Overview Leaderboard Methodology
Industry Report

Anti-Tracking Extensions

Browser add-ons and plugins that block trackers, prevent cross-site profiling, and manage cookies to reduce online surveillance.

Brands tracked: 29
Brands analyzed: 29
Last updated: 2026-04-23
Model: OpenAI GPT-5
Prompts: 239
Total responses: 101
Top Brand Overall?
uBlock Origin
33/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
uBlock Origin
0

Highest score on the LBA metric in this industry.

Authority Leader?
uBlock Origin
100

Highest score on the Authority metric in this industry.

TOM Leader?
uBlock Origin
100

Highest score on the TOM metric in this industry.

Anti-Tracking Extensions is an emerging or highly fragmented category

No brand in Anti-Tracking Extensions scored above 40 on overall AI visibility. That means AI assistants do not currently recommend specific brands for this category with any consistency. Either the category is too new or too regional for the models to have converged on a default set of answers, or the queries users ask don't lend themselves to brand-specific responses.

Brand Leaderboard All 29 Anti-Tracking Extensions 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
uBlock Origin
ublockorigin.com
 0
100
100
33
2
Privacy Badger
privacybadger.org
 0
79
97
30
3
DuckDuckGo
duckduckgo.com
 0
9
58
12
4
ClearURLs
clearurls.xyz
 0
12
32
9
5
AdGuard
adguard.com
 0
15
15
8
6
C
Cookie AutoDelete
cookieautodelete.com
 0
6
17
6
7
Decentraleyes
decentraleyes.org
 0
0
17
3
8
NoScript
noscript.net
 0
0
17
3
9
Disconnect
disconnect.me
 0
0
10
2
10
LocalCDN
localcdn.org
 0
0
11
2
11
AdBlock
getadblock.com
 0
0
0
0
12
Adblock Plus
adblockplus.org
 0
0
0
0
13
AdNauseam
adnauseam.io
 0
0
0
0
14
Avast Secure Browser
avast.com
 0
0
0
0
15
AVG Secure Browser
avg.com
 0
0
0
0
16
Bitdefender Anti-Tracker
bitdefender.com
 0
0
0
0
17
Blur
abine.com
 0
0
0
0
18
Cookiebro
cookiebro.com
 0
0
0
0
19
EditThisCookie
editthiscookie.com
 0
0
0
0
20
Firefox Focus
mozilla.org
 0
0
0
0
21
Ghostery Private Browser
ghostery.com
 0
0
0
0
22
I
I don't care about cookies
idontcareaboutcookies.eu
 0
0
0
0
23
JShelter
jshelter.org
 0
0
0
0
24
Malwarebytes Browser Guard
malwarebytes.com
 0
0
0
0
25
Norton AntiTrack
norton.com
 0
0
0
0
26
P
Privacy Possum
privacypossum.org
 0
0
0
0
27
S
ScriptSafe
andryou.com
 0
0
0
0
28
Total Adblock
totaladblock.com
 0
0
0
0
29
Trace
absolutedouble.co.uk
 0
0
1
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 239 shared Anti-Tracking Extensions 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 239 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 →