Trouver des influenceurs YouTube pour des partenariats de marque nécessite généralement des plateformes de marketing d'influence coûteuses (200-500 $/mois) ou une recherche manuelle. Ce tutoriel construit un pipeline automatisé utilisant les données SERP pour découvrir des YouTubers dans n'importe quel créneau, évaluer leur pertinence et compiler des listes de prospection. Chaque recherche coûte 0,005 $, et découvrir 50 influenceurs dans un créneau coûte environ 0,05 $ (10 recherches).
Prérequis
- Python 3.9+ installé
- bibliothèque requests installée
- Une clé API Scavio depuis scavio.dev
Parcours
Étape 1: Définir des requêtes de recherche de niche
Créez des requêtes de recherche conçues pour faire apparaître les chaînes YouTube dans votre créneau cible. Combinez des mots-clés thématiques avec des modificateurs spécifiques à YouTube.
Python
def generate_queries(niche: str, modifiers: list = None) -> list:
if modifiers is None:
modifiers = [
'best {niche} youtube channels 2026',
'top {niche} youtubers to follow',
'site:youtube.com {niche} tutorial',
'site:youtube.com {niche} review 2026',
'{niche} youtube creator recommendations',
]
return [m.format(niche=niche) for m in modifiers]
niche = 'python programming'
queries = generate_queries(niche)
for q in queries:
print(f' {q}')
print(f'\n{len(queries)} queries = ${len(queries) * 0.005:.3f}')Étape 2: Découvrir les créateurs à partir des résultats de recherche
Recherchez chaque requête et extrayez les noms de chaînes YouTube uniques et les données vidéo des résultats.
Python
import requests, os, time, re
from collections import defaultdict
SCAVIO_KEY = os.environ['SCAVIO_API_KEY']
def discover_creators(queries: list) -> dict:
creators = defaultdict(lambda: {'videos': [], 'mentions': 0, 'sources': []})
for query in queries:
resp = requests.post('https://api.scavio.dev/api/v1/search',
headers={'x-api-key': SCAVIO_KEY, 'Content-Type': 'application/json'},
json={'query': query, 'country_code': 'us', 'num_results': 10})
for r in resp.json().get('organic_results', []):
link = r.get('link', '')
title = r.get('title', '')
# Extract channel from YouTube URLs
if 'youtube.com/watch' in link:
# Channel often in title as "Video Title - Channel Name"
parts = title.replace(' - YouTube', '').split(' - ')
if len(parts) >= 2:
channel = parts[-1].strip()
creators[channel]['videos'].append(parts[0].strip())
creators[channel]['mentions'] += 1
creators[channel]['sources'].append(link)
elif 'youtube.com/@' in link or 'youtube.com/c/' in link:
channel = title.replace(' - YouTube', '').strip()
creators[channel]['mentions'] += 1
creators[channel]['sources'].append(link)
time.sleep(0.3)
return dict(creators)
creators = discover_creators(queries)
print(f'Discovered {len(creators)} unique creators')
for name, data in sorted(creators.items(), key=lambda x: -x[1]['mentions'])[:5]:
print(f' {name}: {data["mentions"]} mentions, {len(data["videos"])} videos')Étape 3: Noter et classer les créateurs
Notez chaque créateur en fonction de la fréquence d'apparition dans les recherches, du nombre de vidéos uniques trouvées et de la pertinence du créneau.
Python
def score_creators(creators: dict, niche_terms: list) -> list:
scored = []
for name, data in creators.items():
# Frequency score: more mentions = more prominent
freq_score = min(data['mentions'] * 15, 40)
# Content volume: more videos found = more active
volume_score = min(len(data['videos']) * 10, 30)
# Niche relevance: check if videos match niche
niche_text = ' '.join(data['videos']).lower()
term_hits = sum(1 for t in niche_terms if t.lower() in niche_text)
relevance_score = min(term_hits / max(len(niche_terms), 1) * 30, 30)
total = round(freq_score + volume_score + relevance_score, 1)
scored.append({
'channel': name, 'score': total,
'mentions': data['mentions'],
'videos_found': len(data['videos']),
'sample_videos': data['videos'][:3],
'channel_url': data['sources'][0] if data['sources'] else ''
})
scored.sort(key=lambda x: -x['score'])
return scored
niche_terms = ['python', 'programming', 'tutorial', 'code']
ranked = score_creators(creators, niche_terms)
print(f'Top 10 {niche} YouTube creators:\n')
for i, c in enumerate(ranked[:10], 1):
print(f'{i:2}. [{c["score"]:5.1f}] {c["channel"]}')
if c['sample_videos']:
print(f' Videos: {c["sample_videos"][0][:50]}')Exemple Python
Python
import requests, os, time
from collections import defaultdict
SCAVIO_KEY = os.environ['SCAVIO_API_KEY']
def find_creators(niche, count=5):
queries = [f'site:youtube.com {niche} tutorial', f'best {niche} youtubers 2026',
f'site:youtube.com {niche} review 2026']
creators = defaultdict(int)
for q in queries:
resp = requests.post('https://api.scavio.dev/api/v1/search',
headers={'x-api-key': SCAVIO_KEY, 'Content-Type': 'application/json'},
json={'query': q, 'country_code': 'us', 'num_results': 10})
for r in resp.json().get('organic_results', []):
title = r.get('title', '').replace(' - YouTube', '')
parts = title.split(' - ')
if len(parts) >= 2:
creators[parts[-1].strip()] += 1
time.sleep(0.3)
return sorted(creators.items(), key=lambda x: -x[1])[:count]
for name, mentions in find_creators('python programming'):
print(f'{name}: {mentions} mentions')Exemple JavaScript
JavaScript
const SCAVIO_KEY = process.env.SCAVIO_API_KEY;
async function findCreators(niche) {
const queries = [`site:youtube.com ${niche} tutorial`, `best ${niche} youtubers 2026`];
const creators = {};
for (const q of queries) {
const resp = await fetch('https://api.scavio.dev/api/v1/search', {
method: 'POST',
headers: { 'x-api-key': SCAVIO_KEY, 'Content-Type': 'application/json' },
body: JSON.stringify({ query: q, country_code: 'us', num_results: 10 })
});
for (const r of (await resp.json()).organic_results || []) {
const parts = r.title.replace(' - YouTube', '').split(' - ');
if (parts.length >= 2) {
const ch = parts[parts.length - 1].trim();
creators[ch] = (creators[ch] || 0) + 1;
}
}
}
return Object.entries(creators).sort((a, b) => b[1] - a[1]).slice(0, 10);
}
findCreators('python programming').then(c => c.forEach(([n, m]) => console.log(`${n}: ${m}`)));Sortie attendue
JSON
best python programming youtube channels 2026
top python programming youtubers to follow
site:youtube.com python programming tutorial
Discovered 18 unique creators
Tech With Tim: 4 mentions, 3 videos
Corey Schafer: 3 mentions, 2 videos
Programming with Mosh: 3 mentions, 2 videos
Top 10 python programming YouTube creators:
1. [ 85.0] Tech With Tim
Videos: Python Full Course for Beginners 2026
2. [ 72.5] Corey Schafer
3. [ 68.3] Programming with Mosh