Case study
Rank Prompt
Humand
From 0% to 18% AI visibility in a brand new market.
Humand builds HR software for deskless and frontline workers. AI assistants already recommended it in Argentina and had never once named it in the United States. The same weekly system moved both.
Visibility by market, every week
Share of tracked AI answers naming Humand, 15 April to 3 September 2026
Argentina
United States
- 1 English roundup published
- 2 Argentina tracking begins
- 3 Reddit comments live
- 4 Spanish guides live
24% 48%
Argentina AI visibility across 16 weekly reports, measured on six AI engines with prompts that never change. Report by report figures are in the chart above.
First report in that market scored zero
Across 8,106 citations recorded in the window
humand.co, behind only YouTube
Nothing in the set went backwards
A category leader at home, absent from the answers abroad
Humand builds a mobile-first employee experience platform for deskless and frontline workers: the people in warehouses, on shop floors and out in the field who have never had a work laptop. Over 1.5 million of them use it, across 1,500 organisations.
In February 2026 the company raised $66M, with US expansion named as one of the things it was for. Ask an AI assistant in Spanish for an employee experience platform for plant and field staff and Humand came back in about a quarter of the answers. Ask the same question in English, for the US market, and it came back in none of them.
That is a harder problem than a low score. A quarter of the answers is a position to defend. Zero is a category that has already been decided by other people, in public, before the company arrived.
One blended brand score would have reported a respectable number and hidden the whole thing, because it averages a market they lead with a market they were not in.
The US market, all twenty-two reports. Flat on the floor from 15 April until early July, then a climb that has not stopped. The window average of 7% is the cost of the four months it took to get moving.
Their rivals were already writing the category
Before writing anything, every source cited in a tracked answer was pulled and ranked. That was 13,260 URLs across 3,598 domains. Eight of the twelve most cited were rival vendors publishing about their own market, each carrying five hundred citations or more. humand.co sat forty-sixth with 174.
What the answers were actually citing
| Source | Citations |
|---|---|
 YouTube 532 separate videos, none of them dominant | 1,145 |
 Reddit 230 threads, and 171 citations from one of them | 901 |
 Rival vendor blogs eight of the twelve most cited domains | 929 to 502 |
| humand.co forty-sixth | 174 |
Two of the four are not owned by anybody. That is where a company arriving late gets to start.
The number that set the plan
YouTube was the most cited domain in the category, and those 1,145 citations were spread across 532 different videos. The single most cited one was reached 56 times.
Reddit was the opposite shape. Third overall, and one thread carried 171 of its citations on its own. Fragmented and concentrated are both openings, and they need different work.
Four moves, in order
Every one of them came out of the citation data. None was a guess about what might work.
Defined the market before defining the content
Two markets, two prompt sets, two reports, running side by side every week. The prompts were written in the language buyers use in each one, and then they stopped changing, so every week after that is a comparison rather than a fresh measurement.
The categories came from the same place. Four of them, chosen because they were where the deskless workforce question actually gets asked.
Engines tracked
ChatGPT chat + search 
Claude chat + search 
Google AI Mode 
Gemini 
Perplexity Sonar 
Grok Six engines, and ChatGPT and Claude are tracked in both chat and search mode, so a single prompt comes back with eight answers.
Prompt categories
| Signal | Argentina | United States |
|---|---|---|
| First tracked report | 18 May | 15 Apr |
| Visibility at baseline | 24% | 0% |
| Weekly reports since | 16 | 22 |
| Answers scored | 1,920 | 1,760 |
Published the thing the answers were already reaching for
The citation list said models were building the category out of tested, opinionated roundups written by outsiders. So that is what got written, from the inside, with the testing actually done.
Eleven pieces are live across four markets. Two of them carry most of the load.
Published 20 April 2026. Nothing cited it for ten weeks. It now carries more US citations than any other page in the account.
Two pages, 165 citations between them. Both sat at zero for weeks before anything moved, and both then climbed without another edit. The English piece is reached most often by Grok and Perplexity; the Spanish one by Perplexity and Google AI Mode.
- Answer the question in the first two sentences, before any positioning.
- One claim per paragraph, so a model can lift a sentence without lifting a caveat with it.
- FAQ blocks mirrored word for word into FAQPage schema.
- Named frameworks the category did not already have, so there is something specific to cite.
- Customers named, with the published case behind them, instead of a claim about what the product can do.
- Every piece written to a tracked prompt category, never to a content calendar slot.
