{"id":5964,"date":"2025-06-10T14:49:48","date_gmt":"2025-06-10T18:49:48","guid":{"rendered":"https:\/\/beomniscient.com\/?p=5964"},"modified":"2026-03-18T15:29:19","modified_gmt":"2026-03-18T19:29:19","slug":"the-matthew-effect","status":"publish","type":"post","link":"https:\/\/beomniscient.com\/blog\/the-matthew-effect\/","title":{"rendered":"The Matthew Effect"},"content":{"rendered":"\n

A few months ago, on a relatively unremarkable week, I wrote a listicle.<\/p>\n\n\n\n

It was titled something like \u201cBest Generative Engine Optimization (GEO) Agencies<\/a>,\u201d and at the top of that list I placed (surprise) my own agency, Omniscient Digital. To accompany it, we built a services page for GEO and linked the two.<\/p>\n\n\n\n

That\u2019s it. No digital PR push. No paid ads. No topic clusters. Not even Surround Sound SEO<\/a>. <\/p>\n\n\n\n

But the timing turned out to be everything. <\/p>\n\n\n\n

A16Z dropped a piece titled “How Generative Engine Optimization (GEO) Rewrites the Rules of Search<\/em><\/a>“<\/em>. Alright, we\u2019ve got a tailwind! Several clients forwarded me the article (and this stuff doesn\u2019t usually rise to the attention of anyone but SEO nerds like me who spend free time on LinkedIn). The piece reframed an emerging conversation around SEO\u2019s evolution into the generative era.<\/p>\n\n\n\n

And suddenly, our two little pages\u2014the listicle and the services page\u2014were getting tons of traffic.<\/p>\n\n\n\n

We started picking up links. Mentions. Inclusion in other lists we didn\u2019t write, written by companies we do not know. All of this, due to LLMs summarizing and aggregating consensus recommendations across several sources, increased our already high visibility in LLMs. Which, if you follow my logic, should contribute to further mentions on new lists and pages (because people research using these tools), which increases visibility\u2026ad infinitum (hopefully). <\/p>\n\n\n\n

I\u2019m not saying this visibility advantage will always stay, and it likely won\u2019t (there are many, many factors that contribute to organic growth success, not to mention visibility in LLMs<\/a>). <\/p>\n\n\n\n

But it\u2019s what got me thinking about the Matthew Effect and how it so often factors into organic success. <\/p>\n\n\n\n

What Is the Matthew Effect?<\/strong><\/h2>\n\n\n\n

The term originates from the Gospel of Matthew:<\/p>\n\n\n\n

\u201cFor to every one who has will more be given, and he will have abundance; but from him who has not, even what he has will be taken away.\u201d<\/em> \u2014 Matthew 25:29<\/p>\n\n\n\n

Merton borrowed this line<\/a> to describe how, in academia, renowned scientists received disproportionate credit (and funding) compared to lesser-known but equally capable peers. Once you were visible, you attracted more citations, which led to more funding, which led to more visibility, and so on. A flywheel of prestige and progress.<\/p>\n\n\n\n

It\u2019s the compounding nature of advantage. Not merely \u201csuccess begets success,\u201d but systems<\/em> that systematically reward early traction and visibility, making it harder for latecomers to catch up, regardless of merit.<\/p>\n\n\n\n

And when you start to look closely, you see it everywhere<\/em> in marketing.<\/p>\n\n\n\n

The Double Jeopardy Law, Brand Affinity, and the Compounding Curse<\/strong><\/h2>\n\n\n\n

In the 1960s, social scientist William McPhee<\/a> observed the phenomenon that the less popular a TV show or radio program was, the less loyal its audience tended to be. <\/p>\n\n\n\n

Shortly after, marketing scientist Andrew Ehrenberg<\/a> described what he called the Double Jeopardy Law <\/em>as applied to marketing and brand. He found that brands with higher market share didn\u2019t just have more customers. They had more loyal<\/em> customers. And smaller brands didn\u2019t just have fewer buyers. They suffered from less<\/em> loyalty among those buyers.<\/p>\n\n\n\n

So the rich don\u2019t just get richer, they defend their lead with a fortress of familiarity, brand salience, and consumer habit. The poor don\u2019t just stay poor, they lose even their existing footholds as churn and drift sets in.<\/p>\n\n\n\n

In digital marketing, we see this in organic search. A page that ranks #1 gets more traffic, more links, more dwell time and engagement signals. These user and linking signals reinforce its position, building some sense of an organic moat. The feedback loop strengthens. You can write a better page, but breaking in becomes expensive in competitive spaces. <\/p>\n\n\n\n

And now we\u2019re seeing it emerge again in generative search and GEO, though the dust hasn\u2019t nearly settled on how these systems will function and change over time. Currently, however, brand mentions in relation to prompts have a strong correlation with brand visibility. And brand mentions beget citations. Citations beget visibility in AI-generated summaries. Visibility in AI begets more mentions as users copy, link, and expand on AI output.<\/p>\n\n\n\n

Growth Loops, Flywheels, and Why Funnels Are Incomplete<\/strong><\/h2>\n\n\n\n

If the Matthew Effect describes a macro pattern, growth loops<\/em> are the micro-level mechanics that power it.<\/p>\n\n\n\n

A traditional funnel is a linear metaphor: attract, convert, close, delight. But loops are circular and self-reinforcing. As Brian Balfour at Reforge put it<\/a>:<\/p>\n\n\n\n

“Loops are closed systems where the inputs through some process generate more of an output that can be reinvested in the input.”<\/em><\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Let me riff on a few examples I could apply to my own business model (top of the dome here, I’m not saying these are actually explicitly planned growth loops we designed):<\/p>\n\n\n\n