The Value of Exact Match Domains (A Hamsterdam History Lesson)

By Ethan Lazuk

Welcome to another edition of Hamsterdam History!

This is a series of posts where we look at “vintage” SEO articles to celebrate their contributors, gain historical knowledge, and discuss how things have changed (or haven’t) since.

In this edition, we’ll be looking at “Google’s EMD Algo Update – Early Data” by Dr. Pete for the SEOMoz blog on September 29, 2012.

The article talks about data showing a decline in the visibility for 41 exact-match domains that fell out the of the top 10 positions.

The article has 141 comments as well, so it was quite a topic of conversation 14 years ago.

Let’s talk about what exact-match domains are and how their influence on search and now AI visibility has evolved.

What is an exact-match domain?

An exact-match domain (EMD) is a domain name that closely or exactly matches the keyword or query a site wants to rank for.

For example, if a site was targeting “cheap car insurance” as a query, its domain might be “cheapcarinsurance.com.”

Historically, Google used words in domain names as a relevance signal, hence the focus on EMDs.

In a 2011 Google Webmaster video, Matt Cutts acknowledged that Google assigned weight to keyword domains and said Google was considering “turning the knob down” because keyword-rich domains appeared to receive too much weight.

Another benefit of EMDs was keyword-rich anchor text in natural backlinks.

Today, however, while Google still acknowledges that domain words can contribute to relevance, their influence has been dramatically constrained (like we saw in the 2012 Moz article).

Google has an “exact match domain system,” but per Google’s documentation, that system prevents Google from giving too much credit to sites whose domains were designed to exactly match queries.

So while there are (or were) legitimate reasons to have an EMD, it’s generally a better practice to go with your brand name instead.

If I were advising a new business on choosing a domain name, I’d suggest choosing your brand (or something close to it) to build brand awareness over time, instead of an EMD, which is more limited for general marketing purposes.

In my mind, an EMD is an SEO-focused decision, not a people-first optimization. I have heard of people creating EMDs as third-party sites to try and get mentions from them for AI visibility, but that to me is a short-sighted and spammy tactic.

Retrieval has also evolved to make EMDs less relevant.

For starters, Google no longer needs literal word matching nearly as much as it once did. Its current ranking documentation describes systems such as neural matching and RankBrain that can understand relationships between concepts and retrieve pages even when those pages don’t contain all the exact words in the query. So rather than looking at whether a document or domain contains the words the user typed, Google’s systems can identify which pages or entities best satisfy what the person actually means.

We can also consider how ChatGPT (and other LLMs) use the site: operator in their fanout queries to find “official” websites, making them less susceptible to EMD influence, in theory.

Let’s look at a historical hypothetical example:

In 2010, a user might type in “project management software,” in which case the domain “projectmanagementsoftware.com” might look particularly relevan to search systems.

Fast forward to today, a prompt like “What’s a good project management platform for a small marketing agency?” might have the AI assistant generate fanout queries like “site:asana.com pricing.”

The system has effectively stopped asking “Which domain looks most like the query?” and started asking “Which entities might answer this question, and where can I verify facts about them?”

In short, the EMD has much less opportunity to act as a shortcut because the retrieval system may have selected the candidate entity before it even performs the final search.

Takeaways

Exact-match domains were more valuable when search engines needed simple lexical shortcuts for relevance, but modern search systems increasingly don’t.

Google’s response to EMDs was initially algorithmic by reducing the excessive weight given to domains that mirrored queries. AI search may take the idea even further: instead of discounting a keyword-rich domain, systems like ChatGPT can reformulate the user’s question, identify candidate brands or sources, and issue source-specific searches such as site: or “official.” The optimization target therefore moves from owning the query string to being the entity the system decides is worth investigating.

Outro

I hope you’ve enjoyed this edition of Hamsterdam History!

Stay tuned for another edition soon, or check out related history articles below.

Until next time, enjoy the vibes:

Thanks for reading. Happy optimizing!

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