Pricing & Monetization & tech stack - coding4vinayak/leadworks-intelligence-platform- GitHub Wiki
For LeadWorks Intelligence, pricing should be:
✅ Scalable → Supports small businesses & enterprises.
✅ Value-Based → Higher cost for premium AI insights.
✅ Flexible → Monthly/Annual plans & usage-based tiers.
4.1 Pricing Models
1️⃣ Freemium Model (Basic Free, Paid Upgrades)
✅ Best for: Gaining early traction & user base.
🔹 Features:
Free basic lead scoring (limited leads per month).
No CRM integrations.
No AI insights.
No automation.
💰 Paid Plan Unlocks:
✔ Advanced AI lead scoring.
✔ CRM sync & automation.
✔ Lead enrichment & insights.
2️⃣ Subscription Model (Fixed Monthly Fee)
✅ Best for: B2B clients needing predictable costs.
💰 Example Pricing Tiers:
Plan Leads/Month AI Insights CRM Sync Automation Price
Starter 500 Basic ❌ ❌ $19/mo
Pro 5,000 Advanced ✅ ✅ $79/mo
Enterprise Unlimited Custom AI ✅ ✅ $249/mo
🔹 Upsell Opportunity:
Offer add-ons (e.g., extra 10,000 leads = $50).
White-label solutions for agencies.
3️⃣ Usage-Based Model (Pay per Lead Processed)
✅ Best for: Businesses with fluctuating needs.
💰 Example Pricing:
$0.01 per lead processed.
$0.05 per AI-enriched lead.
$0.10 per predictive insight.
🔹 Ideal for API integrations where users want to scale dynamically.
4️⃣ Enterprise Custom Pricing
✅ Best for: Large teams & custom needs.
Custom AI models & scoring rules.
Dedicated support & SLAs.
Integration with private CRM setups.
💰 Pricing: $10,000+ per year (Custom Quote).
4.2 Monetization Enhancements
💡 1. Lead Data Marketplace
Sell pre-verified, enriched leads to businesses.
AI can score & recommend the best leads.
Companies pay per lead or per batch.
💡 2. White-Label Licensing
Offer a custom-branded version to agencies.
Charge a one-time setup fee + recurring revenue.
💡 3. Affiliate & API Partnerships
Integrate with CRM tools & marketing platforms (HubSpot, Salesforce).
Charge API usage fees for data enrichment.
5. Tech Stack & Backend Architecture
5.1 Core Technology Choices
Component Technology
Backend FastAPI / Flask (Python)
Database PostgreSQL / MongoDB (Lead Storage)
AI Model Scikit-learn / TensorFlow (Lead Scoring)
Frontend React / Next.js (User Interface)
Hosting AWS / Vercel / GCP
CRM Integrations HubSpot, Salesforce API
Automation Zapier / Webhooks
🔹 Why these choices?
✅ Scalable & Fast → FastAPI ensures async performance.
✅ Secure & Reliable → PostgreSQL handles structured lead data.
✅ Modular & Future-Proof → Can add ML models as microservices.
5.2 System Architecture
📌 How the system processes leads:
1️⃣ User Uploads or API Ingests Leads → Leads enter PostgreSQL.
2️⃣ AI Model Scores & Enriches Data → Fetches LinkedIn, company info.
3️⃣ Quality Check Runs (Spam, Duplicates, Completeness)
4️⃣ CRM Sync & Automations Triggered → Based on lead score & actions.
5️⃣ User Dashboard Shows Insights → Conversion probability, engagement tracking.
🔹 Microservices Approach:
Lead Scoring Service → API-based scoring using ML.
Lead Enrichment Service → Fetches missing details.
Automation Engine → Syncs CRM, triggers workflows.
5.3 API Endpoints (For External Integrations)
Endpoint Function
POST /leads/upload Upload CSV or JSON leads.
GET /leads/score Get AI lead scores.
POST /leads/enrich Fetch missing data.
POST /crm/sync Sync lead data with HubSpot/Salesforce.
POST /automation/trigger Run automation workflows.
🔹 Why APIs Matter?
✅ Allows third-party platforms to integrate LeadWorks.
✅ Enables white-label solutions (other apps can use our AI).