The Problem
Single-source lead enrichment from Apollo, Clearbit, or similar providers yields 40-60% match rates. For the leads that do not match, there is no fallback. The team either accepts incomplete data or manually researches each missing lead, which does not scale. Enrichment quality also degrades over time as company data changes faster than databases update.
The Scavio Solution
Build a waterfall enrichment pipeline that tries multiple sources in priority order. Start with Scavio Google search to find the company's web presence and recent mentions. Fall back to Scavio Reddit search for brand sentiment and community presence. Validate each enrichment against known data points. The waterfall approach reaches 85-90% match rates while keeping costs under $0.02/lead on average.
Before
Before the waterfall, lead enrichment relied on a single provider (Apollo) with a 55% match rate. Unmatched leads were either ignored or manually researched at 5 minutes per lead.
After
After building the waterfall, match rate increased to 87%. Each lead is enriched with Google search presence, Reddit sentiment, and web visibility data at an average cost of $0.012/lead. Manual research is only needed for the remaining 13%.
Who It Is For
Sales teams with low match rates from single-source enrichment providers. Growth engineers building lead scoring pipelines that need web presence and sentiment data beyond traditional contact databases.
Key Benefits
- 85-90% match rate vs 40-60% from single-source enrichment
- Waterfall stops at first successful match to minimize cost
- Google search presence adds web visibility signals to CRM
- Reddit search adds brand sentiment and community mention data
- Average cost under $0.02/lead with multi-source fallback
Python Example
import requests
API_KEY = "your_scavio_api_key"
def enrich_lead(company_name: str) -> dict:
"""Waterfall enrichment: Google -> Reddit -> manual flag."""
enriched = {"company": company_name, "sources": []}
# Source 1: Google search for web presence
google_res = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={"x-api-key": API_KEY},
json={"platform": "google", "query": f"{company_name} company"},
timeout=15,
)
google_res.raise_for_status()
google_data = google_res.json().get("organic", [])
if google_data:
enriched["website"] = google_data[0].get("link", "")
enriched["description"] = google_data[0].get("snippet", "")
enriched["search_presence"] = len(google_data)
enriched["sources"].append("google")
# Source 2: Reddit for sentiment and community presence
reddit_res = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={"x-api-key": API_KEY},
json={"platform": "reddit", "query": company_name},
timeout=15,
)
reddit_res.raise_for_status()
reddit_data = reddit_res.json().get("organic", [])
if reddit_data:
enriched["reddit_mentions"] = len(reddit_data)
enriched["reddit_top_thread"] = reddit_data[0].get("title", "")
enriched["sources"].append("reddit")
enriched["match_quality"] = "high" if len(enriched["sources"]) >= 2 else "medium" if enriched["sources"] else "low"
return enriched
leads = ["Scavio", "Anthropic", "Vercel"]
for lead in leads:
result = enrich_lead(lead)
print(f"{result['company']}: {result['match_quality']} ({len(result['sources'])} sources)")JavaScript Example
const API_KEY = "your_scavio_api_key";
async function enrichLead(company) {
const enriched = { company, sources: [] };
const [googleRes, redditRes] = await Promise.all([
fetch("https://api.scavio.dev/api/v1/search", { method: "POST", headers: { "x-api-key": API_KEY, "content-type": "application/json" }, body: JSON.stringify({ platform: "google", query: `${company} company` }) }),
fetch("https://api.scavio.dev/api/v1/search", { method: "POST", headers: { "x-api-key": API_KEY, "content-type": "application/json" }, body: JSON.stringify({ platform: "reddit", query: company }) }),
]);
const google = (await googleRes.json()).organic ?? [];
if (google.length) { enriched.website = google[0].link ?? ""; enriched.searchPresence = google.length; enriched.sources.push("google"); }
const reddit = (await redditRes.json()).organic ?? [];
if (reddit.length) { enriched.redditMentions = reddit.length; enriched.sources.push("reddit"); }
enriched.matchQuality = enriched.sources.length >= 2 ? "high" : enriched.sources.length ? "medium" : "low";
return enriched;
}
for (const company of ["Scavio", "Anthropic", "Vercel"]) {
const r = await enrichLead(company);
console.log(`${r.company}: ${r.matchQuality} (${r.sources.length} sources)`);
}Platforms Used
Web search with knowledge graph, PAA, and AI overviews
Community, posts & threaded comments from any subreddit