The Problem
B2B prospect lists from databases (Apollo, ZoomInfo) provide firmographic data but miss real-time signals: recent news, product launches, hiring patterns, and online reputation.
The Scavio Solution
For each prospect, run 3 Google and Reddit searches ($0.015 total) to find recent news, reviews, and market context. Feed search snippets to an LLM for personalized outreach copy.
Before
Before search enrichment, a sales team sent generic cold emails to 200 prospects weekly. Reply rate: 2.1%. Each prospect received the same template with only name and company swapped.
After
After adding search enrichment, each prospect gets 3 search queries ($0.015). An LLM generates a custom opener referencing the company's recent news or product launch. Reply rate: 11.3%. Cost: $3/week for 200 prospects.
Who It Is For
Sales development reps, account executives, B2B marketers, and outreach teams that need real-time prospect context for personalization.
Key Benefits
- $0.015/prospect for 3 enrichment searches
- Real-time signals: funding, hiring, product launches
- Reddit sentiment adds qualitative context
- LLM generates personalized openers from search data
- Reply rates jump from 2% to 10%+
Python Example
import requests, os
H = {'x-api-key': os.environ['SCAVIO_API_KEY'], 'Content-Type': 'application/json'}
def enrich_prospect(company):
queries = [f'{company} news 2026', f'{company} review', f'{company} hiring']
context = []
for q in queries:
data = requests.post('https://api.scavio.dev/api/v1/search',
headers=H, json={'query': q, 'country_code': 'us'}).json()
for r in data.get('organic_results', [])[:2]:
context.append(f"{r.get('title', '')}: {r.get('snippet', '')}")
return {'company': company, 'context': context,
'cost': len(queries) * 0.005}
enriched = enrich_prospect('Acme Corp')
print(f"Found {len(enriched['context'])} context snippets at ${enriched['cost']}")JavaScript Example
const H = {'x-api-key': process.env.SCAVIO_API_KEY, 'Content-Type': 'application/json'};
async function enrichProspect(company) {
const queries = [`${company} news 2026`, `${company} review`];
const context = [];
for (const q of queries) {
const r = await fetch('https://api.scavio.dev/api/v1/search', {
method: 'POST', headers: H, body: JSON.stringify({query: q, country_code: 'us'})
}).then(r => r.json());
(r.organic_results || []).slice(0, 2).forEach(r =>
context.push(`${r.title}: ${r.snippet || ''}`));
}
return {company, context, cost: queries.length * 0.005};
}
enrichProspect('Acme Corp').then(e => console.log(`${e.context.length} snippets at $${e.cost}`));Platforms Used
Web search with knowledge graph, PAA, and AI overviews
Community, posts & threaded comments from any subreddit