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Three List-Building Methods: Software Scraping, List Brokers, and Manual Community Scraping

The Framework

The Three List-Building Methods from Alex Hormozi's $100M Leads solve Problem 1 of the Three Problems Strangers Create: you can't reach strangers if you don't have their contact information. Before any cold outreach campaign can begin, you need a list of people to contact — names, emails, phone numbers, or social profiles. These three methods produce lists with different tradeoffs between speed, cost, quality, and volume.

The Three Methods

1. Software Scraping. Use automated tools to extract contact information from public directories, LinkedIn profiles, websites, social media platforms, and business databases. Tools like Apollo, ZoomInfo, LinkedIn Sales Navigator, and various scraping scripts can produce thousands of contacts in hours. Software scraping is the fastest and highest-volume method.

Advantages: massive volume in minimal time, scalable to millions of contacts, and relatively low cost per contact. Modern tools can filter by industry, company size, role, location, and other targeting criteria.

Limitations: data quality varies significantly. Email addresses may be outdated (people change jobs), phone numbers may be wrong, and the targeting criteria may not perfectly match your ideal customer profile. The further your filters deviate from perfect accuracy, the more wasted outreach you produce.

2. List Brokers. Companies that compile and sell targeted contact lists segmented by industry, role, geography, company size, revenue, and dozens of other criteria. Brokers like InfoUSA, Dun & Bradstreet, and industry-specific data providers maintain databases of millions of business contacts.

Advantages: pre-segmented lists save the time of scraping and filtering yourself. Good brokers verify their data regularly, producing higher-quality contacts than raw scraping. Industry-specific brokers offer targeting precision that general tools can't match.

Limitations: cost per contact is higher than self-scraping. Lists may be oversold — if 50 competitors bought the same list, the contacts are receiving 50 similar cold emails. And broker data, while verified, still degrades over time as people change roles and companies.

3. Manual Community Scraping. Personally identifying prospects from online communities, industry forums, event attendee lists, social media groups, trade show directories, and professional associations. You manually visit each source, evaluate each potential contact for fit, and add qualified prospects to your list one by one.

Advantages: highest quality of any method because every contact has been manually verified for relevance. You've seen their profile, their activity, and their context — you know they're a real person in your target market. This knowledge also enables superior personalization in outreach (referencing their posts, their company, their community involvement).

Limitations: painfully slow compared to the other methods. One person might identify 20-50 high-quality contacts per hour through manual scraping, versus thousands per hour through software. This method is viable for low-volume, high-value outreach (expensive products/services) but impractical for mass campaigns.

Hormozi's Recommended Progression

Start with manual community scraping to build your initial list and refine your ideal customer profile through direct observation. The contacts you identify manually serve double duty: they're your first outreach targets AND they define the criteria for automated methods.

Once you've manually identified 100-200 ideal contacts and understand what makes them ideal (company size, role, industry, behavioral signals), use those criteria to configure software scraping or broker purchases at scale. The manual phase provides the targeting intelligence that makes the automated phases effective.

As your outreach matures and you can measure which contact sources produce the highest conversion rates, shift budget toward the highest-performing method. Some businesses find that broker lists convert 2x better than scraped lists despite costing 5x more — making brokers the better investment. Others find that software scraping at massive volume produces more total customers despite lower per-contact conversion.

Cross-Library Connections

Dib's CRM Customer Journey Mapping from Lean Marketing provides the infrastructure for managing contacts from all three sources. Tags, segments, and automated workflows differentiate broker-sourced leads from scraped leads from manually identified leads — enabling source-specific optimization.

Hormozi's Cold Outreach Scaling Triad builds on top of the list: once you have contacts (from any of the three methods), the Triad's three automation levers (automate delivery, automate distribution, multi-channel follow-up) transform the list into a functioning outreach system.

Voss's assumptions-to-hypotheses model from Never Split the Difference applies to list building: your initial manual scraping produces hypotheses about who your ideal contact is. Each outreach campaign tests those hypotheses. The conversion data refines your targeting, which improves the quality of subsequent lists.

Implementation

  • Start with manual community scraping this week. Identify 3-5 online communities where your ideal customers gather. Spend 2 hours building a list of 50-100 contacts.
  • Evaluate each contact against your ideal customer profile. Note which characteristics the highest-quality contacts share.
  • Use those characteristics to configure software scraping or broker purchases for your next batch.
  • Track conversion rate by list source. Manual lists, scraped lists, and broker lists may convert at dramatically different rates.
  • Invest in the source that produces the best LTGP-to-CAC ratio, not the cheapest per-contact cost.

    • 📚 From $100M Leads by Alex Hormozi — Get the book