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People analytics · October 2026 Edition

Crunchr vs BambooHR

Six of fourteen models named Crunchr first on the direct prompt; zero named BambooHR. Crunchr was named by thirteen of the fourteen models and BambooHR by thirteen and Crunchr carries 48 labels and BambooHR 32, so the shares are not directly comparable.

Crunchr

accepted challenger

Named in two categories this edition.

BambooHR

accepted challenger

Named in twenty-eight categories this edition.

First-choice share22%9%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate17%16%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#1#4A position in a field of 11; printed, not drawn.
Labels4832A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Crunchr reading right to left. Rank and label count are printed, not drawn.ChartHop was named alongside these two in ten of the fourteen direct answers. Crunchr vs ChartHop · Crunchr vs HiBob · Crunchr vs Rippling

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen 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 fourteen models made each the first choice, per way of asking, and how many argued against it.
CrunchrFirst choices, of fourteen modelsBambooHR
Direct60
Paraphrase401 against BambooHR
Comparative101 against BambooHR
Budget-constrained053 against Crunchr · 1 against BambooHR
Scale-constrained30
Negative305 against Crunchr · 2 against BambooHR
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Crunchr and BambooHR stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
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
GPT-6 Luna
Muse Glimmer 30B
Crunchr BambooHR first choice named as an alternative argued againstblank: not namedEach cell is one answer, Crunchr on the left and BambooHR on the right.

The direct prompt

The plain question, one answer per model, grouped by where Crunchr and BambooHR stood in it.

Crunchr first, BambooHR an alternative

6 of 14 modelsBambooHR was named in the answer but not as the choice, or not at all.
Mistral SmallChartHop, Crunchr alternatives: BambooHR, Eletive
DeepSeek V4 FlashCrunchr alternatives: ChartHop, Culture Amp
Llama 4 MaverickCrunchr alternatives: Ordio, Workhuman iQ
GLM 4.7 FlashXCrunchr, Orgnostic alternatives: ChartHop, HiBob, Worklytics
MiniMax M2.5Crunchr alternatives: ChartHop, Culture Amp, Workday People Analytics, Workhuman iQ
Muse Glimmer 30BChartHop, Crunchr

Neither was the first choice, one was named

3 of 14 modelsThe answer put something else first and named one of the two as an alternative.
GPT-5.4 miniHiBob alternatives: Crunchr, PeopleInsight
Perplexity SonarHiBob alternatives: Crunchr
Grok 4.1 FastChartHop alternatives: BambooHR, Culture Amp, Eletive, Lattice, Visier

Neither was named

5 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5HiBob alternatives: Rippling, Visier
Gemini 3.5 FlashKnoetic alternatives: ChartHop, Culture Amp, Visier
Qwen 3.7 FlashChartHop alternatives: HiBob, Lattice, One Model, Visier
Kimi K2ChartHop alternatives: HiBob, Lattice
GPT-6 LunaChartHop alternatives: HiBob, Lattice, Visier

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 fifty-three points.
BambooHR53%#1 of 16
Crunchr0%#13 of 16
The full small business standing →
Mid-marketThe figures above
The order flips: Crunchr leads at mid-market.
Crunchr22%#1 of 11
BambooHR9%#4 of 11
The full mid-market standing →
Enterprise
Crunchr leads by six points.
Crunchr6%#4 of 10
BambooHR0%#– of 10
The full enterprise standing →

What the models said about Crunchr

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.

“criticized challenger in SMB modelling and included in the enterprise-grade caution list” Muse Glimmer 30B · negative prompt · hard negative
“avoid enterprise-focused tools like Visier, Workday, One Model, ChartHop, Crunchr” Mistral Small · negative prompt · hard negative
“Enterprise tools like Visier/Crunchr (~$50K+/yr) aren't budget-friendly.” Grok 4.1 Fast · budget prompt · hard negative
“In summary, Crunchr is a strong, practical choice for organizations that want straightforward, self-service HR analytics and workforce insights, especially in the mid-market segment.” Muse Glimmer 30B · paraphrase prompt · first choice
“Crunchr and ChartHop are frequently cited as top choices due to their scalability, ease of use, and focus on self-serve analytics.” Mistral Small · direct prompt · first choice
“1. Crunchr: Best for mid-market and enterprise HR teams that want self-serve people analytics without building everything in BI.” Llama 4 Maverick · direct prompt · first choice

What the models said about BambooHR

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. One of one in this category shown.

“Strategic Tip: If you are on a strict budget, start with BambooHR... Best balance of ease-of-use and affordable reporting features.” Qwen 3.7 Flash · budget 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.