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 in this industry.

Authority Leader?
Hightouch
100

Highest score on the Authority metric in this industry.

TOM Leader?
Hightouch
100

Highest score on the TOM metric in this industry.

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

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
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 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 →