Small business=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.
0%from 0% in September 2026
Inside the floor by 13 pointsRank 69 → 88 of 89
3 categories · Ranked42Judge labels
0First choices
37Negative labels
13 / 14Models named it
3Categories
October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10.7, every buyer segment counted.
Best standing
0% in Frontline employee apps for mid-market buyers
Rank 106 of 106 in the mid-market standingcriticized challenger
0 of 14 models made it the first choice on the direct prompt; 83% of its 12 labels there were negative.
What the models named instead of WhatsApp →By buyer segmentRead the same way at every buyer size.
Small business89 of 90
0%13 labels
criticized challenger
Mid-market106 of 106
0%12 labels
criticized challenger
Enterprise91 of 91
0%10 labels
criticized challenger
In frontline employee apps · each standing computed within its segment · bars are 0 to 100 · the accent bar is the product's own best reading
Standing by category
Every category where a model named WhatsApp for a mid-market B2B company. Share is first choices across the direct, paraphrase, budget and scale prompts; rank is within every product named in that category.
| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| Frontline employee apps | Onboarding and employee experience | 0% | 106 of 106 | 83% | 12 | criticized challenger | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. |
| Job advertising and distribution | Talent acquisition | 0% | 100 of 111 | 100% | 1 | under 10 labels · led by JobTarget at 23% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. |
| Whistleblowing and investigations | Core HR and payroll | 0% | 101 of 107 | 100% | 1 | under 10 labels · led by FaceUp at 25% |
Movement
Since September 2026, WhatsApp held within the floor in all three categories: no change cleared 13 points.
Best category · Frontline employee apps · by segment
Mid-market=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.
0%from 0% in September 2026
Inside the floor by 13 pointsRank 95 → 100 of 100
Enterprise=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.
0%from 0% in September 2026
Inside the floor by 13 pointsRank 99 → 82 of 82
All categories · Mid-market
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| Frontline employee apps | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 95 → 106 of 106 |
| Job advertising | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 84 → 100 of 111 |
| Whistleblowing | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 101 of 107, unchanged |
Shares here are read over the models both editions asked, so they can differ by a point or two from the standing above, which counts every model in this edition.
The floor is 13 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one is noise, and both are shown. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. How the floor is measured · The editions
By model
How each model treated WhatsApp across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.ShowHide
By model
How each model treated WhatsApp across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.
ShowHide| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 0 | 0 | 0 | 1 | 1 |
| GPT-5.4 mini | 0 | 0 | 0 | 0 | 0 |
| Gemini 3.5 Flash | 0 | 0 | 0 | 1 | 1 |
| Perplexity Sonar | 0 | 0 | 0 | 2 | 2 |
| Grok 4.1 Fast | 0 | 0 | 0 | 1 | 1 |
| Mistral Small | 0 | 0 | 0 | 1 | 1 |
| DeepSeek V4 Flash | 0 | 0 | 0 | 0 | 0 |
| Llama 4 Maverick | 0 | 0 | 0 | 1 | 1 |
| Qwen 3.7 Flash | 0 | 0 | 0 | 1 | 1 |
| Kimi K2 | 0 | 0 | 0 | 1 | 1 |
| GLM 4.7 FlashX | 0 | 0 | 0 | 1 | 1 |
| MiniMax M2.5 | 0 | 0 | 1 | 1 | 2 |
| GPT-6 Luna | 0 | 0 | 0 | 0 | 0 |
| Muse Glimmer 30B | 0 | 0 | 1 | 1 | 2 |
By framing
Which of the six questions produced the naming. By model says how often; this says asked what. The first-choice count on the right carries the marks of the models that produced it.
FramingLabels by classFirst choices
Direct1 labelNone
Paraphrase0 labelsNone
Comparative0 labelsNone
Budget-constrained3 labelsNone
Scale-constrained1 labelNone
Negative37 labelsNone
First choiceAlternativeMentionNegative42 labels in all, every segment counted; 0 of the 0 first choices count toward share, since the comparative and negative framings do not. The bar is one segment per label class, to scale within the framing.
What the models said for it
Verbatim evidence the judge attached to positive labels.
No positive label carried a quote.
And against it
Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.
“Generic communication apps used as reporting channels, such as WhatsApp... flag them as invasive or unsuitable for anonymous disclosure workflows” Perplexity Sonar · Whistleblowing · negative prompt · hard negative
“scammers use platforms like Facebook, Instagram, TikTok, WhatsApp, and Telegram to promote fake opportunities” Claude Haiku 4.5 · Job advertising · negative prompt · hard negative
“main apps to avoid or be cautious about for frontline work are consumer messaging apps like WhatsApp” Perplexity Sonar · Frontline employee apps · negative prompt · hard negative
“Apps to Avoid/Cautious Of: WhatsApp, iMessage, Facebook Messenger, SMS (Standard Texting), Telegram.” Qwen 3.7 Flash · Frontline employee apps · negative prompt · hard negative
Named alongside
The products named in the same answers as WhatsApp, over the 42 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and WhatsApp was named but was not.ShowHide
Named alongside
The products named in the same answers as WhatsApp, over the 42 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and WhatsApp was named but was not.
