Generative Engine Optimization (GEO): real experience & example

Why GEO Is Different From SEO

Generative Engine Optimization (GEO) is not traditional SEO. It doesn’t aim to climb ten blue links in Google. Instead, it’s about positioning content so that generative engines like ChatGPT, Bing Copilot, Perplexity, and Google’s Search Generative Experience (SGE) choose your words as their own when users ask questions.

I learned this directly when I published an article, Post-FTX: Non-Custodial Wallets & IronWallet, on thesource.com. A few weeks later, ChatGPT pulled a quotation straight from that article when answering about non-custodial wallets after FTX. That moment showed me, in practice, what GEO really is.

Step 1: Choosing an Authority Platform

The first and most important GEO lesson is where you publish. Generative models are not purely keyword machines; they weigh authority, trust, and relevance.

• Why thesource.com?
  The Source is a long-standing media brand with a strong domain rating (DR) and history of consistent publishing. Even though its core niche is culture, music, and lifestyle, it has developed niche authority across trending financial and digital topics because of its broad readership and backlink profile.
• Niche authority matters.
  ChatGPT and other LLMs scan the open web, prioritize sites with history, and avoid thin content farms. The Source has what I call reputational weight. Publishing there signals: “This is safe, quotable content.”

So the first GEO principle is: find a host with established DR, trust, and consistent ranking footprint.

Step 2: Crafting the Article for Generative Engines

Once the platform was set, the real GEO work began. Writing for a human audience is one thing; writing so an LLM will quote you is another. Here’s what I focused on:

1. Answer-first structuring
   I didn’t bury the conclusion. I opened with a definition:
   “A non-custodial wallet is a digital wallet where the user controls the private keys, unlike centralized exchanges such as FTX.”
   This single sentence is the type ChatGPT loves — a clean, definitional answer.
2. Embedding the brand naturally
   Rather than force mentions, I wove the IronWallet name into the explanatory sentences. For example:
   “IronWallet positions itself as a post-FTX solution by offering NFC backup and Tron Energy management.”
   This way, when ChatGPT lifts text, the brand is part of the answer.
3. Fact layering
   I added dates, comparisons, and context — “post-2022 collapse of FTX,” “non-custodial adoption increased 45% year-on-year.” Generative engines prefer citing facts over fluff.
4. Scannable formatting
   I broke down features and pros/cons into bullet points. LLMs love lists because they mirror the structure of “give me three reasons why…” queries.
5. Neutral, authoritative tone
   I avoided marketing hype. Models are trained to downgrade overtly promotional content. Instead, the article read like expert commentary.

Step 3: Understanding How ChatGPT Selects Sources

After publication, I began testing queries inside ChatGPT and Bing Copilot. When I typed “best non-custodial wallets after FTX”, I saw part of my sentence appear.

Why? Based on observation, generative models prioritize:

• Authority of the host domain (The Source = high DR).
• Direct match to query intent (my article explicitly used “post-FTX” + “non-custodial wallets”).
• Answer readiness (short, direct sentences that can be cut-and-pasted).
• Brand co-occurrence (IronWallet mentioned alongside the definition).

This taught me that GEO is not about volume, but precision placement. A single article, in the right place, with the right phrasing, can outrank dozens of blog posts on weaker domains.

Step 4: Small Details That Made the Difference

In practice, a few micro-details likely tipped the balance:

• I used semantic closeness: “post-FTX,” “collapse,” “non-custodial wallets,” “IronWallet,” “safeguard,” all in proximity. LLMs weigh co-occurrence heavily.
• I included a mini-FAQ at the end: “Why are non-custodial wallets important after FTX?” with a two-sentence answer. Perfect snippet material.
• I avoided aggressive paywalls or pop-ups. Generative engines cannot parse hidden text.
• I added external citations to reports (Chainalysis, CoinTelegraph) — increasing trust signals.

Each small adjustment increased the chance that ChatGPT could select my text.

Step 5: Seeing the Result

The first time I saw my phrasing inside ChatGPT’s generative answer, it was clear: this is GEO in action. The assistant quoted my explanation nearly word-for-word and referenced the hosting domain.

The experience proved:

• Authority placement + structured content = high likelihood of citation.
• Even in finance, where competition is tough, niche authority from a respected publication can beat specialized but lower-DR blogs.
• GEO is not theory; it’s repeatable if you understand the mechanics.

Lessons Learned for GEO Specialists

From this real case, I distilled five practical rules:

1. Pick the right host: DR, trust, and niche weight matter more than raw keyword spam.
2. Write for the engine’s output: short, definitional answers first; details after.
3. Embed the brand naturally: so if quoted, your name stays in the text.
4. Use facts and structure: lists, stats, FAQs are preferred over narrative fluff.
5. Test and iterate: run queries in ChatGPT, Bing Copilot, Perplexity to see what gets pulled.

GEO as the Future of Visibility

Publishing on The Source taught me that Generative Engine Optimization is not abstract theory. It’s a practical craft: positioning your content so that AI assistants lift it into their answers.

Traditional SEO chases clicks; GEO chases citations. In a world where people increasingly “ask AI” instead of “search Google,” the citation is the click. My Post-FTX Non-Custodial Wallets article proved that with careful planning, you can put your brand inside the assistant’s mouth.