Finding YouTube influencers for brand partnerships typically requires expensive influencer marketing platforms ($200-500/month) or manual searching. This tutorial builds an automated pipeline using SERP data to discover YouTubers in any niche, score their relevance, and compile outreach lists. Each search costs $0.005, and discovering 50 influencers in a niche costs about $0.05 (10 searches).
Prerequisites
- Python 3.9+ installed
- requests library installed
- A Scavio API key from scavio.dev
Walkthrough
Step 1: Define niche search queries
Create search queries designed to surface YouTube channels in your target niche. Combine topic keywords with YouTube-specific modifiers.
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}')Step 2: Discover creators from search results
Search each query and extract unique YouTube channel names and video data from the results.
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')Step 3: Score and rank creators
Score each creator based on how often they appear across searches, number of unique videos found, and niche relevance.
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]}')Python Example
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')JavaScript Example
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}`)));Expected Output
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