ShowHideProductSame answerTook the first choice insteadHead to head
A head-to-head page exists where both products are among a category's top eight. The other rows are the same fact without a page behind them, so they link to the product instead.
What carried it into the answer
The sites and pages cited by the answers that named WhatsApp. A fact about retrieval, not a lever on the model.
Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 42 of the 42 answers that named WhatsApp and are not a share of its labels.
Domains cited
hr-ai-index.com24
mangoapps.com22
joinblink.com18
getflip.com15
pebb.io12
staffbase.com12
getzelos.com11
redeapp.com11
speakap.com9
firsthr.app8
142 of the 142 domain citations in answers naming WhatsApp came from somebody else's page.
Pages cited
Pages are listed as the models cited them.
Search and answers
whatsapp.com is not in Google's top ten for any of the category's searches. In the answers, WhatsApp takes 0% of first choices and Connecteam takes 49%.ShowHide
Search and answers
whatsapp.com is not in Google's top ten for any of the category's searches. In the answers, WhatsApp takes 0% of first choices and Connecteam takes 49%.
ShowHideIn search
Google, US estimatesPosition for “frontline apps”
–
not in the top ten
Position for “frontline employee communication app”
–
not in the top ten
- Searches for its name, Google
- 3,350,000 a month (“whatsapp”)
- AI search demand for its name, est.
- 149,185 a month
- Organic visits to its site
- about 10,630,949 a month
- Searches its site ranks for
- 41,401 · 24,397 in the top three
- Sites linking to it
- 5,504,880
- Paid Google search
- No ads found in the estimate; that does not mean it runs none
In answers
This editionShare of first choices
0%
rank 106 of 106 in frontline employee apps
Segment leader
49%
Connecteam
- First choices
- 0 across its categories
- Named in
- 42 answers
- Its own site cited
- in 42 of the answers that named it
Search figures are US estimates from DataForSEO, read September 28, 2026; AI search demand is its modeled, directional estimate, not a count of queries to any assistant. The answers are this edition's. Two measurements side by side: neither is read as the cause of the other.
What it publishes
ShowHide
What it publishes
ShowHideAddresses on whatsapp.com
191
subdomains included
Content
156
counted in the table below
Documentation
8
Product · Integration
13 · 1
| Kind | Pages | Last 90 days | 2025-11 to 2026-10 | Latest | Categories named |
|---|---|---|---|---|---|
| Blog | 153 | undated | |||
| Case study | 1 | undated | |||
| Report or ebook | 1 | undated | |||
| Comparison | 1 | 0 | 2024-08-06 |
Most recent
- 2024-08-06Whatsapp vs whatsapp business comparison
How it is countedHide how it is counted
Every page whatsapp.com exposes, subdomains included. Kind is read from the address and title. The last 90 days, the latest date and the twelve months count pages by when they were published, from the site's feeds, a date in the address, or the page's own publication date, read from up to a hundred of its most recently changed pages; a page that says only when it last changed is counted in its kind but not in when, so the recent counts are a floor, and a kind none of whose pages gives a publication date reads undated. Read October 5, 2026.
Names read as WhatsApp
What the judge wrote, as written, with how often. The vendor table decides that these count as WhatsApp; a claim can dispute any of them.
WhatsApp/WeChat 1
Follow WhatsApp
An email the morning each edition publishes: where this product moved, where it held, and by how much against the noise floor. One address, confirmed by a click; a stop link in every email.
Already following? Everything you follow, with a stop for each.
The company
WhatsApp is its own company.ShowHide
The company
WhatsApp is its own company.
ShowHideIn its own words
Stated by the vendor, not checked- Positioning
- Secure and Reliable Free Private Messaging and Calling
- For
- friends and family
- Price stated
- free whatsapp.com
- Free plan or trial
- free whatsapp.com
- Not stated on the pages read
- Starting price, integrations, certifications, hosting, customers
What WhatsApp's own pages state, read October 5, 2026: whatsapp.com. A claimed page can correct any of them.
Is this your product?
Claim this page
Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when WhatsApp's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as WhatsApp, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.
What a new claim receivesHide what a new claim receives
A new claim receives the current edition's vendor brief for WhatsApp by email, built from the raw record of the edition. It shows:
- where WhatsApp is named, by buyer and by framing, and which cells hold its first choices;
- the claims the models make when they name it, ranked, with the strongest and the weakest quoted;
- its vocabulary against the segment leader's, and the pages the models cited;
- who was chosen in the answers that did not name WhatsApp, and every reason the record gives;
- a battlecard for each top rival: the head-to-head split, why they win, and the reservation quoted against them;
- one page of published figures cleared to show a buyer.