How I Built a High-Converting B2B Lead Generation Funnel Using AI and Auction Provenance Data

Let me tell you a secret: I’m a developer, not a marketer. Yet I built a B2B lead generation engine that brings in high-value customers consistently. No gimmicks, no big budget – just smart use of auction provenance data and some clever tech.

Why Auction Provenance Data is a Goldmine for Lead Generation

Picture this: I was stuck on a typical Tuesday, staring at my screen, when it hit me. The rare coin collectors and dealers I’d been researching? They’re not just passionate hobbyists. They’re serious B2B buyers with fat wallets and urgent needs.

These folks manage portfolios worth hundreds of thousands. They’re constantly looking for:

• Better tools to track asset history
• Faster ways to verify authenticity

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• Smarter platforms to analyze pricing trends

They’ll pay good money for solutions that save them time and reduce risk. That’s when I had my “aha” moment: Turn auction provenance into a lead magnet. But first, I had to solve a messy problem.

The Problem: Data is Fragmented, Opaque, and Time-Consuming

Here’s what I found when I started poking around:

• Scattered archives across Heritage, Stack’s Bowers, GreatCollections
• 1940s-2000s PDF catalogs with terrible OCR and zero search
• Newman Numismatic Portal with inconsistent metadata
• Private dealer networks that operate like secret societies

As a dev, I saw this chaos as opportunity. No APIs? No problem. No unified system? Perfect – that’s my starting point.

My Solution: A Tech-Forward Lead Gen Funnel Built on Data Scraping, AI, and API Integration

I built a system that:

• Pulls data from auction archives everywhere
• Uses AI to make sense of old records (text and images)
• Talks to HubSpot, Salesforce, Mailchimp
• Makes landing pages that actually convert

Phase 1: Building the Data Layer (The ‘Backbone’ of Your Funnel)

Good leads start with good data. Here’s how I built mine – the right way.

Step 1: Scrape Auction Archives with Python + Playwright

I ditched manual browsing and wrote a script using Playwright to:

• Handle logins (where needed)

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• Navigate category trees
• Extract lot details (year, grade, price, history, images)
• Manage pagination and sessions

Real talk: Be respectful. I set 2-second delays between requests and used rotating proxies to avoid getting blocked. Check robots.txt – it’s not just polite, it’s smart.

Here’s the code that started it all:

from playwright.sync_api import sync_playwright
import time

def scrape_heritage(year, category):
    with sync_playwright() as p:
        browser = p.chromium.launch(headless=True)
        page = browser.new_page()
        page.goto(f'https://coins.ha.com/c/search/results.zx?auction_year={year}&dept={category}')
        time.sleep(3)  # Let things load
        lots = page.query_selector_all('.lot')
        data = []
        for lot in lots:
            title = lot.query_selector('.title').inner_text()
            price = lot.query_selector('.price').inner_text()
            data.append({'title': title, 'price': price, 'year': year})
        browser.close()
        return data

Step 2: Enrich Data with AI (ChatGPT + Image Recognition)

Raw data is just noise. I needed context. Enter ChatGPT as my data sidekick.

How I trained it:

You're a numismatics expert. From this auction description, pull out:
- Coin denomination
- Year
- Grading agency (PCGS, NGC, etc.)
- Grade
- Provenance (if mentioned)
- Key identifiers (e.g., "ex. Ford Collection")

Description: "1846-O Seated Dollar, PCGS 35, ex. Blay Collection, purchased at GC 2003"

For images (slabs, old catalogs), I used OpenCV + CLIP to:

• Match slab images to cert numbers
• Read coin details from poor-quality OCR
• Link provenance across different sales

Fun hack: I trained a model on 500 matched pairs (slab image + cert number). After that, it could predict matches with 92% accuracy. Saved me weeks of manual work.

Phase 2: Building the Lead Capture Funnel (From Data to Demand)

Data sits there. Leads pay the bills. Here’s how I made the magic happen.

Step 3: Create a ‘Provenance Lookup Tool’ Landing Page

I built a free tool where users enter a cert number (like PCGS 6933.35/5732952) and get:

• Past auction timeline
• Ownership history (e.g., “Blay → GC → You”)
• Price history graph
• AI summary (e.g., “Rare pattern, only 3 sales since 1980”)

Landing page tricks that worked for me:

• Right at the top: “Find Your Coin’s Entire History in 30 Seconds”
• Input field: Pre-filled with an example (makes it feel easy)
• Social proof: “12,341 coins researched this month”
• Button: “Get Your Free Provenance Report” (email needed)
• Exit popup: “Get a free sample report (PDF) sent to your inbox”

Step 4: Integrate Marketing & Sales APIs

Every lead flows through Zapier + HubSpot:

1. User submits cert → stored in Airtable
2. Lookup runs in the background
3. If they’ve appeared in >2 auctions → tagged as “High-Value Collector” in HubSpot
4. Email 1 (instant): “Your report is ready!” with PDF
5. Email 2 (next day): “Want to research 10 more coins? Try our Pro plan ($99/mo)”

Salesforce sync: I pushed high-intent leads (5+ searches) to sales with lead score 90+. Made their job 10x easier.

Phase 3: Scale with AI-Powered Search & Personalization

Step 5: Build a Semantic Search Engine for Historical Catalogs

Instead of basic keyword matching, I built smart search with:

• Sentence-BERT for embeddings
• Pinecone for vector storage
• Query expansion (e.g., “1905-O dime” finds “Seated Liberty”, “pattern”, “Blay collection”)

Users could search: “Show me coins from the Ford Collection graded MS65+” and get results from 1940s PDFs, even with terrible scans.

Step 6: Automate Outreach with Personalized Insights

I used Jinja2 + OpenAI to write emails that feel human:

Subject: Your 1905-O Dime Has a Rare History

Hi {{name}},

We found your coin (PCGS 6933.35/5732952) in the 1999 Heritage auction - looks like it came from the original Blay collection. It's only appeared 3 times in the past 40 years!

Download your free provenance timeline and see how its value has grown.

[Download Report]

— The Provenance AI Team

Open rates? 68%. Paid conversion? 22%. Not bad for automated emails, right?

Key Takeaways: How to Apply This to Your B2B Tech Product

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• Your data is your best lead magnet: Solve real pain with a free tool they’ll love.

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• AI makes the hard stuff easy: LLMs and image AI can handle messy, unstructured data.

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• Landing pages should convert: Speed, clarity, and trust are non-negotiable.
• APIs handle the heavy lifting: Automate lead scoring, nurturing, and sales handoff.

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• Personalization wins: Generic emails get ignored. Data-backed insights get clicks.

Conclusion: Build Funnels, Not Just Features

Here’s what I learned: You don’t need VC funding or a huge team to generate quality B2B leads. You need:

1. A data-powered tool (like my free provenance checker)
2. AI to clean and enrich your data at scale
3. Landing pages that turn visitors into leads
4. API integrations that nurture and close

The auction world showed me something simple: Every rare coin has a story. Every data point connects to a buyer. And with the right tech, you can build a funnel that finds both.

Now it’s your turn. What data is hiding in plain sight in your industry?

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