---
title: "How to Create Search Demand for a Phrase Nobody Knows - Carlos Arias"
description: "Can you create search demand for a phrase nobody knows? Ranking is trivial. Demand takes off-search seeding, and here is the method, plus a dated live log."
url: "https://carlosarias.com/blog/guides/create-search-demand-phrase-nobody-knows"
---

# How to Create Search Demand for a Phrase Nobody Knows

Can you create search demand for a phrase nobody knows? Ranking is trivial. Demand takes off-search seeding, and here is the method, plus a dated live log.

  [Carlos Arias](/blog/authors/carlos-arias) · September 7, 2026  · 11 min read

![An ink-brush rabbit sits looking up at a swirling cluster of curls and dots, with a red seal below.](/_astro/cover.Dl_fNBrX_1wWhSj.webp)

*An ink-brush rabbit sits looking up at a swirling cluster of curls and dots, with a red seal below. AI-generated illustration by Carlos Arias .*

      Sumi-e ink illustration for an editorial article titled "Honey Honey Sweet Bunny: Can You Make a Phrase Go Viral in Google and AI Search?". A single restrained conceptual image brushed in black sumi ink on warm off-white washi paper (#F6F5F2) — visible paper grain, generous negative space, asymmetric off-centre composition, calm and minimal. Wabi-sabi: natural, imperfect, hand-brushed strokes with dry-brush texture and soft bleed; matte and desaturated, no gloss, no glow, no cinematic lighting, no gradients. One small vermillion-red seal mark (#D0342C) is the only saturated colour, placed deliberately like a hanko stamp. No text, no words, no letters, no logos, no UI labels.  Prompt sent to Higgsfield · nano_banana_pro · 3:2

Can you create search demand for a phrase nobody knows? I invented one to find out. The phrase is Honey Honey Sweet Bunny, the title of a song I wrote, and this page is the lab notebook.

## The short answer, on day one

Yes, in the narrow sense a search engine cares about. No, in the sense that pays.

Ranking for an invented string is close to trivial. No rival document exists, so the first properly crawled page carrying the exact words takes the result by default.

Demand does not bend to markup. It bends to exposure, and exposure happens somewhere other than the search box. Nobody types a phrase they have never heard. Volume sits at a true zero until something outside the index puts those words in front of a human being, which is a job with known mechanics rather than a mystery, and I have written the whole of that job out below before I have a single data point that would justify it.

Attribution lives between the two. It is the only half worth engineering.

That last part is a prediction, not a finding. I am writing it down on 8 September 2026, with zero data behind it, so it cannot be quietly revised later. The log will confirm it or wreck it. The seeding tactics are a different kind of claim, older and better evidenced than anything I am going to observe here, which is why they go in now instead of waiting on my results. That second half is where almost everyone quits, then reports the first half as a win.

## The method, if you want to run it yourself

You do not need my results to start, and you do not need the phrase to be any good either. The whole procedure, in order:

1. Start with a real work, not a keyword. The phrase has to be attached to something a person might plausibly want. Mine is a song with lyrics and audio.
2. Record the baseline before anything ships. Exact match in quotation marks. Then the phrase plus “song”, plus “lyrics”, plus “poem”, plus “who wrote”, plus “what is”. Save the raw text and a screenshot, and stamp both with the date.
3. Publish one canonical page, alone. No second format, no sharing, no cross-posting. You are watching discovery and indexing with nothing else pushing on them.
4. Put authorship in markup, not only in prose. Use the specific creator fields your Schema.org type offers rather than one vague author field.
5. Submit for indexing, then ignore the submission. Log the crawl. Never log the request as a result.
6. Add one format at a time, each with its live date. Audio first. Video weeks later.
7. Separate live retrieval from model memory in the log. A cited page proves it is retrievable. It proves nothing about weights.
8. Seed the phrase to humans away from search, and log the exposure before you look at any dashboard. Who heard it, how many, and whether they could have clicked instead of typed.

Step 7 is the one people skip, which is why so many write-ups end up unfalsifiable. Step 8 is the one they never attempt at all, which is why the write-ups have no demand in them to measure.

