Overview Leaderboard Methodology
Industry Report

Employee Experience Platforms

Comprehensive platforms that integrate onboarding, feedback, recognition, surveys, and analytics to optimize the end-to-end employee journey.

Brands tracked: 34
Brands analyzed: 34
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 269
Total responses: 1,365
Top Brand Overall?
Qualtrics
82/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Qualtrics
79

Highest score on the LBA metric.

Authority Leader?
Qualtrics
70

Highest score on the Authority metric.

TOM Leader?
Qualtrics
100

Highest score on the TOM metric.

Qualtrics leads the Employee Experience Platforms category in AI responses

Qualtrics is the most consistently-surfaced brand when users ask AI assistants about Employee Experience Platforms, but not to the point of monopolising the conversation. Culture Amp and a handful of others appear regularly, giving users a reasonable set of alternatives to compare. The top of this leaderboard is where most of the AI-driven traffic will go.

Brand Leaderboard All 34 Employee Experience Platforms brands ranked

Ranked by overall AI Visibility Score (geometric mean of LBA, Authority, and TOM). Click any brand for the full report.

# Brand LBA Authority TOM Overall
1
Qualtrics
qualtrics.com
 79
70
100
82
2
Culture Amp
cultureamp.com
 77
62
88
75
3
Workday
workday.com
 73
40
73
60
4
Lattice
lattice.com
 78
28
69
53
5
Peakon
peakon.com
 75
25
71
51
6
15Five
15five.com
 74
18
59
43
7
Leapsome
leapsome.com
 73
9
38
29
8
Bonusly
bonus.ly
 74
6
38
25
9
Glint
glintinc.com
 70
5
36
24
10
Workvivo
workvivo.com
 70
12
14
23
11
Officevibe
officevibe.com
 66
7
9
17
12
Workhuman
workhuman.com
 65
4
15
16
13
BambooHR
bamboohr.com
 73
3
4
10
14
Staffbase
staffbase.com
 71
7
2
10
15
Simpplr
simpplr.com
 69
2
5
9
16
Motivosity
motivosity.com
 61
0
13
6
17
Awardco
awardco.com
 65
0
5
2
18
Medallia
medallia.com
 71
0
22
2
19
WorkTango
worktango.com
 37
0
12
2
20
Achievers
achievers.com
 69
0
4
1
21
Enboarder
enboarder.com
 51
0
1
1
22
Kudos
kudos.com
 54
0
1
1
23
Nectar
nectarhr.com
 63
0
4
1
24
Perceptyx
perceptyx.com
 51
0
5
1
25
Reward Gateway
rewardgateway.com
 66
0
5
1
26
Assembly
assembly.com
 29
0
0
0
27
EngageRocket
engagerocket.co
 35
0
0
0
28
Firstup
firstup.io
 60
0
0
0
29
Limeade
limeade.com
 63
0
0
0
30
Matter
matterapp.com
 36
0
0
0
31
Mo
mo.work
 0
0
1
0
32
People Element
peopleelement.com
 36
0
0
0
33
Quantum Workplace
quantumworkplace.com
 57
0
0
0
34
StaffCircle
staffcircle.com
 33
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 269 shared Employee Experience Platforms prompts. The same prompts, same model, same iterations. So differences in scores reflect actual differences in AI visibility, not differences in measurement.

Overall AI Visibility Score
Geometric mean of LBA, Authority and TOM: (LBA × Authority × TOM)^(1/3). Geometric mean is used so that any single weak metric pulls the overall score down, rather than being masked by strength elsewhere.
Shared industry prompts
For Authority and TOM, all brands in the industry are scored against the same 269 category prompts (e.g. "best SEO tools for agencies"). This makes brand-to-brand comparisons valid - everyone faces identical inputs. LBA prompts are per-brand because they ask brand-specific questions.
Latent Brand Association (LBA)
5 brand probes + 1 control prompt, each run 5 times in recall mode (no web search). LBA = quality × meta × stability × share × recognition × 100. Read the full LBA methodology →
LLM Authority
50 organic category prompts (discovery, comparison, problem and transactional intents), each run once in recall mode and once in retrieval mode. Score = frequency × log-decayed prominence × intent weight, then 50/50 averaged across the two modes. Read the full Authority methodology →
Top of Mind (TOM)
15 high-volume discovery prompts (sourced from Keywords Everywhere search-volume data), each run 5 times in pure recall mode (no web). Score = frequency × (0.5 + 0.5 × log-prominence), volume-weighted. Read the full TOM methodology →