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Case Study REMAX · Michigan

How Ben Lang Beat His Competitors To Be  #1 in AI Search

"When I do something, I want to dominate. I don’t want to do it halfway." Watch how Ben Lang made this happen with AI search.

$890K Transaction Value
$55K Estimated GCI
30 Days First Inbound Lead
5 AI-Sourced Calls

In her words — from “SEO never worked” to the top of her market. Get results like Ben’s

The full story

From invisible to inevitable

Ben Lang knew AI search mattered—but needed a way to win it. That's why he partnered with FlyDragon.

  1. The Challenge

    SEO had never paid off for Ben Lang in the past

    Ben has always kept up with changes in real estate marketing, SEO, and technology. He knew prospective clients were increasingly researching agents before they ever picked up the phone, but he did not want to spend his time trying to become an AI-search expert himself.

    For Ben, the stakes were especially clear in a market full of analytical, research-heavy clients. His ideal clients want data, independent validation, and confidence before they agree to meet. Traditional lead sources were no longer delivering the same quality of opportunities.

    He tested the landscape himself, asking Claude, Perplexity, ChatGPT, Manus, and Gemini how to build a dominant AI presence as a real estate agent. The same answer kept appearing: FlyDragon.

    “They like to do all their research on their own. They don’t want to be sold. They want to know all the data prior to the meeting.”
  2. The Solution

    A strategy built around trust and authority.

    Ben partnered with FlyDragon to make sure he appeared when prospective buyers and sellers asked AI platforms who the most trusted agent in his market was. Rather than chasing vague promises, Ben valued FlyDragon’s measured approach and clear communication. The team set realistic expectations of three to four months—then began delivering visible results far sooner.

    • Built visibility around high-intent “best agent” searches
    • Positioned Ben as a trusted answer across multiple AI platforms
    • Strengthened the proof points research-heavy clients use to vet an agent before they call
    • Supported the journey from referral or search to a confident listing conversation
  3. The Results

    AI started sending Ben ready-to-list sellers.

    Within roughly 30 days, Ben received his first inbound text from a retired engineer who had already researched him and was ready to list an $850K home. That listing received 11 offers and was double-ended $40K over asking—an approximately $890K transaction and an estimated $53.4K in GCI before brokerage splits.

    In the first 90 days, Ben estimates he received four to five high-intent calls and texts from people who found and vetted him through AI search. One of those opportunities was already moving toward another condo listing.

    “Love inbound. Inbound business is the best… I don’t think it gets any better than that.” — Ben Lang