From Manual to Machine: The Fundamentals Of Building Enterprise-Scale AI - Brie Moreau, White Light Digital Marketing
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We were drowning in link building chaos - managing massive campaigns across 1,000+ keywords for enterprise clients with traditional methods that just didn't scale. So we did what any overwhelmed team would do: we built a machine learning algorithm to do it better. Our AI-powered system now handles what used to take our entire team tens of thousands of hours, analyzing hundreds of thousands of websites and finding the perfect link opportunities with just a click. I'll share how we transformed our business with smart automation and why this approach is changing everything about digital marketing. Key Takeaways: • From Chaos to AI: How to identify when manual processes are holding you back and transition to intelligent automation that actually works • Smart Systems That Scale: Building technology that learns from your data and gets better over time, without needing a computer science degree • Real ROI Results: Practical insights on implementing AI solutions that deliver measurable business impact and 10x performance improvements
From Manual to Machine: The Fundamentals Of Building Enterprise-Scale AI - Brie Moreau, White Light Digital Marketing
- 1. MASTER CLASS Brie Moreau CEO WHITE LIGHT DIGITAL MARKETING From Manual to Machine: The Fundamentals Of Building Enterprise-Scale AI SYDNEY, AUSTRALIA ~ AUGUST 13 - 14, 2025 DIGIMARCONAUSTRALIA.COM | #DigiMarConAustralia
- 2. An Indie Hackers Guide to the Future of AI - Today Brie Moreau +
- 3. Our Mission & Astronauts • 18 years SEO experience • Founded the longest running remote Digital Marketing agency in Australia – White Light Digital Marketing 70+ employees worldwide • Mainly focus on Fortune 500 companies and US private equity • We solve complex and expensive problems using SEO, Data Science, Machine Learning & AI • Though we also work with smaller Australian based clients too! • Go Australia, lets make this tech community stronger and smarter <3
- 4. “If you want to understand SEO, build a search engine…” John Mueller, Senior Webmaster Trends Analyst at Google What this talk isn’t: 7 Tips and 5 Hacks to Use AI Tools Instead, this is you understanding the fundamentals of AI, Machine Learning, SEO and Data Science from first principles thinking. Welcome to the Indie Hacker’s Guide to building Google’s search engine in 2025 We’ll cover: • The most important Google patents of today and how to implement for them • Some foundational knowledge in LLM’s, Machine Learning and Data Science • Why content and guest posts don’t work anymore (and why semantic links do) • And how to rank #1 for the hardest keyword in the world, with proof • I am teaching you how to fish, not giving you fish. And yes it will be an expansive and wild ride, I hope you enjoy <3
- 5. Our Bio
- 6. The most volatile period in Google ever…
- 7. And this
- 8. This too
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- 12. But wait, there’s more… even with the new sites.
- 13. Understanding Information Retrieval Costs The strongest and cleanest signal wins the result Create an on-page and off-page pressure system to alert Google Your saving Google time and money = traffic!
- 14. What is Vector Search and LLMs? digimarcon.wldm.io
- 15. Word2Vec is a neural network model that learns word associations from a large corpus of text. It predicts a word based on its context (surrounding words) or predicts surrounding words given a target word. Apple = fruit or tech company? Word2Vec Google’s First LLM
- 16. Words = Vectors
- 17. Words = Vectors Through training, the model adjusts word vectors so words sharing similar contexts in the corpus have similar vector representations. These resulting vectors, known as word embeddings, capture semantic relationships between words.
- 18. Enable machine learning models to understand and process natural language more effectively by providing a numerical representation of word meanings. Word Embeddings
- 19. Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt When phase 1 of ML comes back as a good site. Then we scrape the page where the link comes from and do entity extraction with Googles NLP. Then cross check our Google BERT LLM embedding space to see if the keyword the link we want to get from is topically relevant. Entity Extraction On Link Building Pages
- 20. Entities Extracted of a Quality Website In an Embed Space
- 21. When phase 1 of ML comes back as a good site. Then we scrape the page where the link comes from and do entity extraction with Googles NLP. Then cross check our Google BERT LLM embedding space to see if the keyword the link we want to get from is topically relevant. Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt Entity Extraction On Link Building Pages
- 22. Entities Extracted of a Link Farm Site In an Embed Space Now compare the 2 clusters, see the difference?
