Overview Leaderboard Methodology
Industry Report

Team Time Tracking Software

Applications that track employee or project time, produce timesheets, and integrate time data with billing and payroll.

Brands tracked: 37
Brands analyzed: 37
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 287
Total responses: 1,470
Top Brand Overall?
Toggl Track
90/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Toggl Track
85

Highest score on the LBA metric.

Authority Leader?
Toggl Track
93

Highest score on the Authority metric.

TOM Leader?
Harvest
96

Highest score on the TOM metric.

Toggl Track is the default answer in AI responses for Team Time Tracking Software

When users ask ChatGPT, Claude, or Gemini about Team Time Tracking Software, Toggl Track is the brand that surfaces first - unprompted, consistently, and usually at the top of any list the model generates. Clockify 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 37 Team Time Tracking Software 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
Toggl Track
toggl.com
 85
93
94
90
2
Clockify
clockify.me
 71
82
90
80
3
Harvest
getharvest.com
 81
63
96
79
4
Hubstaff
hubstaff.com
 67
26
72
50
5
QuickBooks Time
quickbooks.com
 78
18
74
47
6
RescueTime
rescuetime.com
 78
8
13
20
7
Deputy
deputy.com
 75
4
16
17
8
Everhour
everhour.com
 63
4
6
12
9
Jibble
jibble.io
 60
5
3
9
10
Timely
gettimely.com
 68
2
6
9
11
Time Doctor
timedoctor.com
 63
0
35
3
12
ClickUp
clickup.com
 79
0
14
2
13
ClockShark
clockshark.com
 60
10
0
2
14
Connecteam
connecteam.com
 79
0
5
2
15
FreshBooks
freshbooks.com
 80
0
8
2
16
Homebase
joinhomebase.com
 59
0
7
2
17
Paymo
paymoapp.com
 58
0
8
2
18
Replicon
replicon.com
 61
0
17
2
19
TimeCamp
timecamp.com
 61
1
0
2
20
Asana
asana.com
 85
0
2
1
21
Buddy Punch
buddypunch.com
 64
0
0
1
22
ClickTime
clicktime.com
 60
0
5
1
23
My Hours
myhours.com
 53
0
6
1
24
Rippling
rippling.com
 72
0
1
1
25
When I Work
wheniwork.com
 68
0
1
1
26
actiTIME
actitime.com
 56
0
0
0
27
Beebole
beebole.com
 33
0
0
0
28
DeskTime
desktime.com
 58
0
0
0
29
Kimai
kimai.org
 61
0
0
0
30
Monday CRM
monday.com
 52
0
0
0
31
Monitask
monitask.com
 39
0
0
0
32
OnTheClock
ontheclock.com
 48
0
0
0
33
Tick
tickspot.com
 41
0
0
0
34
TimeClock Plus
timeclockplus.com
 57
0
0
0
35
Timeero
timeero.com
 37
0
0
0
36
TimeTac
timetac.com
 38
0
0
0
37
TrackingTime
trackingtime.co
 47
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 287 shared Team Time Tracking Software 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 287 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 →