Commented in the Reddit threads AI actually cites
Reddit was the third most cited domain in the market. Every thread cited anywhere in the account was ranked by citation count, and the top of that list got the work: eight comments, across seven subreddits.
Answer the question first, name the brand once, always include a caveat that costs something. Some of these threads are three years old and still get pulled into answers.
r/internalcomms 36 citations What internal communication tools do you use at your organization?
Three years old and still cited. The comment leads with the failure mode, names Humand once, then hands the question back to the thread.
r/internalcomms Top-cited thread in the set What tools are you using in your Internal Comms role right now?
A stack list, not a recommendation. It ends by admitting measurement is the gap the writer has not solved.
r/internalcomms Cited across four engines Internal comms and intranet trends for 2026
Agrees with an earlier commenter first, then adds the number nobody in the thread had: what share of the workforce actually saw the announcement.
r/internalcomms Follow-up comment Three things that actually worked for us
Ends on a caveat that costs something: it took a quarter to roll out properly. A comment that reads like an advert gets removed, and a removed comment cites nothing.
Let the weekly report pick the next piece
Nothing here ran on a content calendar. Each week's report named the prompts that had moved and the prompts that had not, and the next piece was written against whichever gap was widest.
Over the US window that produced ten prompts up and none down, which is the tell that the work is compounding rather than trading one answer for another.
Ten winners, zero losers. The prompt that moved most is a straight comparison question, which is the one a buyer asks last, right before they shortlist.
The new market opened, and the old one doubled
Neither market was traded for the other. Argentina went from 24% to 48% over the same window the US went from nothing to 18%.
| First | Latest | |
|---|---|---|
| US AI visibility | 0% | 18.0% |
| Argentina AI visibility | 24% | 48.0% |
| US citation share | 0% | 2.8% |
| Argentina citation share | 4.0% | 11.3% |
| Rank among cited domains, Argentina | Unplaced | #2 |
| Answers naming Humand, Argentina | 29 of 120 | 58 of 120 |
Where the movement came from
Change in visibility per engine, over each market's tracked window
Argentina United States
- Perplexity Sonar +32.5% +26.8%
- Google AI Mode +25.8% +9.1%
- ChatGPT Search +10.8% -1.0%
- Claude Search +9.2% -3.4%
- ChatGPT +5.8% -0.6%
- Claude +3.3% +2.7%
- Gemini +3.3% +4.1%
- Grok -6.7% +24.5%
At home, their own site is now the second most cited source in the category
Across 8,106 citations recorded in the Argentina window, humand.co is reached more often than any competitor domain and is beaten only by YouTube. Citation share went from 4% in May to 11.3% at the end of August.
Argentina. 596 citations to humand.co, second only to YouTube's 666, and ahead of every competitor domain in the market.
United States. The same curve, four months behind, off a base of zero. 5,381 citations recorded in the window, 2.8% of them pointing at humand.co.
And in the US, the answers name them
Two Google AI Mode answers, three weeks apart, on two different buyer prompts. Both rank Humand inside a shortlist of platforms that were already there in April, when the company was in none of them.
13 August 2026. "I need an HR management app that supports frontline workers." Google AI Mode splits its answer into dedicated frontline platforms and traditional HR suites, puts Humand second in the first group, and cites humand.co to describe it.
3 September 2026. "Anyone know good HR software that specializes in engaging deskless employees?" A five-name shortlist, and Humand is described by the exact capability the content was written around.
The written half is working. The rest is still open.
Two of the four most cited source types in this category are still doing nothing for Humand.
- 01
Take the video slot
YouTube is the most cited domain in this category on both continents, and no single video owns it. The most cited one in the US pull was reached 56 times out of 1,145. A modest amount of video, aimed at the prompts the written work already wins, would be enough to take a share of that.
- 02
Earn the outside mentions
The roundups and explainers that models lean on are written by people outside the category, and they are already being cited. Getting named in those costs less than anything else on this list, and it is the half of the work a website cannot do for itself.
- 03
Close the schema gap
The FAQPage and Article markup shipped with every piece has not been pasted into the live pages. The pages are ranking without it. They would be quoted more cleanly with it.
- 04
Run the pattern into Mexico and Colombia
Both markets are tracked and both open near zero, which is exactly where the US sat in April. The queue is already built against their prompts.
Why this worked. Tracking each market separately, every week, on prompts that never change is what made the zero visible at all. One blended score would have averaged it away. Ranking every cited source before writing a word is what turned that zero into four specific jobs rather than an instruction to publish more. A new market does not need more content than the old one. It needs the right four things, in order, and four months of patience while nothing appears to happen.
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