Overview Leaderboard Methodology
Industry Report

Reverse ETL Tools

Platforms that operationalize analytics by syncing transformed data from warehouses back into SaaS applications and operational systems.

Brands tracked: 40
Brands analyzed: 40
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 305
Total responses: 1,575
Top Brand Overall?
Hightouch
92/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Databricks
82

Highest score on the LBA metric.

Authority Leader?
Hightouch
100

Highest score on the Authority metric.

TOM Leader?
Hightouch
100

Highest score on the TOM metric.

Hightouch is the default answer in AI responses for Reverse ETL Tools

Hightouch and Census together dominate AI responses for Reverse ETL Tools. Both brands consistently surface unprompted, with the model treating them as the default answers for most category queries. Brands outside the top two face a structural disadvantage: users are usually given these two before the model even considers alternatives.

Brand Leaderboard All 40 Reverse ETL Tools 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
Hightouch
hightouch.com
 77
100
100
92
2
Census
getcensus.com
 71
86
100
85
3
RudderStack
rudderstack.com
 71
64
87
73
4
Polytomic
polytomic.com
 39
16
43
30
5
Omnata
omnata.com
 18
10
54
22
6
Salesforce
salesforce.com
 56
7
18
19
7
Fivetran
fivetran.com
 64
11
5
15
8
HubSpot
hubspot.com
 65
3
16
15
9
Workato
workato.com
 66
2
20
15
10
Snowflake
snowflake.com
 66
4
8
13
11
Segment
segment.com
 78
2
9
11
12
Airbyte
airbyte.com
 60
6
3
10
13
dbt
dbt.com
 73
1
7
7
14
ActionIQ
actioniq.com
 53
0
14
2
15
Braze
braze.com
 54
0
10
2
16
Databricks
databricks.com
 82
0
6
2
17
Grouparoo
grouparoo.com
 47
0
11
2
18
Slack
slack.com
 49
0
7
2
19
Google
google.com
 29
0
5
1
20
GrowthLoop
growthloop.com
 44
0
4
1
21
mParticle
mparticle.com
 67
0
2
1
22
Portable
portable.io
 37
0
7
1
23
Tealium
tealium.com
 65
0
5
1
24
Treasure Data
treasuredata.com
 59
0
2
1
25
Amazon
amazon.com
 32
0
0
0
26
Blueshift
blueshift.com
 43
0
0
0
27
C
Castled
castled.io
 21
0
0
0
28
CData
cdata.com
 47
0
0
0
29
Couchbase
couchbase.com
 45
0
0
0
30
Dataddo
dataddo.com
 45
0
0
0
31
Estuary
estuary.dev
 47
0
0
0
32
Hevo Data
hevodata.com
 56
0
0
0
33
Hopsworks
hopsworks.ai
 47
0
0
0
34
Hull
hull.io
 34
0
0
0
35
MessageGears
messagegears.com
 38
0
0
0
36
SeekWell
seekwell.io
 43
0
0
0
37
Simon Data
simondata.com
 61
0
0
0
38
Snowplow
snowplow.io
 53
0
0
0
39
Syncari
syncari.com
 38
0
0
0
40
Zeotap
zeotap.com
 41
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 305 shared Reverse ETL Tools 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 305 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 →