Resumen
Nuevo leads enter your CRM diario con solo un nombre y correo electronico. Este flujo de trabajo enriquece cada nuevo lead automaticamente by busqueda Google for company informacion y Reddit for sentiment y employee discussions. It replaces multi-vendor enriquecimiento stacks (Clearbit, Phantombuster, Google Personalizado Search) con un single Scavio MCP herramienta ese el agent calls dynamically basado on que datos es missing.
Desencadenador
Cron programar (diario at 10 AM UTC) o CRM webhook on nuevo lead
Programación
Diario at 10 AM UTC
Pasos del flujo de trabajo
Obtener unenriched leads
Consulta your CRM for leads added in el last 24 horas ese lack company datos (industria, tamano, tech stack).
Search Google for company info
For cada lead's company, consulta Scavio Google search for firmographics, reciente news, y tech stack senales.
Search Reddit for sentiment
Consulta Reddit for el company nombre to encontrar employee resenas, producto discussions, y puntos de dolor.
Analizar y structure datos
Extraer industria, approximate tamano, technology menciones, y sentiment de resultados de busqueda.
Actualizar CRM registros
Escribir enriquecimiento datos back to cada lead's CRM registro con fuente URLs for verification.
Marcar high-priority leads
Puntuacion leads by enriquecimiento senales (growing company, active hiring, expressing puntos de dolor) y marcar top prospects.
Implementacion en Python
import requests, os, json
H = {"x-api-key": os.environ["SCAVIO_API_KEY"]}
def enrich_lead(company, domain):
google = requests.post("https://api.scavio.dev/api/v1/search", headers=H,
json={"platform": "google", "query": f"{company} {domain} company info"}, timeout=10).json()
reddit = requests.post("https://api.scavio.dev/api/v1/search", headers=H,
json={"platform": "reddit", "query": f"{company} review"}, timeout=10).json()
web_data = [{"title": o.get("title"), "snippet": o.get("snippet"),
"url": o.get("link")} for o in google.get("organic", [])[:5]]
reddit_data = [{"title": o.get("title"), "url": o.get("link")}
for o in reddit.get("organic", [])[:5]]
# Extract signals from results
all_text = " ".join(o.get("snippet", "") for o in google.get("organic", [])[:5]).lower()
signals = {
"hiring": "hiring" in all_text or "careers" in all_text,
"growing": "series" in all_text or "funding" in all_text or "raised" in all_text,
"has_tech_mentions": any(t in all_text for t in ["api", "saas", "cloud", "aws", "python"])
}
return {
"company": company, "domain": domain,
"web_results": web_data, "reddit_mentions": reddit_data,
"signals": signals, "priority": "high" if signals["growing"] else "standard"
}
leads = [{"company": "Acme Corp", "domain": "acme.com"}]
for lead in leads:
enriched = enrich_lead(lead["company"], lead["domain"])
print(json.dumps(enriched, indent=2))Implementacion en JavaScript
const H = {"x-api-key": process.env.SCAVIO_API_KEY, "Content-Type": "application/json"};
async function enrichLead(company, domain) {
const [google, reddit] = await Promise.all([
fetch("https://api.scavio.dev/api/v1/search", {
method: "POST", headers: H,
body: JSON.stringify({platform: "google", query: company + " " + domain + " company info"})
}).then(r => r.json()),
fetch("https://api.scavio.dev/api/v1/search", {
method: "POST", headers: H,
body: JSON.stringify({platform: "reddit", query: company + " review"})
}).then(r => r.json())
]);
return {
company, domain,
webResults: (google.organic || []).slice(0, 5).map(o => ({title: o.title, snippet: o.snippet, url: o.link})),
redditMentions: (reddit.organic || []).slice(0, 5).map(o => ({title: o.title, url: o.link}))
};
}Plataformas utilizadas
Búsqueda web con grafo de conocimiento, PAA y resúmenes de IA
Comunidad, publicaciones y comentarios en hilos de cualquier subreddit