Category: Cutting-Edge Domaining

Bayesian Thinking and the Probabilistic Reality of Domain Portfolio Sell-Through Rates

Sell-through rate has always been one of the most misunderstood metrics in domain investing. Investors talk about it casually, quote industry averages, and compare themselves to peers, yet rarely interrogate what the number actually represents or how uncertain it truly is. Traditional approaches treat sell-through as a fixed property of a portfolio, something that can…

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The Quiet Power of a Private Comparable Sales Database for Domainers

Comparable sales are the invisible scaffolding beneath every serious domain valuation, yet most investors rely on fragments. Public databases, anecdotal reports, forum posts, and headline sales form a loose collage that feels informative but is fundamentally incomplete. The problem is not that public comps are wrong, but that they are selective, delayed, and context-poor. A…

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Beyond Lists and Volumes: The Rise of AI-Assisted Keyword Expansion in Domaining

Keyword discovery has always been a foundational activity in domain investing, yet for most of its history it has been constrained by the tools available. Traditional keyword tools revolve around search volume, advertiser competition, and explicit query logs. They are built for marketers, not investors, and they inherently reflect what people already know how to…

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Using Google Trends Like a Quant as a Domain Investor

Google Trends is one of the most misunderstood tools in domain investing. Most investors glance at it briefly, see a spiky line, and either get excited or dismiss the signal as noise. Used casually, it is little more than a curiosity. Used like a quantitative analyst would use a time series, it becomes something very…

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Phonetic Similarity Scoring in Brandable Domaining

Brandable domains live or die by how they sound. Long before a buyer evaluates spelling, meaning, or market fit, they hear the name internally, subvocalized in their own voice or spoken aloud in conversation. This auditory dimension is so fundamental that it often overrides rational analysis. A name that sounds right feels inevitable; one that…

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From Words to Markets: Predicting Which New Terms Become Categories

Every major market category begins as a word that does not yet mean much. Before it anchors billions of dollars in value, a term often exists as a tentative label, used inconsistently by a small group of insiders. Most of these terms fade. A few crystallize into categories that shape industries, investment theses, and naming…

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AI-Generated Chatbots on Domain Landers: The Conversational Edge?

Domain landing pages have traditionally been static surfaces. A name, a price or contact form, and little else. This minimalism was born partly of convenience and partly of fear: fear of saying too much, fear of scaring buyers away, fear of revealing leverage. As domain portfolios scale and inbound interest grows more heterogeneous, this static…

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Getting Into the Inbox: Deliverability Engineering for Domain Investors

Email remains one of the most powerful tools available to domain investors, whether for outbound sales, follow-ups on inbound inquiries, escrow coordination, or relationship building with brokers and buyers. Yet email is also one of the most fragile channels. Messages that never reach the inbox might as well not exist, and in modern mail systems,…

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Using LLMs to Score Domain Brandability at Scale

The domain name market has always sat at the intersection of linguistics, psychology, and commerce, but until recently it relied heavily on human intuition and small-sample heuristics to determine what “sounds like a brand.” The emergence of large language models has shifted this balance by making it possible to operationalize brand intuition itself, turning what…

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Predicting Domain Renewal ROI with Machine Learning

For domain investors operating at scale, renewal decisions quietly determine long-term profitability more than almost any acquisition strategy. Every year, portfolios face a recurring tax in the form of renewal fees, and the decision to keep or drop a name is often made with incomplete information, gut instinct, or blunt heuristics like age or past…

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