- 23. Cosine Similarity Is used because it captures the semantic meaning behind words better than other maths used in Machine Learning and AI
- 24. What cosine similarity means for backlinks • WLDM links have a significantly higher average CS Score (0.35) compared to Vendor links (0.20) • WLDM links perform 1.8x better than Vendor links based on CS Score • WLDM links have a more consistent performance profile with most scores clustering in the 0.3-0.5 range • The dataset contains 520 WLDM links vs only 28 Vendor links https://digimarcon.wldm.io/cs-compare
- 25. Correlational Matrix Showing all websites with all variables and factors to show how a link farm looks compared to a good website
- 26. Current Machine Learning Protocol Y o u r t e x t h e r e We can successfully identify link farms with ML. So if we can, imagine how Google can do it? Again is it ranking for any results with the specific eyword you want to rank for? If not move on! Its that simple. Training Set: 9,000 Guest post farms compared to 9,000 “average” sites Over 1000 features compared – aka content length/diversity, keywords ranking for, backlinks with traffic and other features. How long would it take a link builder to check 1000 features per website? This is how detailed we go. Machine>Human
- 27. Y o u r t e x t h e r e Algorithms • Decision Tree • Random Forest • XGBoost • Logistic Regression • SVM (Support Vector Machine) • Neural Networks Example: 3 out of 5 models say it’s a link farm → final result = link farm.
- 28. Entity Distribution This shows how link farms are different from normal sites and we can predict link farms at scale.
- 29. Y o u r t e x t h e r e Guest Post Sentiment Analysis Through our research we discovered sentiment analysis is a good predictor for finding link farms. Super easy to spot.
- 30. Y o u r t e x t h e r e If this is what we can do, just imagine what Google can… • Neural Networks
- 31. Everybody Knows PageRank So the question is: Has your SEO ever run PageRank algorithm on your site? • This algorithm is the foundation of the Information Age <3 • Ranks pages based on link authority, not keywords. • Not how many links you have, but who links to you (& their authority) • Google never stopped using PageRank – they just stopped showing public scores. • PageRank flows through links - internal and external - like water. Poor architecture = lost ranking power. Internal PageRank is crucial for SEO. • Fix link flow • Reveal silos and orphans • Data-backed structure • Unlock hidden ranking potential • Spot link hoarders • Get more ROI from existing content/backlinks
- 32. Internal PageRank Score Using Screaming Frog and Google Search Console; you can find your IPR score. Analysis for a client, more than 4k URLs and more than 300k inlinks. The table shows the In PageRank of each link - the higher the PageRank, the higher the authority of the page. This table allows us to also uncover correlations between Internal PageRank and other key metrics like CTR and average position.
- 33. Then, you can visualize it in Gephi • The bigger the node, the higher number of links • Green nodes = high position in Google • Big black nodes = high number of in links not listed in Google and watch the magic happen.
- 34. Semantic Linkbuilding Y o u r t e x t h e r e
- 35. Y o u r t e x t h e r e Content is NOT King! The cost of creating high quality content will go to $0 Think of algo as a bunch of individual music tracks that are altered for each keyword search https://zyppy.com/seo/google-index-size/
- 36. So what is important then? A Private Conversation With Gary
- 38. Reasonable Surfer Patent Its simply tracking links with clicks and user engagement metrics on people going to the page. https://patents.google.com/patent/US8117209B1/en
- 40. The worlds biggest link building aggregator We scraped almost all guest post marketplaces (23 to be exact) to create the largest link building opportunity database. We have over 500,000 websites on file and 100’s of Millions of keywords that we can find linking opportunities for in the top 20 rankings. So we put a list of keywords in and we find pages that are ranking for that EXACT keyword (or variations of) and have a high probability of linking to them
- 41. Linkbuilding the Data Science Way A client gave us 1000 keywords they want to rank for. Then we found over 20,000 linking opportunities. We do what would take hundreds of thousands man hours by running a script and get results almost instantly. As opposed to probably years of for a large link building team. We can do this in ANY niche and can get the best of the best of links and avoid the rest. From the 20,000 we found, we picked the best 1,000 for the client based on relevancy and pricing. Best ROI from link building campaign possible!
- 42. Y o u r t e x t h e r e Massive thanks and credit to the SEO genius Peter Macinkovic SEO Lead for Stake
- 44. The change in last 10 months since Stake.com started working with us
- 45. Quick Recap Information retrieval cost efficiency and speed aka the strongest signal wins the result Make the strongest signal by giving Google exactly what its looking for with: • Semantic backlinks that rank for keyword (or related keyword) in top 20 • External pressure from Semantic backlinks and internal pressure from Page Rank internal linking optimisation. The combination of these pressure systems will create the strongest signal for that keyword. LESS = MORE
- 46. Thanks for listening <3 Subscribe to my YouTube Channel @Brie Moreau SEO Follow me on LinkedIn www.linkedin.com/in/briemoreau brie@wldm.io https://digimarcon.wldm.io