How to Build a Proposal Tracking and Follow-Up System

This proposal tracking and follow up automation system tells you exactly when prospects open your proposals and triggers follow-ups automatically. I use this to close the gap between sending and signing.

What You Need Before Starting

• Python 3.8+
• Claude or GPT API key
• Jinja2 for templating
• weasyprint for PDF generation

Step 1: Create Tracked Links

Generate a unique tracking URL for each proposal. When the prospect clicks it, you know they are looking. This replaces the blind send-and-hope approach.

import uuid
import sqlite3
from datetime import datetime

def create_tracked_proposal(deal_id, proposal_path):
    tracking_id = str(uuid.uuid4())[:8]
    conn = sqlite3.connect("proposals.db")
    conn.execute(
        "INSERT INTO tracked_proposals (tracking_id, deal_id, proposal_path, created_at) VALUES (?, ?, ?, ?)",
        (tracking_id, deal_id, proposal_path, datetime.now().isoformat())
    )
    conn.commit()
    return f"https://proposals.yourdomain.com/view/{tracking_id}"

Step 2: Log View Events

Serve the proposal through your tracking endpoint. Every page load gets logged with a timestamp and basic visitor info. This tells you not just if they opened it, but how many times.

from flask import Flask, request
from datetime import datetime

app = Flask(__name__)

@app.route("/view/<tracking_id>")
def track_view(tracking_id):
    log_event(tracking_id, {
        "timestamp": datetime.now().isoformat(),
        "ip": request.remote_addr,
        "user_agent": request.headers.get("User-Agent"),
    })
    return serve_proposal(get_path(tracking_id))

Step 3: Trigger Follow-Ups

First view triggers a soft follow-up 24 hours later. Three views without a response means escalation. The prospect is interested but stuck on something. That is when your sales rep needs to call.

def on_view(tracking_id):
    deal = get_deal(tracking_id)
    views = get_view_count(tracking_id)

    if views == 1:
        schedule_followup(deal["owner"], deal["id"], delay_hours=24,
            message=f"Prospect opened your proposal for {deal['name']}")

    if views >= 3 and not has_responded(deal["id"]):
        escalate_to_manager(deal["id"],
            reason="Viewed 3+ times without responding")

Step 4: Build Engagement Dashboard

Show all active proposals, their view counts, and which need attention. Sort by engagement so the hottest prospects surface to the top.

def proposal_dashboard():
    proposals = get_active_proposals()
    dashboard = []
    for p in proposals:
        views = get_view_count(p["id"])
        dashboard.append({
            "deal": p["deal_name"],
            "sent_date": p["created_at"],
            "views": views,
            "last_viewed": get_last_view(p["id"]),
            "status": "hot" if views >= 3 else "warm" if views >= 1 else "cold",
        })
    return sorted(dashboard, key=lambda x: x["views"], reverse=True)

Step 5: Measure Win Rates

Track which proposals convert. Over time this data shows you the average number of views before a close, the best day to send proposals, and which templates perform best.

def proposal_analytics(date_range):
    proposals = get_proposals(date_range)
    won = [p for p in proposals if p["outcome"] == "won"]
    return {
        "total_sent": len(proposals),
        "won": len(won),
        "win_rate": len(won) / max(len(proposals), 1),
        "avg_views_before_close": sum(p["views"] for p in won) / max(len(won), 1),
    }

What to Build Next

Add engagement scoring. Rank prospects by how much time they spend on each section.

Related Reading

• Creating an Automated Affiliate Tracking System - automated affiliate tracking system
• The Automation Decision Tree - automation decision tree framework
• Building Your First Automation: A Complete Guide - first automation guide business