People analytics · September 2026 Edition
BambooHR vs Visier
Zero of twelve models named BambooHR first on the direct prompt; three named Visier. Both were named by all twelve models and BambooHR carries 26 labels and Visier 48, so the shares are not directly comparable.
Named in twenty-four categories this edition.
Named in eight categories this edition.
First-choice share13%11%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate19%44%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#4A position in a field of 12; printed, not drawn.
Labels2648A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, BambooHR reading right to left. Rank and label count are printed, not drawn.ChartHop was named alongside these two in eight of the twelve direct answers. HiBob vs BambooHR · HiBob vs Visier · Crunchr vs BambooHR
Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all twelve models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the people analytics page.
By framing
How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
BambooHRFirst choices, of twelve modelsVisier
Direct032 against BambooHR · 6 against Visier
Paraphrase021 against BambooHR
Comparative09
Budget-constrained704 against Visier
Scale-constrained013 against Visier
Negative002 against BambooHR · 8 against Visier
Bars are first choices, 0 to 12 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to twelve.
Every model, every framing
The seventy-two answers behind the chart above, one cell each: where BambooHR and Visier stood in it.
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | | |||||
| GPT-5.4 mini | | | | | ||
| Gemini 3.5 Flash | | | | | | |
| Perplexity Sonar | | | | | | |
| Grok 4.1 Fast | | | | | | |
| Mistral Small | | | | |||
| DeepSeek V4 Flash | | | | | | |
| Llama 4 Maverick | | |||||
| Qwen 3.7 Flash | | | | | | |
| Kimi K2 | | | | | ||
| GLM 4.7 FlashX | | | | | ||
| MiniMax M2.5 | | | |
BambooHR Visier first choice named as an alternative argued againstblank: not namedEach cell is one answer, BambooHR on the left and Visier on the right.The direct prompt
The plain question, one answer per model, grouped by where BambooHR and Visier stood in it.
Visier first, BambooHR not the choice
3 of 12 modelsBambooHR was named in the answer but not as the choice, or not at all.GPT-5.4 miniVisier alternatives: ChartHop, Crunchr, Workday Peakon
Qwen 3.7 FlashVisier alternatives: Culture Amp, HiBob, Looker, Tableau
MiniMax M2.5Visier alternatives: Lattice, Workday HCM
Neither was the first choice, one was named
2 of 12 modelsThe answer put something else first and named one of the two as an alternative.Kimi K2Crunchr alternatives: ChartHop, Visier
GLM 4.7 FlashXCrunchr alternatives: BambooHR, ChartHop, Personio
Neither was named
7 of 12 modelsThe answer made no first choice from these two in this category.Claude Haiku 4.5HiBob alternatives: Rippling, UKG People Analytics
Gemini 3.5 FlashKnoetic alternatives: ChartHop, Culture Amp, Illoominus, Paradox
Perplexity SonarCrunchr, HiBob alternatives: ChartHop, Culture Amp
Grok 4.1 FastCrunchr alternatives: ChartHop, Lattice
Mistral SmallCrunchr alternatives: HiBob, Lattice
DeepSeek V4 FlashChartHop, Crunchr alternatives: Culture Amp, Lattice, Leapsome, Orgnostic
Llama 4 MaverickChartHop
Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.
By buyer segment
The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
BambooHR leads by forty-one points.
BambooHR41%#1 of 16Visier0%#16 of 16Mid-marketThe figures above
Enterprise
The order flips: Visier leads at enterprise.
Visier65%#1 of 9BambooHR0%#– of 9What the models said about BambooHR
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Two of two in this category shown.
“BambooHR (if you want an all-in-one HR + analytics system) or 15Five (for the lowest cost with no seat minimums) are the strongest choices” DeepSeek V4 Flash · budget prompt · first choice
“Top Pick: BambooHR \u2013 Frequently recommended for budget SMBs due to affordability, ease of use, and built-in reports” Grok 4.1 Fast · budget prompt · first choice
What the models said about Visier
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“Enterprise platforms like Visier offer custom enterprise pricing and implementation complexity that make them a poor fit for small to mid-market organizations.” Claude Haiku 4.5 · direct prompt · hard negative
“Platforms to Avoid in the Mid-Market ... Visier or One Model ... generally poor fits for the mid-market” Gemini 3.5 Flash · direct prompt · hard negative
“Avoid enterprise tools. Visier, Workday, and Eightfold AI typically require 500\u20131,000+ employees” DeepSeek V4 Flash · budget prompt · hard negative
“The category standard. Pre-built people-data model, deep metric library, 30M+ employee benchmarks, strong forecasting. Very powerful but complex.” Kimi K2 · comparative prompt · first choice
“| 1 | Visier | Large enterprises with complex, multi‑source workforce data | Deep workforce analytics, AI‑powered insights” GLM 4.7 FlashX · comparative prompt · first choice
“Market leader in people analytics, known for workforce planning, talent acquisition, and employee engagement.” Mistral Small · comparative prompt · first choice
Also compared
Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.