La generación de leads locales a escala requiere encontrar empresas en una categoría objetivo, enriquecerlas con datos de presencia web y calificarlas según su probabilidad de conversión. La investigación manual no va más allá de unas pocas docenas de clientes potenciales. Este tutorial crea un canal automatizado que busca empresas locales utilizando la API de Scavio, enriquece cada cliente potencial con señales de calidad del sitio web y produce una lista de clientes potenciales calificada lista para su divulgación. El proceso completo cuesta alrededor de $0,015 por cliente potencial (3 llamadas API).
Requisitos previos
- Python 3.9+ instalado
- solicita biblioteca instalada
- Una clave API de Scavio de scavio.dev
- Una categoría de negocio objetivo y una lista de ubicaciones
Guia paso a paso
Paso 1: Encuentre empresas locales a través de datos SERP
Busque empresas en su categoría objetivo en varias ubicaciones. Extraiga nombres, calificaciones e información de contacto básica de los resultados locales.
Python
import os, requests, json, time, csv
SCAVIO_KEY = os.environ['SCAVIO_API_KEY']
H = {'x-api-key': SCAVIO_KEY, 'Content-Type': 'application/json'}
URL = 'https://api.scavio.dev/api/v1/search'
def find_businesses(category: str, location: str) -> list:
resp = requests.post(URL, headers=H,
json={'query': f'{category} {location}', 'country_code': 'us', 'num_results': 10})
data = resp.json()
leads = []
for b in data.get('local_results', data.get('local_pack', [])):
leads.append({
'name': b.get('title', b.get('name', '')),
'address': b.get('address', ''),
'phone': b.get('phone', ''),
'rating': b.get('rating', ''),
'reviews': b.get('reviews', 0),
'website': b.get('website', b.get('link', '')),
'category': category,
'location': location,
})
return leads
leads = find_businesses('dental offices', 'Denver CO')
print(f'Found {len(leads)} dental offices in Denver')Paso 2: Enriquezca los clientes potenciales con señales de presencia web
Para cada empresa con un sitio web, busque su presencia en la web para evaluar la madurez digital. Las empresas con una presencia web débil tienen mejores perspectivas para los servicios de marketing.
Python
def enrich_lead(lead: dict) -> dict:
name = lead['name']
website = lead.get('website', '')
domain = website.split('/')[2] if '/' in website and len(website.split('/')) > 2 else ''
if not domain:
lead['web_score'] = 0
lead['web_signals'] = 'no website'
return lead
# Check web presence
resp = requests.post(URL, headers=H,
json={'query': f'site:{domain}', 'country_code': 'us', 'num_results': 5})
indexed_pages = len(resp.json().get('organic_results', []))
time.sleep(0.3)
# Check social presence
resp2 = requests.post(URL, headers=H,
json={'query': f'"{name}" ({lead["location"]})', 'country_code': 'us', 'num_results': 5})
mentions = len(resp2.json().get('organic_results', []))
# Score: higher = more established web presence
lead['indexed_pages'] = indexed_pages
lead['web_mentions'] = mentions
lead['web_score'] = min(indexed_pages * 2 + mentions, 20)
lead['web_signals'] = 'strong' if lead['web_score'] > 10 else 'moderate' if lead['web_score'] > 5 else 'weak'
return lead
enriched = enrich_lead(leads[0])
print(f'{enriched["name"]}: web_score={enriched["web_score"]}, signals={enriched["web_signals"]}')Paso 3: Calificar y exportar la lista de clientes potenciales
Calcule una puntuación compuesta de clientes potenciales basada en la calificación, el recuento de reseñas y la presencia en la web. Exportar resultados puntuados a CSV ordenados por puntuación.