## The old version of this experiment

Around 2001, give or take a year, I spent afternoons doing something that felt slightly illicit. I would invent words that meant nothing, then watch what the search engines did with them once the page went live. Would a crawler find the word? Would it index it? Would my page be the one thing that came back when someone typed it? It was the cheapest laboratory a teenager could build.

I kept no logs. That machine and its dial-up connection are long gone, I cannot produce a screenshot of any of it, and memory is a lossy format that flatters the person doing the remembering. So take the story as motivation rather than evidence. Everything in this article that carries weight is dated below and checkable.

Twenty-five years later the search box has company. Language models answer questions directly now, often without a click, and “search demand” means something more tangled than a number in a keyword tool. So I am running the old experiment again, on one deliberately obscure phrase, this time with the receipts.

## The phrase, and the thing it is attached to

Honey Honey Sweet Bunny is the title of an original song I wrote and published. It lives here: the song and lyrics. That page is a creative work and stays one. This page gets edited as observations come in, and the edits are dated.

## Can you create search demand if nobody knows the phrase?

The full version of the question: can an original phrase with almost no established search history become discoverable and reliably attributed to a specific source, across both search engines and AI systems?

### The easy half

Ranking. The page takes the result the moment a crawler notices it, because nothing else is competing for those four words in that order. That win proves almost nothing about whether a human being ever wanted them.

### The hard half

Demand and attribution. Getting a human being to type the phrase at all. Then getting the systems that answer questions to point back at the right source when they do.

## How you actually manufacture the demand

Ranking took a page. Demand takes people. This is the part of the method that does not depend on how my experiment turns out, because the mechanics were established long before I picked a rabbit, so it goes in the article on day one rather than arriving later as a footnote in the log.

### A search is a gap plus a string

Somebody types a phrase when two conditions hold at the same moment. The words are in their head. The answer is not. Remove either condition and the query never happens, which is why the most common way to kill your own search demand is to be generous with links.

Consider the accident that proved it at scale. Just after midnight on 31 May 2017 a sitting US president tweeted the fragment “Despite the constant negative press covfefe” and left it up for roughly six hours. The string had no measurable Google activity before that night and was the top trending hashtag in the world by morning, retweeted more than 127,000 times. Nothing about the word was good. It was six letters of nonsense with no meaning to discover. What produced the searches was the gap: millions of people had seen a string they could not resolve, and the tweet offered them nothing to click on that would resolve it.

Advertising has run the same play deliberately for sixty years. A Super Bowl spot puts a name in front of a hundred million people with no clickable surface anywhere in the room, which is exactly why 82% of TV-ad-driven searches during the game happen on mobile, on the second screen in the viewer’s hand. The gap gets opened on the first screen on purpose. The phone is where it closes.

I do not have a hundred million people. The mechanic scales down anyway.

### Seeding it to humans, off search

Each of these puts four words in a human head with no link attached to them. That constraint is the whole point, and it is what separates seeding from promotion:

- Say it out loud in rooms. Open mics, house shows, dive bars where half the room is not listening, the ninety seconds between songs when it goes quiet. The title gets said whole at the start and again at the end. No QR code, nothing to photograph.
- Print it on objects that cannot hyperlink. Stickers, or a card carrying four words and no URL anywhere on it. A hundred die-cut stickers cost roughly what one month of a keyword tool costs.
- Get it spoken on audio. Podcast guest spots and community radio are unlinkable by their nature. A listener with headphones on and hands full either remembers the phrase or loses it, and the ones who remember arrive at the search box a few hours later, which is the cleanest signal in this entire experiment.
- Release the music where the web index cannot follow. Spotify and Bandcamp sit outside the crawlable web for most practical purposes. Someone who hears the track in a playlist and wants the lyrics has to leave the app and type.
- Use text surfaces that strip or discourage links. A plain-text email with no anchor tag. A comment in a forum where self-linking gets you removed. The phrase travels; the URL does not.

One tactic I am ruling out, in writing, before the temptation arrives. Asking friends to go and search the phrase produces query volume that looks identical to demand in every dashboard I own. If I ever do it, the log records it as a seeded query with the count and date. It is not demand. It is me typing through someone else’s hands.

