Push GitHub Leads to Klenty

Why Klenty for Developer GTM?

Klenty is a sales engagement platform that sequences cold outreach across email, LinkedIn, calls, and SMS. For developer-focused GTM teams, Klenty's cadence engine lets you enroll GitHub leads — engineers who just starred your repo or mentioned your keyword — into automated sequences without leaving your existing workflow. GitLeads captures the signal; Klenty handles the outreach.

How GitLeads Pushes Leads to Klenty

GitLeads captures developer buying signals from GitHub in real time and can route enriched lead profiles into Klenty through three integration paths:

• Webhook → Klenty API: GitLeads fires a webhook on each new lead; a lightweight server (or Cloudflare Worker) POSTs to Klenty's prospect API
• Zapier: GitLeads → Zapier trigger → Klenty "Create/Update Prospect" action — no-code, 5-minute setup
• Make (Integromat): same pattern with Make's Klenty module for visual flow building
• n8n: self-hosted option using n8n's HTTP Request node to call Klenty API with GitLeads payload

Direct Klenty API Integration (Webhook Route)

// Klenty webhook receiver — enroll GitHub leads as prospects
import type { VercelRequest, VercelResponse } from '@vercel/node';

const KLENTY_API_KEY = process.env.KLENTY_API_KEY!;
const KLENTY_BASE = 'https://app.klenty.com/apis/v1';

interface GitLeadsPayload {
  login: string;
  name: string | null;
  email: string | null;
  company: string | null;
  location: string | null;
  bio: string | null;
  html_url: string;
  signal_type: 'star' | 'keyword';
  signal_context: string;
  repo?: string;
}

export default async function handler(
  req: VercelRequest,
  res: VercelResponse
) {
  const lead = req.body as GitLeadsPayload;
  if (!lead.email) return res.status(200).json({ skipped: 'no email' });

  // Create or update prospect in Klenty
  await fetch(`${KLENTY_BASE}/prospect`, {
    method: 'POST',
    headers: {
      'x-API-Key': KLENTY_API_KEY,
      'Content-Type': 'application/json',
    },
    body: JSON.stringify({
      Email: lead.email,
      FirstName: lead.name?.split(' ')[0] ?? lead.login,
      LastName: lead.name?.split(' ').slice(1).join(' ') ?? '',
      Company: lead.company ?? '',
      customFields: {
        GitHubProfile: lead.html_url,
        SignalType: lead.signal_type,
        SignalContext: lead.signal_context,
        GitHubRepo: lead.repo ?? '',
        Location: lead.location ?? '',
      },
    }),
  });

  // Optionally start a cadence immediately
  // await fetch(`${KLENTY_BASE}/cadence/start`, { ... })

  return res.status(200).json({ enrolled: lead.email });
}

Zapier Setup: GitLeads → Klenty (No-Code)

1. In GitLeads, go to Integrations → Zapier → Connect
2. Trigger: "New Lead from GitLeads" — fires on every new star or keyword signal
3. Action: "Create or Update Prospect in Klenty"
4. Map fields: Email, FirstName, LastName, Company, and custom field GitHubProfile
5. Optional second step: "Add to Cadence" — select your developer outreach cadence
6. Test with a live GitLeads signal and verify the prospect appears in Klenty

Klenty Cadence Strategy for Developer Leads

Developer buyers respond to directness and technical credibility. Klenty cadences for GitHub leads should be shorter and more technical than standard B2B sequences:

• Day 1: Personalized email referencing the exact repo starred or keyword mentioned (pulled from signal_context)
• Day 3: LinkedIn connection request with a note about the tool they showed interest in
• Day 6: Follow-up email with a technical blog post or integration example
• Day 10: Final email with a direct free-trial or sandbox CTA
• LinkedIn task at any point if no email — GitHub profile often links to LinkedIn

Filtering Leads Before Enrolling in Klenty

Not every GitHub signal warrants a Klenty sequence. Apply these filters before auto-enrollment:

• Email is present — Klenty sequences require a valid email address
• Followers > 10 — filters out bots and throwaway accounts
• Company field is non-empty — signals a professional context
• Bio does not contain "student" or "learning" — reduces student noise
• Signal type is "keyword" — keyword signals have higher intent than passive stars