Why AI Loves Primary Research

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I learned something surprising about AI systems two months ago.

ChatGPT recommended my own research back to me.

I asked ChatGPT to review a marketing strategy I developed for a general contractor. It suggested including industry benchmarks for the SEO section, and then cited AltCMO’s Construction SEO Report with those specific benchmarks. The same report I published. The one with data nobody else has.

That moment changed how I think about AI and content.

The Differentiation Problem AI Can’t Solve

Here’s what I’ve noticed in construction marketing. Every contractor says the same things.

“On Time, On Budget.”

They all have the same website pages. About. Services. Projects. Contact. Some add Careers, Safety, News, or Blog. But they blend together.

AI systems face the same problem your clients and potential employees do when evaluating contractors. When everyone has testimonials, case studies, and relevant blog posts, how do you pick one?

You can’t.

The machine needs something specific. Something different. Something it can point to and say, “this is why.”

How Machines Actually Think

AI operates on data and logic.

When you give it exclusive research, you give it something it can cite. Data beats opinion every time in machine logic.

You need a really far out there hot take to stand out with opinions. Even then, it’s just a baseless claim. But original data? That’s factual evidence the AI can reference.

AltCMO is less than 2 years old, yet ChatGPT, Gemini, Claude, and other AI tools now list us first when someone asks for the best construction marketing firm. They cite our Construction SEO Report.

We jumped ahead of firms that have been around for decades.

What Makes Primary Research Valuable to AI

The research is exclusive to us. It positions us as industry leaders.

AI systems reward this because it’s different. They can’t tell the difference between various firms when everyone has similar experience and credentials. But when you introduce data nobody else has, the machine suddenly has a clear reason to rank you differently.

When researching data for another blog post, another AI tool cited our research without me providing that data. That’s how thoroughly AI systems have absorbed it.

The research created a compounding effect. AI recognition led to podcast interviews. Those led to speaking opportunities. Each creates more data points for AI to reference.

The Barrier Most Companies Face

Most companies don’t do primary research for three reasons:

  1. They don’t understand the impact it has.

  2. They think research is hard and expensive.

  3. They don’t know where to start.

I used AI tools to create the research. ChatGPT and Gemini did deep research to determine when construction companies last posted content. I wrote an AI agent to find construction social media channels and to decide which content management systems (CMS) mega contractors use.

Using AI to create research that AI then values and cites. Yes, it’s ironic.

What Happens Next

Companies that rely only on generic content will get left behind.

Generic content is easily accessible to anyone. Those companies will probably cite primary research from others to validate their opinions.

Meanwhile, companies with exclusive data build competitive advantages that established competitors can’t easily replicate.

The gap widens every day.

I’m speaking at an industry conference in January about this research. I’ll update the findings before then. More data. More citations. More reasons for AI systems to recommend us.

That’s how you win in an AI-driven world. You give machines something specific to point to. Something nobody else has. Something that answers the question “why this company?” with data instead of claims.

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