Python
def score_lead(lead: dict) -> float:
score = 0
# Rating score (high rating = established business)
rating = float(lead.get('rating', 0) or 0)
score += rating * 4 # Max 20
# Reviews (more reviews = larger business)
reviews = int(lead.get('reviews', 0) or 0)
score += min(reviews / 10, 15) # Max 15
# Web presence (weak = better prospect for services)
web = lead.get('web_score', 0)
if web <= 5:
score += 15 # Weak web = needs help
elif web <= 10:
score += 8
return round(score, 1)
def build_lead_list(category: str, locations: list, output: str = 'leads.csv') -> list:
all_leads = []
for loc in locations:
leads = find_businesses(category, loc)
for lead in leads:
enrich_lead(lead)
lead['lead_score'] = score_lead(lead)
all_leads.append(lead)
time.sleep(0.2)
print(f'{loc}: {len(leads)} leads found')
# Sort by score
all_leads.sort(key=lambda x: x.get('lead_score', 0), reverse=True)
# Export
keys = ['name', 'lead_score', 'phone', 'website', 'rating', 'reviews', 'web_signals', 'location', 'address']
with open(output, 'w', newline='') as f:
writer = csv.DictWriter(f, fieldnames=keys, extrasaction='ignore')
writer.writeheader()
writer.writerows(all_leads)
cost = len(all_leads) * 0.015
print(f'\nPipeline complete: {len(all_leads)} scored leads')
print(f'Top leads:')
for lead in all_leads[:5]:
print(f' [{lead["lead_score"]:5.1f}] {lead["name"][:30]} | {lead["web_signals"]} web | {lead.get("phone", "N/A")}')
print(f'Cost: ${cost:.3f}')
print(f'Saved to {output}')
return all_leads
build_lead_list('dental offices', ['Denver CO', 'Boulder CO'])Ejemplo en Python
Python
import os, requests, time
SCAVIO_KEY = os.environ['SCAVIO_API_KEY']
H = {'x-api-key': SCAVIO_KEY, 'Content-Type': 'application/json'}
def lead_gen(category, location):
resp = requests.post('https://api.scavio.dev/api/v1/search', headers=H,
json={'query': f'{category} {location}', 'country_code': 'us', 'num_results': 10})
leads = resp.json().get('local_results', resp.json().get('local_pack', []))
print(f'{category} in {location}: {len(leads)} leads')
for b in leads[:5]:
name = b.get('title', b.get('name', ''))
rating = b.get('rating', 'N/A')
phone = b.get('phone', 'N/A')
print(f' {name[:30]} | {rating} stars | {phone}')
print(f'Cost: $0.005')
for loc in ['Denver CO', 'Boulder CO']:
lead_gen('dental offices', loc)
time.sleep(0.3)Ejemplo en JavaScript
JavaScript
const SCAVIO_KEY = process.env.SCAVIO_API_KEY;
async function leadGen(category, location) {
const resp = await fetch('https://api.scavio.dev/api/v1/search', {
method: 'POST',
headers: { 'x-api-key': SCAVIO_KEY, 'Content-Type': 'application/json' },
body: JSON.stringify({ query: `${category} ${location}`, country_code: 'us', num_results: 10 })
});
const data = await resp.json();
const leads = data.local_results || data.local_pack || [];
console.log(`${category} in ${location}: ${leads.length} leads`);
leads.slice(0, 5).forEach(b => {
console.log(` ${(b.title || b.name || '').slice(0, 30)} | ${b.rating || 'N/A'} stars`);
});
}
(async () => {
await leadGen('dental offices', 'Denver CO');
await leadGen('dental offices', 'Boulder CO');
})();Salida esperada
JSON
Found 8 dental offices in Denver
ACE Dental: web_score=4, signals=weak
Denver CO: 8 leads found
Boulder CO: 6 leads found
Pipeline complete: 14 scored leads
Top leads:
[ 44.2] Mountain View Family Dental | weak web | (303) 555-0123
[ 42.8] Cherry Creek Dental Center | weak web | (303) 555-0456
[ 38.5] Denver Smile Design | moderate web | (303) 555-0789
[ 36.1] Boulder Dental Arts | weak web | (720) 555-0321
[ 33.9] Pearl Street Dentistry | moderate web | (720) 555-0654
Cost: $0.210
Saved to leads.csv