AEO Playbook · Founder Notes
How I Got Copilot to Cite Digiton 365 Times in 30 Days
Last month, Microsoft Copilot cited digiton.ai 365 times in Bing's own AI Performance data. Here is exactly what I built to make that happen, and how you can do the same for your own site.
The number, and why it is unusual to publish it
Bing's AI Performance data shows Copilot citing digiton.ai 365 times in the last 30 days. Most agencies that talk about AEO or GEO do it in the abstract: best practices, frameworks, predictions. I would rather show the receipt. This is the exact playbook, applied to our own site, with a number I can point to instead of a theory.
Why AEO is a different game from SEO
Classic SEO optimizes for a position in a list of blue links. Answer engines like ChatGPT, Copilot, Perplexity and Google AI Overviews do not show a list, they compose an answer and decide, sentence by sentence, whether to cite a source inside it. That is a different target, and it rewards different things: clarity, structure and machine readability over keyword density and backlink volume alone.
What I actually shipped
- Direct-answer content. Every page that matters opens with a tight, self-contained answer to a real question, in the exact words a person would ask, before any marketing framing. Models extract that first block far more reliably than a page that buries the answer under three paragraphs of introduction.
- Structured schema on every page. FAQ schema, Article schema and Speakable schema, consistently, so an answer engine does not have to guess what a paragraph means, it can read the structure directly.
- An llms.txt manifest. A plain-language file at the root of the site that tells any AI system what Digiton is, what it knows, and where the canonical answers live. It is a small file that does a disproportionate amount of work.
- Fast indexing through Bing and IndexNow. Copilot and ChatGPT's browsing layer both lean heavily on the Bing index, so I ping IndexNow on every publish and submit through Bing directly, instead of waiting weeks for organic crawl.
- A consistent publishing cadence. One burst of content does not build trust. A steady stream of narrow, genuinely useful answers, published regularly, is what turns occasional citations into a recurring pattern.
How I measured it, not guessed at it
I do not rely on a single number in isolation. I ask the major engines the actual questions a prospective client would ask, on a regular schedule, and log whether Digiton gets cited, a competitor gets cited, or nobody does. That log is what tells me which pages are working and which need a rewrite, and it is the same discipline behind the 365-citation figure: it comes from Bing's own AI Performance reporting, not a vanity metric I made up.
Mistakes that quietly kill AEO efforts
The most common mistake I see is treating this as a one-time project instead of an operating discipline. A business publishes ten pages of 'answer content,' checks a box, and stops, then wonders months later why citations never grew. Answer engines reward freshness and consistency the same way they reward structure: a domain that keeps publishing accurate, narrow answers earns more trust over time than one that published a burst and went quiet. The second mistake is writing for search engines instead of for the actual question. A page stuffed with keywords but light on a direct, honest answer gets skipped by a model looking for something it can confidently quote. The fix is almost embarrassingly simple: answer the real question, in the first two sentences, before anything else.
Why this matters even for a small business
AEO is not a game only large brands can win. Because answer engines reward clarity and structure over domain authority alone, a small, technically disciplined business can out-cite a much bigger competitor on a specific question, simply by publishing the clearest, most honestly structured answer. That is the opposite of how classic SEO usually works, where raw domain authority tends to dominate. It is also why I think this channel matters disproportionately for a company the size of Digiton: it rewards the work, not just the budget.
What this means if you are trying to get cited
The businesses that win this channel are not the ones with the biggest content budget, they are the ones willing to structure content for machines as carefully as they structure it for people. That is a genuinely different skill from traditional SEO, and most agencies have not rebuilt their process around it yet. I have, because I run the same playbook on our own domain before I ever recommend it to a client.
Where to start
If you want to know whether ChatGPT, Copilot or Perplexity currently mention your business at all, that is the first thing worth checking, before any content gets written. It is also the first thing I check in an AI SEO engagement. If you want a straight answer on where you stand, get in touch and I will tell you honestly.
Frequently asked questions
How many times does Copilot cite Digiton?
According to Bing's own AI Performance data, Copilot cited digiton.ai 365 times in a 30-day period. That figure comes directly from Bing's reporting, not an internal estimate.
What is the difference between AEO and traditional SEO?
Traditional SEO optimizes for a ranked position in a list of links. AEO, or answer engine optimization, optimizes for being the cited source inside an AI-generated answer, which rewards clear, structured, machine-readable content over keyword density and backlinks alone.
What is an llms.txt file and why does it matter?
An llms.txt file is a plain-language manifest at a website's root that tells AI systems what a business is, what it knows, and where its canonical answers live. It gives answer engines a structured summary instead of forcing them to infer everything from crawled pages.
Related
Ready to put AI to work?
Book a discovery audit and we will map the highest-ROI AI agents and automations for your business.
Book a discovery audit →