### Make the phrase survive the trip to the keyboard

Between the ear and the keyboard a phrase sheds pieces. Spelling goes first. Word order follows it, and the back half of a long title has usually evaporated by the time somebody sits down with a browser open.

Mine has a known collision sitting right at the front of it. ABBA released “Honey, Honey” in 1974, and fifty-two years of chart history own those two words in every autocomplete on earth. So the title only ever gets said whole and never shortened, and the identifying work falls on the words after the collision. That is also the argument for four common words a seven-year-old could spell. I would like to claim I planned it. I picked them because they sounded right in the chorus, and the spellability was luck, but it is the first property I would insist on if I ever chose a phrase deliberately.

### Proving a seed worked, rather than assuming it

Log the exposure event before you go anywhere near a dashboard. Date, rough audience size, whether a link was reachable in that moment, and what else went out that week. Then watch Search Console impressions for the exact phrase over the following 72 hours, not clicks. An impression is evidence that somebody typed the words. A click only tells me my title tag was appealing once they had already done the hard part.

Two cautions on that measurement, both of which have burned people into publishing nonsense. Google omits rare queries from the query table to protect user privacy, so five real searches can show up as an empty report while still counting in the totals, and a missing row is not a zero. Second, an impression from a seeded room and an impression from a stranger are indistinguishable in the interface, which is the entire reason the exposure log gets written first and timestamped.

## Where it stands right now

Last updated 8 September 2026, the day this page went live. Everything below is something I checked myself, and nothing here is projected forward. Ranking: settled. Demand sits at zero, which is exactly what day one should look like. Nobody has claimed attribution yet, including me.

### The baseline reading

Before anything shipped I recorded what a set of search engines and several AI systems returned for the exact phrase and its close variants:

- The phrase in quotation marks.
- The phrase plus “song”, then plus “lyrics”, then plus “poem”, then plus “meaning”.
- “Who wrote Honey Honey Sweet Bunny”.
- “What is Honey Honey Sweet Bunny”.

Nothing came back that referred to Honey Honey Sweet Bunny as a specific work.

Now the honest problem with that sentence. I took the readings on 7 September 2026 and saved full-page screenshots and raw text, every file stamped with that date, and they are sitting unpublished in a folder on my own machine. A private screenshot is just my word with a timestamp on it. Weigh it that way. The piece you can check without trusting me is this page, which goes to the Wayback Machine on publication day and freezes the claim at a date I am not able to edit afterwards; if you want the folder, write and I will send it. None of it is proof the four words have never appeared anywhere on the internet, which is a far weaker statement than it sounds like it should be. If an earlier use turns up, it goes into this log accurately rather than quietly disappearing.

### What the assistants said before publication

Asked cold, in fresh conversations with no prior context, the assistants I tested did one of two things. They said they had no record of the phrase, or they guessed at a nursery rhyme from the shape of the words. None named a source. That was a handful of conversations on a single afternoon, transcripts saved with the rest, and the sample is far too small to call a survey. Call it a reading rather than a result.

### The instrument that does not work

Google Trends only publishes data above an undisclosed minimum volume, so low-volume terms show up as zero. A flat zero line is not a measurement of nothing. It is the absence of a measurement. Treating those as the same thing is how people talk themselves into a fake baseline and then build a case study on top of it.

## Seven things I refuse to collapse into one

Most “I made a keyword rank” write-ups fail because they blur these together. I am keeping them separate:

- Discovery by a crawler.
- Indexing of the page.
- Ranking for the exact phrase and close variants.
- Real demand and traffic, which is an entirely different thing.
- AI retrieval and correct attribution.
- Engagement and sharing.
- The effect of adding formats, such as the music itself or a video.

Two traps I am not going to fall into. Ranking first for a phrase nobody searches is not demand; it is an empty room with my name on the door. And an AI system citing this page once is not evidence that a model has learned the phrase, because it may simply be fetching the page live, which vanishes the moment the page does.

## Running the method here

### The sequence

The temptation is to push everything at once. Do that and you learn nothing about which signal did the work.

So the song page goes first, alone, while I watch discovery and indexing with nothing else pushing on it. Then signals get introduced deliberately, one at a time. Distribution of the music first. A video after that, then the off-search seeding described above, each exposure logged with the date it happened and each format logged with the date it went live.

