Creating ‘Non-Commodity’ Content That Cuts Through the Noise: the Practical Angle

Most of the advice we get about "quality content" these days feels like it was written by a committee that has never actually published a word of their own. We see definitions of what makes content "good" or "unique" that are so vague they become useless. When the guidelines are this thin, it's easy to fall into the trap of producing content that looks right on a checklist but feels empty to a human reader.

This matters because we are currently witnessing a fundamental shift in how information is consumed. If your content is just a polished version of what already exists, you aren't providing value—you're providing a commodity. And in a world of generative AI, commodities are the first things to be automated away.

The Reality of the Commodity Trap

To put it bluntly: if you are producing content solely for the sake of SEO without adding a unique perspective, you are wasting your budget. Commodity content is essentially "safe" content—it follows the top ten search results, hits all the expected keywords, and says exactly what everyone else is saying.

There are two primary reasons why this approach is now a failing strategy. First, because this content is so predictable, it is incredibly easy for AI to summarize. When an answer engine can synthesize ten identical articles into one perfect paragraph, the user has no reason to click through to your site. Second, in a "zero-click" environment, the traditional monetization models for commodity content are collapsing. If the user gets the answer on the search page, your ad impressions and lead captures vanish.

The goal now is to move beyond being "just an SEO." The role is shifting toward helping broader business teams—editorial, social, and product—structure their workflows to extract maximum value from every channel. This involves using demand analysis to figure out not just what people are searching for, but why they are searching for it right now.

Expert Interpretation: The trade-off here is between efficiency and impact. Commodity content is efficient to produce (especially with AI), but its impact is nearing zero. The decision you need to inspect is your current content pipeline: are you measuring success by the number of articles published, or by the unique value added to the existing web corpus?

Why Generic Content Is No Longer Viable

Human behavior is governed by the path of least resistance. We don't want to hunt for an answer; we want the answer delivered to us as effortlessly as possible. This is why AI-generated summaries are so disruptive. If a user can get a "good enough" answer without leaving the search results, they will.

Commodity content has been the foundation of "evergreen" strategies for a decade, but that foundation is crumbling because it is too easy to synthesize. Google has explicitly signaled that the path to success in an AI-driven search experience is to create non-commodity content—material that is genuinely helpful and satisfying because it offers something the AI cannot simply aggregate from other sources.

Before you hit publish on any piece of content, I suggest asking two questions: 1. Does this add something unique to the existing body of information? 2. Does it provide a perspective or data point that isn't already common knowledge? If the answer to both is "no," the content belongs in the bin. You simply cannot afford to spend resources on material that doesn't move the needle.

The Evolving Role of Search Volume

There is a common misconception that because AI is changing search, metrics like search volume are now useless. That isn't true, but the way we use them must change. Looking at a single keyword's volume to decide what to write is a legacy mindset that no longer generates significant value.

Instead, view search volume as a signal of demand. When you analyze monthly trends, you can identify the "when" and "why" of user interest. For example, if you see a consistent spike in searches for "family holidays" every January, that isn't just a keyword target—it's a behavioral pattern. People are planning their year during the coldest part of the winter.

The value now lies in coordination. Instead of working in an SEO silo, this data should be shared with social media and editorial teams so the entire organization can align its output with actual human demand. It's no longer about a simple "create X to get Y" transaction; it's about strategic timing and integrated distribution.

Expert Interpretation: The risk here is treating search volume as a mandate rather than a hint. The trade-off is between chasing high-volume "head terms" (which are almost always commodity topics) and targeting high-intent demand windows. Inspect whether your content calendar is driven by a keyword tool or by actual user behavior patterns.

Turning the Commodity into the Unique

It is possible to take a topic that is inherently "commodity"—like "how to do evergreen content"—and turn it into something non-commodity. However, this requires more than just better writing. It requires a combination of deep expertise, lived experience, and a platform to amplify that voice.

You cannot "optimize" your way into uniqueness. You have to be unique. This means bringing a level of understanding to the topic that elevates it above the standard discourse. It requires the courage to disagree with the consensus or the ability to provide a nuanced take that only someone who has actually done the work would know.

The Pillars of Non-Commodity Content

If we want to build content that survives the AI shift, we have to focus on a few non-negotiable pillars.

