| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| Recognition and rewards | Onboarding and employee experience | 29% | 1 of 98 | 7% | 57 | accepted challenger | ▲+1Since September 2026: 22% → 23%, +1 point. Inside the 13-point floor: within noise. Read over the models both editions asked. |
| Employee engagement surveys | Onboarding and employee experience | 0% | 17 of 58 | 0% | 5 | under 10 labels · led by Culture Amp at 37% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. |
| HR AI assistants | Onboarding and employee experience | 0% | 27 of 142 | 0% | 3 | under 10 labels · led by MeBeBot at 21% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. |
| 360 feedback | Performance and talent management | 0% | 27 of 73 | 0% | 1 | under 10 labels · led by Lattice at 34% | newNew since September 2026: not ranked then, 0% now. |
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| Recognition and rewards | 22% | 23% | ▲+1Since September 2026: 22% → 23%, +1 point. Inside the 13-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 1 of 98, unchanged |
| Employee engagement surv | 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 14 → 17 of 58 |
| HR AI assistants | 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 26 → 27 of 142 |
| 360 feedback | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 27 of 73, 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
| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 0 | 2 | 1 | 0 | 3 |
| GPT-5.4 mini | 1 | 2 | 1 | 0 | 4 |
| Gemini 3.5 Flash | 1 | 3 | 1 | 1 | 6 |
| Perplexity Sonar | 1 | 1 | 1 | 0 | 3 |
| Grok 4.1 Fast | 2 | 2 | 2 | 1 | 7 |
| Mistral Small | 1 | 2 | 2 | 1 | 6 |
| DeepSeek V4 Flash | 3 | 3 | 2 | 0 | 8 |
| Llama 4 Maverick | 0 | 0 | 1 | 0 | 1 |
| Qwen 3.7 Flash | 2 | 3 | 0 | 0 | 5 |
| Kimi K2 | 3 | 1 | 1 | 1 | 6 |
| GLM 4.7 FlashX | 0 | 4 | 1 | 0 | 5 |
| MiniMax M2.5 | 2 | 0 | 1 | 0 | 3 |
| GPT-6 Luna | 3 | 0 | 1 | 0 | 4 |
| Muse Glimmer 30B | 2 | 3 | 0 | 0 | 5 |
Verbatim evidence the judge attached to positive labels.
“The best employee recognition software for most mid-market companies in 2025 is Bonusly for budget-conscious teams wanting fast peer-to-peer adoption” Muse Glimmer 30B · Recognition and rewards · direct prompt · first choice
“For most mid-market B2B companies (roughly 100–1,000 employees), Bonusly is consistently ranked as the best overall choice.” DeepSeek V4 Flash · Recognition and rewards · direct prompt · first choice
“Bonusly (Best Overall Value) ... widely considered the gold standard for affordability among professional recognition platforms” Qwen 3.7 Flash · Recognition and rewards · budget prompt · first choice
“the best overall choice is usually Bonusly because it is repeatedly recommended for small businesses and small budgets” Perplexity Sonar · Recognition and rewards · budget prompt · first choice
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.
“Some AI models explicitly recommend avoiding SMB-focused "peer-shout-out" tools like Bonusly for large organizations” Mistral Small · Recognition and rewards · negative prompt · hard negative
“Common gripes include monthly point caps that run out fast ... Reviewers say it feels generic and limiting for larger or unique teams.” Grok 4.1 Fast · Recognition and rewards · negative prompt · soft negative
“Smaller international reach, limited regional reward depth, point-to-value inconsistencies” Kimi K2 · Recognition and rewards · negative prompt · soft negative
“you find major players like Bonusly or Nectar too expensive” Gemini 3.5 Flash · Recognition and rewards · budget prompt · soft negative
Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 176 of the 186 answers that named Bonusly and are not a share of its labels.
666 of the 724 domain citations in answers naming Bonusly came from somebody else's page.
Pages are listed as the models cited them.
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.
| Kind | Pages | Last 90 days | 2025-10 to 2026-09 | Latest | Categories named |
|---|---|---|---|---|---|
| Blog | 654 | undated | Performance management, People analytics | ||
| Webinar or virtual event | 102 | undated | |||
| Case study | 45 | undated | |||
| Template or tool | 17 | undated | Recognition and rewards, Employee onboarding | ||
| Comparison | 10 | undated | |||
| Glossary or explainer | 8 | undated | Performance management | ||
| Conference or event | 6 | undated | |||
| Report or ebook | 4 | undated |
Every page bonusly.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. An event counts as online when its address or title says so (webinar, on demand, virtual or online summit); a conference, summit, trade show, expo or roadshow that does not say so is counted as a conference or event, which on a vendor's site is mostly in person. Read September 29, 2026.
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.
What Bonusly's own pages state, read September 28, 2026: bonusly.com, bonusly.com/pricing, bonusly.com/blog-topic/security, bonusly.com/product/growth, bonusly.com/blog-topic/customer-stories. A claimed page can correct any of them.
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 Bonusly'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 Bonusly, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.
A new claim receives the current edition's vendor brief for Bonusly by email, built from the raw record of the edition. It shows:
AI models recommend Bonusly first in Recognition and rewards this edition. Each badge says so in the buyer's words, names the edition, and links to the standing. The next edition issues a new badge; this one stays true as a record of October 2026.
Badges read on light and dark pages. Alt text carries the claim, the category, the edition and the index, so it stays a citation where the image does not load.