Overview
New leads enter your CRM daily with just a name and email. This workflow enriches each new lead automatically by searching Google for company information and Reddit for sentiment and employee discussions. It replaces multi-vendor enrichment stacks (Clearbit, Phantombuster, Google Custom Search) with a single Scavio MCP tool that the agent calls dynamically based on what data is missing.
Trigger
Cron schedule (daily at 10 AM UTC) or CRM webhook on new lead
Schedule
Daily at 10 AM UTC
Workflow Steps
Fetch unenriched leads
Query your CRM for leads added in the last 24 hours that lack company data (industry, size, tech stack).
Search Google for company info
For each lead's company, query Scavio Google search for firmographics, recent news, and tech stack signals.
Search Reddit for sentiment
Query Reddit for the company name to find employee reviews, product discussions, and pain points.
Parse and structure data
Extract industry, approximate size, technology mentions, and sentiment from search results.
Update CRM records
Write enrichment data back to each lead's CRM record with source URLs for verification.
Flag high-priority leads
Score leads by enrichment signals (growing company, active hiring, expressing pain points) and flag top prospects.
Python Implementation
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))JavaScript Implementation
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}))
};
}Platforms Used
Web search with knowledge graph, PAA, and AI overviews
Community, posts & threaded comments from any subreddit