Overview Leaderboard Methodology
Industry Report

Workforce Engagement Management

Solutions for forecasting, scheduling, quality monitoring, and performance management to optimize contact-center staffing and agent performance.

Brands tracked: 35
Brands analyzed: 35
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 275
Total responses: 1,400
Top Brand Overall?
NICE
95/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
NICE
86

Highest score on the LBA metric in this industry.

Authority Leader?
NICE
100

Highest score on the Authority metric in this industry.

TOM Leader?
NICE
100

Highest score on the TOM metric in this industry.

NICE is the default answer in AI responses for Workforce Engagement Management

When users ask ChatGPT, Claude, or Gemini about Workforce Engagement Management, NICE is the brand that surfaces first - unprompted, consistently, and usually at the top of any list the model generates. Verint is a close second, but the gap between them is meaningful. If you're competing in this space and you're not in the top handful, you're effectively invisible to AI-driven discovery.

Brand Leaderboard All 35 Workforce Engagement Management brands ranked

Ranked by overall AI Visibility Score (smoothed geometric mean of LBA, Authority, and TOM with an LBA-based floor on Authority and TOM, see methodology). Click any brand for the full report.

# Brand LBA Authority TOM Overall
1
NICE
nice.com
 86
100
100
95
2
Verint
verint.com
 70
73
91
77
3
Genesys
genesys.com
 82
66
76
75
4
Calabrio
calabrio.com
 74
59
55
62
5
UKG
ukg.com
 72
11
64
39
6
Five9
five9.com
 75
17
42
38
7
Talkdesk
talkdesk.com
 70
17
38
37
8
Playvox
playvox.com
 53
9
22
23
9
Aspect Workforce
aspect.com
 43
4
24
18
10
Amazon
amazon.com
 47
5
14
16
11
CallMiner
callminer.com
 62
6
6
15
12
Cresta
cresta.com
 60
6
6
15
13
Observe.AI
observe.ai
 63
6
6
15
14
MaestroQA
maestroqa.com
 57
6
6
14
15
Zoom
zoom.us
 45
5
9
14
16
Balto
balto.ai
 51
5
5
13
17
Intradiem
intradiem.com
 51
5
5
13
18
Alvaria
alvaria.com
 47
5
5
12
19
Assembled
assembled.com
 49
5
5
12
20
Level AI
level.ai
 47
5
5
12
21
Scorebuddy
scorebuddyqa.com
 47
5
5
12
22
Tymeshift
tymeshift.com
 46
5
5
12
23
injixo
injixo.com
 41
4
4
11
24
DVSAnalytics
dvsanalytics.com
 32
3
3
9
25
Klaus
klausapp.com
 36
4
4
9
26
MiaRec
miarec.com
 33
3
3
9
27
Eleveo
eleveo.com
 30
3
3
8
28
CommunityWFM
communitywfm.com
 20
2
2
6
29
QStory
qstory.ai
 22
2
2
6
30
Enthu.AI
enthu.ai
 19
2
2
5
31
Monet Software
monetsoftware.com
 19
2
2
5
32
EvaluAgent
evaluagent.com
 14
1
1
4
33
I
InVision
invisionwfm.com
 13
1
1
4
34
Pipkins
pipkins.com
 12
1
1
4
35
ccMath
ccmath.com
 0
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 275 shared Workforce Engagement Management 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
Smoothed geometric mean of LBA, Authority and TOM. Authority and TOM are floored at LBA × 0.1 before the geometric mean (the same floor used in the per-metric cards above, so brand cards and the composite tell the same story). Formula: composite = ((LBA + 5)(Authority + 5)(TOM + 5))^(1/3) - 5. The floor keeps brands the model clearly recognises but doesn't yet recommend from collapsing to zero, while a single genuinely weak metric still pulls the composite down. Full methodology.
Shared industry prompts
For Authority and TOM, all brands in the industry are scored against the same 275 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 →