### What counts as a hint, not a result

Requesting indexing in Search Console is a hint rather than a command. Google states plainly that submitting a request does not guarantee the page will be indexed. The same caveat applies to IndexNow, which tells Bing and other participating engines that a URL changed without promising anything about crawling or indexing. Both are worth doing. Neither is a result.

### Making authorship machine-readable

The song page carries MusicComposition markup with the lyrics inline and the audio declared as an AudioObject. Credits are split into lyricist and composer rather than one vague author field. Attribution is the dependent variable here, so stating it unambiguously is the cheapest honest move available to anyone publishing an original work.

## Testing the AI systems

In fresh conversations, with no prior context, I ask about the phrase and record exactly what comes back, word for word, hedges included. Do they find the song? Do they name the right creator, or cite the page the words came from? Some will invent an origin rather than admit a gap. That failure mode gets logged as carefully as a success.

### Retrieval is not memory

Live retrieval and built-in knowledge get logged separately, because only one of them survives the page going offline. The vendors themselves draw this line. OpenAI documents separate user agents for model training (GPTBot) and for its search index (OAI-SearchBot), with a third for user-triggered fetches (ChatGPT-User), and a site owner can allow one while blocking another. A citation from the search index tells you a page is retrievable. It tells you nothing about what a future model weight contains.

### Why attribution outranks ranking

Pew Research Center tracked 68,879 real Google searches from 900 US adults in March 2025. Users clicked a traditional result on 8% of searches with an AI summary present, against 15% without one. Clicks on links inside the summary itself: 1%. Google disputed the methodology as unrepresentative of Search traffic, which is a fair objection to register and not a reason to ignore the direction of travel. When the answer arrives without a visit, being named correctly is most of what you get.

## The rules I am holding myself to

A dated log of observations I have actually verified. No invented rankings, no invented traffic, no invented citations, nothing backfilled to look smarter than the data. If Google never shows an AI Overview for this phrase, that is not a failure; for a simple lyrics query, a plain link to the source is a perfectly good answer.

## Why this is an engineering problem

The interesting part was never the bunny. It is the method: a hypothesis, a controlled change, then honest measurement of what actually moved.

That is the same way I work on a law firm’s growth system. Learn how the practice really makes money before touching anything. Change one variable. Measure the thing that moved rather than the thing you hoped would move.

It is also why I am blunt about vendors who report activity as outcome. I have written before about why most SEO retainers are built for volume instead of depth, and about what it takes to be in front of a query cluster while it is still forming. For the adjacent argument about what search engines and AI systems really do with published content, I made it here: the reality of SEO and AI content.

I will update this page as data comes in, including the parts that make the hypothesis look wrong. My answer stands until the log overturns it. Watch the attribution half. If you would rather meet the thing the experiment is about, the song is right here. If you are a law-firm principal and this is how you would rather have your marketing measured, write me at hi@carlosarias.com.

    Tags [#seo](/tags/seo)[#ai-search](/tags/ai-search)[#search-experiments](/tags/search-experiments)[#digital-marketing](/tags/digital-marketing)   Share        Written by [Carlos Arias](/blog/authors/carlos-arias)

Marketing Engineer for law firms. I combine digital marketing, software, data, automation and AI to improve the whole system — from first click to signed case.

         On this page

- The short answer, on day one
- The method, if you want to run it yourself
- The old version of this experiment
- The phrase, and the thing it is attached to
- Can you create search demand if nobody knows the phrase?
- The easy half
- The hard half
- How you actually manufacture the demand
- A search is a gap plus a string
- Seeding it to humans, off search
- Make the phrase survive the trip to the keyboard
- Proving a seed worked, rather than assuming it
- Where it stands right now
- The baseline reading
- What the assistants said before publication
- The instrument that does not work
- Seven things I refuse to collapse into one
- Running the method here
- The sequence
- What counts as a hint, not a result
- Making authorship machine-readable
- Testing the AI systems
- Retrieval is not memory
- Why attribution outranks ranking
- The rules I am holding myself to
- Why this is an engineering problem

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