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 25 → 54 of 77
Microsoft Power BI
22Judge labels
2First choices
12Negative labels
11 / 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
9 labels, too few to rank
A product needs 10 labels in a category before a share or quadrant is stated. Microsoft Power BI was named 9 times in People analytics, where Crunchr led with 22%. The labels and the evidence are below, counted exactly.
By buyer segmentRead the same way at every buyer size.
Small business62 of 81
0%6 labels
under the label threshold
Mid-market18 of 114
2%9 labels
under the label threshold
Enterprise11 of 79
2%6 labels
under the label threshold
In people analytics · 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 Microsoft Power BI 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 |
|---|---|---|---|---|---|---|---|
| People analytics | Workforce planning and analytics | 2% | 18 of 114 | 56% | 9 | under 10 labels · led by Crunchr 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, Microsoft Power BI held within the floor in its one category: no change cleared 13 points.
Best category · People analytics · 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 77 → 91 of 101
Enterprise▲+2Since September 2026: 0% → 2%, +2 points. Inside the 13-point floor: within noise. Read over the models both editions asked.
2%from 0% in September 2026
Inside the floor by 11 pointsRank 43 → 10 of 72
All categories · Mid-market
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| People analytics | 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 77 → 18 of 114 |
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 Microsoft Power BI 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 Microsoft Power BI 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 | 1 | 1 |
| Gemini 3.5 Flash | 0 | 1 | 0 | 1 | 2 |
| Perplexity Sonar | 0 | 0 | 0 | 0 | 0 |
| Grok 4.1 Fast | 0 | 0 | 0 | 1 | 1 |
| Mistral Small | 0 | 0 | 0 | 0 | 0 |
| DeepSeek V4 Flash | 0 | 0 | 0 | 0 | 0 |
| Llama 4 Maverick | 0 | 0 | 0 | 0 | 0 |
| Qwen 3.7 Flash | 0 | 1 | 0 | 0 | 1 |
| Kimi K2 | 0 | 0 | 0 | 0 | 0 |
| GLM 4.7 FlashX | 0 | 0 | 1 | 1 | 2 |
| MiniMax M2.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-6 Luna | 1 | 0 | 0 | 0 | 1 |
| 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
Direct1 labelNone
Paraphrase0 labelsNone
Comparative2 labelsNone
Budget-constrained7 labels2
Scale-constrained0 labelsNone
Negative12 labelsNone
First choiceAlternativeMentionNegative22 labels in all, every segment counted; 2 of the 2 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.
“For a genuinely tight budget, I'd start with your existing HRIS reports plus Power BI—not buy a dedicated people-analytics platform yet.” GPT-6 Luna · People analytics · budget prompt · first choice
“It is an industry-standard, incredibly robust tool for data modeling... The Catch: High learning curve.” Gemini 3.5 Flash · People analytics · budget prompt · alternative
“you likely already own Power BI licenses. There is no extra cost.” Qwen 3.7 Flash · People analytics · budget prompt · alternative
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.
“Labeled "criticized challenger" in benchmarks; opaque pricing scales poorly for non-enterprises.” Grok 4.1 Fast · People analytics · negative prompt · soft negative
“often recommended for budget-conscious teams but flagged for learning curve and usability” Muse Glimmer 30B · People analytics · negative prompt · soft negative
“require you to build the HR data model, historical logic, and workforce metrics yourself” GPT-5.4 mini · People analytics · comparative prompt · soft negative
“custom-built *Tableau*/*Power BI* setups ... they typically become "shelfware"” Gemini 3.5 Flash · People analytics · negative prompt · soft negative
Named alongside
The products named in the same answers as Microsoft Power BI, over the 22 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Microsoft Power BI was named but was not.ShowHide
Named alongside
The products named in the same answers as Microsoft Power BI, over the 22 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Microsoft Power BI 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 Microsoft Power BI. 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 20 of the 22 answers that named Microsoft Power BI and are not a share of its labels.
Domains cited
firsthr.app11
hrbench.com10
effy.ai8
g2.com7
selectsoftwarereviews.com7
leapsome.com6
currentware.com5
devopsschool.com5
eletive.com5
hr-ai-index.com5
No domain is on file for Microsoft Power BI, so its own site is not marked.
Pages cited
Pages are listed as the models cited them.
Search and answers
Where Microsoft Power BI stands in Google search beside where it stands in the models' answers.ShowHide
Search and answers
Where Microsoft Power BI stands in Google search beside where it stands in the models' answers.
ShowHideIn search
Google, US estimates- Searches for its name, Google
- 14,800 a month (“microsoft power bi”)
- AI search demand for its name, est.
- 515 a month
- Its own site
- No site of its own on file, so no site figures
In answers
This editionShare of first choices
2%
rank 18 of 114 in people analytics
Segment leader
22%
Crunchr
- First choices
- 2 across its categories
- Named in
- 22 answers
- Its own site cited
- No site on file to match
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.
Names read as Microsoft Power BI
What the judge wrote, as written, with how often. The vendor table decides that these count as Microsoft Power BI; a claim can dispute any of them.
Power BI 5Microsoft Power BI / Viva Insights 1
Follow Microsoft Power BI
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 Microsoft Power BI'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 Microsoft Power BI, 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 Microsoft Power BI by email, built from the raw record of the edition. It shows:
- where Microsoft Power BI 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 Microsoft Power BI, 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.