price': product['map_price'],
'amazon_listings': len(amazon),
'google_listings': len(google),
'total_listings': len(all_listings),
'price_range': price_range,
'map_violations': violations,
'violation_count': len(violations)
}
def full_monitor(products: list) -> list:
reports = []
for product in products:
report = monitor_product(product)
reports.append(report)
status = 'VIOLATION' if report['violation_count'] > 0 else 'OK'
print(f'[{status}] {report["product"]}: '
f'${report["price_range"]["min"]}-${report["price_range"]["max"]} '
f'({report["total_listings"]} listings, {report["violation_count"]} violations)')
time.sleep(0.3)
cost = len(products) * 2 * 0.005
print(f'\nTotal cost: ${cost:.2f} ({len(products) * 2} credits)')
return reports
reports = full_monitor(products)Paso 5: Calendario y alerta sobre infracciones
Ejecute el monitor según una programación y envíe alertas cuando se detecten infracciones de MAP o cambios significativos en los precios.
Python
import json
def save_and_alert(reports: list) -> None:
# Save report
filename = f'ecommerce_monitor_{date.today()}.json'
with open(filename, 'w') as f:
json.dump({'date': date.today().isoformat(), 'reports': reports}, f, indent=2)
# Check for alerts
violations = [r for r in reports if r['violation_count'] > 0]
if violations:
print(f'\nALERT: {len(violations)} products with MAP violations:')
for r in violations:
for v in r['map_violations']:
print(f' {r["product"]} on {v["platform"]}: '
f'${v["price"]} (MAP: ${v["map_price"]}, -{v["discount"]}%)')
else:
print('\nNo MAP violations detected.')
# Schedule: add to crontab
# 0 9,15,21 * * * python ecommerce_monitor.py # 3x daily
# Cost: 3 products x 2 platforms x 3 checks x 30 days = 540 credits/mo = $2.70
save_and_alert(reports)Ejemplo en Python
Python
import os, requests, re, time
API_KEY = os.environ['SCAVIO_API_KEY']
EP = 'https://api.scavio.dev/api/v1/search'
def search(body):
return requests.post(EP, headers={'x-api-key': API_KEY, 'Content-Type': 'application/json'}, json=body).json()
def parse_price(p):
try: return float(re.sub(r'[^0-9.]', '', str(p or '0')))
except: return 0.0
def monitor(name, query, map_price):
amazon = search({'platform': 'amazon', 'query': query, 'marketplace': 'US'})
google = search({'query': query, 'country_code': 'us', 'type': 'shopping'})
prices = [parse_price(p.get('price')) for p in amazon.get('products', [])]
prices += [parse_price(p.get('price')) for p in google.get('shopping_results', [])]
prices = [p for p in prices if p > 0]
violations = sum(1 for p in prices if p < map_price)
print(f'{name}: ${min(prices):.2f}-${max(prices):.2f} ({violations} MAP violations)')
monitor('Sony WH-1000XM5', 'Sony WH-1000XM5', 299.99)Ejemplo en JavaScript
JavaScript
const API_KEY = process.env.SCAVIO_API_KEY;
const EP = 'https://api.scavio.dev/api/v1/search';
async function search(body) {
const r = await fetch(EP, {
method: 'POST',
headers: { 'x-api-key': API_KEY, 'Content-Type': 'application/json' },
body: JSON.stringify(body)
});
return r.json();
}
async function monitor(name, query, mapPrice) {
const [amazon, google] = await Promise.all([
search({ platform: 'amazon', query, marketplace: 'US' }),
search({ query, country_code: 'us', type: 'shopping' })
]);
const prices = [
...(amazon.products || []).map(p => parseFloat(String(p.price || 0).replace(/[^0-9.]/g, ''))),
...(google.shopping_results || []).map(p => parseFloat(String(p.price || 0).replace(/[^0-9.]/g, '')))
].filter(p => p > 0);
const violations = prices.filter(p => p < mapPrice).length;
console.log(`${name}: $${Math.min(...prices)}-$${Math.max(...prices)} (${violations} MAP violations)`);
}
monitor('Sony WH-1000XM5', 'Sony WH-1000XM5', 299.99);Salida esperada
JSON
[OK] Sony WH-1000XM5 Headphones: $289.99-$349.99 (8 listings, 0 violations)
[VIOLATION] Apple AirPods Pro 2: $219.00-$249.00 (6 listings, 2 violations)
[OK] Bose QuietComfort Ultra: $429.00-$449.99 (5 listings, 0 violations)
Total cost: $0.03 (6 credits)
ALERT: 1 products with MAP violations:
Apple AirPods Pro 2 on google_shopping: $219.00 (MAP: $249.00, -12.0%)
Apple AirPods Pro 2 on amazon: $229.99 (MAP: $249.00, -7.6%)