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 91 → 101 of 106
Happify
5Judge labels
0First choices
5Negative labels
5 / 14Models named it
1Category
October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10.7, every buyer segment counted.
Standing
5 labels, too few to rank
A product needs 10 labels in a category before a share or quadrant is stated. Happify was named 5 times in Employee wellbeing, where Wellable led with 22%. The labels and the evidence are below, counted exactly.
By buyer segmentRead the same way at every buyer size.
Small businessnot named
0%
No model named it for this buyer.
Mid-market106 of 111
0%5 labels
under the label threshold
Enterprisenot named
0%
No model named it for this buyer.
In employee wellbeing · 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 Happify 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 |
|---|---|---|---|---|---|---|---|
| Employee wellbeing and mental health | Onboarding and employee experience | 0% | 106 of 111 | 100% | 5 | under 10 labels · led by Wellable at 22% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. |
Movement
Since September 2026, Happify held within the floor in its one category: no change cleared 13 points.
Best category · Employee wellbeing · by segment
All categories · Mid-market
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| Employee wellbeing | 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 91 → 106 of 111 |
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 Happify 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 Happify 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 | 0 | 0 |
| GPT-5.4 mini | 0 | 0 | 0 | 0 | 0 |
| Gemini 3.5 Flash | 0 | 0 | 0 | 0 | 0 |
| Perplexity Sonar | 0 | 0 | 0 | 0 | 0 |
| Grok 4.1 Fast | 0 | 0 | 0 | 1 | 1 |
| Mistral Small | 0 | 0 | 0 | 1 | 1 |
| DeepSeek V4 Flash | 0 | 0 | 0 | 1 | 1 |
| Llama 4 Maverick | 0 | 0 | 0 | 1 | 1 |
| Qwen 3.7 Flash | 0 | 0 | 0 | 0 | 0 |
| Kimi K2 | 0 | 0 | 0 | 0 | 0 |
| GLM 4.7 FlashX | 0 | 0 | 0 | 0 | 0 |
| MiniMax M2.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-6 Luna | 0 | 0 | 0 | 0 | 0 |
| Muse Glimmer 30B | 0 | 0 | 0 | 1 | 1 |
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
Direct0 labelsNone
Paraphrase0 labelsNone
Comparative0 labelsNone
Budget-constrained0 labelsNone
Scale-constrained0 labelsNone
Negative5 labelsNone
First choiceAlternativeMentionNegative5 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.
“Others frequently criticized: Happify, Sanvello, Moodfit, Moodkit (EPHA/Mozilla: half-baked science, data-hungry, no proven benefits)” Grok 4.1 Fast · Employee wellbeing · negative prompt · hard negative
“Rely on half-baked science, have zero clinical robustness, and show no net health benefits.” Llama 4 Maverick · Employee wellbeing · negative prompt · hard negative
“Analysis of the sector notes big names including Calm, Happify, Headspace, Sanvello... describes many mental wellbeing apps as "Data-hungry and highly exploitative in nature"” Muse Glimmer 30B · Employee wellbeing · negative prompt · soft negative
“called out these apps as having: "Half-baked science" ... Included: Calm, Happify, Headspace, Sanvello” DeepSeek V4 Flash · Employee wellbeing · negative prompt · soft negative
Named alongside
The products named in the same answers as Happify, over the 5 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Happify was named but was not.ShowHide
Named alongside
The products named in the same answers as Happify, over the 5 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Happify 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 Happify. 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 5 of the 5 answers that named Happify and are not a share of its labels.
Domains cited
epha.org5
cnbc.com4
healthline.com3
therighthairstyles.com3
apa.org2
ftc.gov2
linkedin.com2
mozillafoundation.org2
pmc.ncbi.nlm.nih.gov2
theconversation.com2
No domain is on file for Happify, so its own site is not marked.
Pages cited
Pages are listed as the models cited them.
Follow Happify
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.
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 Happify'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 Happify, 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 Happify by email, built from the raw record of the edition. It shows:
- where Happify 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 Happify, 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.