The Power of Uniqueness

Uniqueness is the only real moat left. Without it, you have no genuine E-E-A-T, and you won't earn the kind of high-quality links or social shares that actually drive growth. One of the most effective ways to achieve this is through proprietary data.

When you have access to high-quality data sources—such as site-level or app-level engagement data from tools like Similarweb—you can create your own metrics. For instance, instead of reporting on generic bounce rates, you could create a composite engagement score by combining pages per session, session duration, and bounce rate. This transforms a commodity report into a proprietary insight that no one else can replicate.

Understanding Information Gain

It is worth noting that Google isn't just guessing about uniqueness; they have attempted to quantify it. A Google patent (US20200349181A1) regarding the "Contextual estimation of link information gain" suggests that the search engine may score documents based on the added value they provide compared to other documents on the same topic.

While patents aren't always a direct map of current algorithms, the logic is sound: if a document provides "information gain"—meaning it tells the user something new that they haven't already encountered in the top three results—it is more valuable than a document that merely repeats the same points.

Designing for Human Purpose

For too long, SEO content was designed for a search engine, not a person. It was designed to make money, not to educate or entertain. As audiences move away from generic "content farm" style articles, the purpose of the piece becomes paramount.

Non-commodity content must have a human purpose. Whether it is to genuinely educate the reader or provide entertainment, it must offer something that a summary cannot. Content that exists only to capture a keyword is a commodity; content that exists to solve a problem in a new way is an asset.

Expert Interpretation: The trade-off here is between "safe" content that follows the SERPs and "bold" content that takes a stand. The decision to inspect is: are you writing to satisfy an algorithm's expectation of what the topic should cover, or are you writing to provide a breakthrough for the reader?

The Reality of E-E-A-T and Entities

E-E-A-T (Experience, Expertise, Authoritativeness, and Trustworthiness) is often treated as a checklist, but in reality, it's about entity recognition. Google tracks authorship and entities through its Knowledge Graph. The goal is "disambiguation"—removing the ambiguity of who the author is and what they actually know.

However, simply having an expert write a piece isn't enough. The expertise must be showcased in a way that adds tangible value. The most successful strategy is to help your experts build a platform of their own. When an expert's content is shared and recognized across the industry, it reduces the business's total reliance on search engines.

If you have a legitimate expert who can structure their knowledge into non-commodity content, you have a massive competitive advantage. Commodity content is doomed because people don't care about it; non-commodity content thrives because it is tied to a real person with real authority.

Measuring True Engagement

If you are still measuring success primarily through page views or clicks, you are using a dying metric. In a zero-click world, we need to track whether people actually care about what we are creating.

I believe that links should be a byproduct of creating something brilliant, not the primary goal. While the market for buying links still exists because they drive rankings, the most sustainable growth comes from "earning" them by doing interesting work.

To measure this, you need to look at quality engagement both on and off-site. Off-site, this means tracking metrics that indicate genuine interest—shares, mentions, and discussions—rather than just raw traffic. I recommend creating composite metrics that guide creators toward quality rather than quantity. Stop chasing page views and start chasing "value signals."

The Importance of Content Structure

Finally, we have to talk about structure. It isn't the most exciting part of the process, but it is critical for both humans and LLMs. There is a documented phenomenon known as the "lost in the middle" effect, where large language models are more likely to reference information found at the very beginning or the very end of a document, often missing the nuance in the middle.

While some might be tempted to "game" this by repeating keywords throughout the text, that makes the content unreadable for humans. The solution is proper, logical structure. A well-structured argument helps the human reader follow the logic and helps the AI accurately cite the most important points without losing the context.

Introduction

The key issue here is Google's recent definition of commodity vs. non-commodity content is a bit meh. Meh if I'm being kind. Downright useless if I'm being more reasonable. Complete and utter rubbish if I've had a drink. They all read like headlines you'd see in Discover and... My read is to treat it as a decision point: what signal needs to become clearer, what part of the system is currently weak, and what evidence would show that the work is improving visibility rather than only adding activity.

That is the difference between reacting to a trend and building a useful search system. Connect this point back to the page template, internal linking, entity signals, content depth, crawl accessibility, and the way the brand is represented across the wider web before deciding what to change first.

Practical next steps

The useful part is not only the idea itself, but the operating habit behind it. Use it as a checklist for decisions: what deserves attention now, what should be monitored, what needs a stronger evidence base, and what can wait until the system has more scale.