Solution

LinkedIn Citation Enrichment for Replies

LinkedIn outreach and replies feel generic because they lack context about the recipient's company or recent activity. Manually researching each contact before replying takes 5-10

The Problem

LinkedIn outreach and replies feel generic because they lack context about the recipient's company or recent activity. Manually researching each contact before replying takes 5-10 minutes per person and does not scale.

The Scavio Solution

Before replying to a LinkedIn thread or sending outreach, call Scavio Google search with the person's name and company. Extract recent news, blog posts, or product launches. Reference a specific detail in your reply to demonstrate genuine awareness rather than template spam.

Before

Generic LinkedIn replies: 'Great post! Would love to connect.' No differentiation. Low response rate. Zero research per contact.

After

Enriched replies: 'Saw your team just launched the new dashboard feature last week. Our search API could feed live data into those widgets.' Response rate improves because the outreach feels human.

Who It Is For

Sales professionals, SDRs, LinkedIn outreach agencies, and anyone doing personalized B2B outreach at scale.

Key Benefits

  • Real-time context about any company or person via Google search
  • One API call per contact at $0.005
  • Specific references in outreach increase response rates
  • Automated enrichment scales to hundreds of contacts
  • Works with any outreach tool that supports custom fields

Python Example

Python
import requests, os
H = {'x-api-key': os.environ['SCAVIO_API_KEY']}

def enrich_contact(name: str, company: str) -> dict:
    resp = requests.post('https://api.scavio.dev/api/v1/search', headers=H,
        json={'platform': 'google', 'query': f'{name} {company} recent news 2026'},
        timeout=10)
    results = resp.json().get('organic', [])[:3]
    return {
        'name': name, 'company': company,
        'recent_context': [{'title': r['title'], 'snippet': r['snippet']} for r in results]
    }

context = enrich_contact('Jane Doe', 'Acme Corp')
print(f"Use in reply: {context['recent_context'][0]['snippet']}")

JavaScript Example

JavaScript
async function enrichContact(name, company) {
  const resp = await fetch('https://api.scavio.dev/api/v1/search', {
    method: 'POST',
    headers: { 'x-api-key': process.env.SCAVIO_API_KEY, 'Content-Type': 'application/json' },
    body: JSON.stringify({ platform: 'google', query: `${name} ${company} recent news 2026` })
  });
  const data = await resp.json();
  return (data.organic || []).slice(0, 3).map(r => ({ title: r.title, snippet: r.snippet }));
}

Platforms Used

Google

Web search with knowledge graph, PAA, and AI overviews

Frequently Asked Questions

LinkedIn outreach and replies feel generic because they lack context about the recipient's company or recent activity. Manually researching each contact before replying takes 5-10 minutes per person and does not scale.

Before replying to a LinkedIn thread or sending outreach, call Scavio Google search with the person's name and company. Extract recent news, blog posts, or product launches. Reference a specific detail in your reply to demonstrate genuine awareness rather than template spam.

Sales professionals, SDRs, LinkedIn outreach agencies, and anyone doing personalized B2B outreach at scale.

Yes. Scavio's free tier includes 500 credits per month with no credit card required. That is enough to validate this solution in your workflow.

LinkedIn Citation Enrichment for Replies

Before replying to a LinkedIn thread or sending outreach, call Scavio Google search with the person's name and company. Extract recent news, blog posts, or product launches. Refere