Every category where a model named Talend for a mid-market B2B company. Share is first choices across the direct, paraphrase, budget and scale prompts; rank is within every product named in that category.

Category	Function	Share	Rank	Negative rate	Labels	Quadrant	Since September 2026
CRM data quality and deduplication	Revenue operations	0%	99 of 99	67%	6	under 10 labels · led by Insycle at 43%	=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
Data management platforms	GTM data and infrastructure	0%	35 of 159	0%	3	under 10 labels · led by Segment at 37%	=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
Identity resolution	GTM data and infrastructure	0%	98 of 140	0%	1	under 10 labels · led by Hightouch Adaptive Identity Resolution at 12%	newNew since September 2026: not ranked then, 0% now.

Movement

Since September 2026, Talend held within the floor in all three categories: no change cleared 11 points.

Best category · CRM data quality · by segment

Small business=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.

0%from 0% in September 2026

Inside the floor by 11 pointsRank 99 → 86 of 87

Mid-market=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.

0%from 0% in September 2026

Inside the floor by 11 pointsRank 29 → 90 of 90

Enterprise=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.

0%from 0% in September 2026

Inside the floor by 11 pointsRank 76 → 25 of 93

All categories · Mid-market

Category	September 2026	Now	Change	Reading	Rank
CRM data quality	0%	0%	=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.	Within noise	Rank 29 → 99 of 99
DMP	0%	0%	=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.	Within noise	Rank 39 → 35 of 159
Identity	0%	0%	newNew since September 2026: not ranked then, 0% now.	New this edition	Rank 98 of 140, unchanged

Shares here are read over the models both editions asked, so they can differ by a point or two from the standing above, which counts every model in this edition.

The floor is 11 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one is noise, and both are shown. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. How the floor is measured · The editions

By model

How each model treated Talend across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.

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Model	Alternative	Mention	Negative	Labels
Claude Haiku 4.5	0	1	0	1
GPT-5.4 mini	1	0	0	1
Gemini 3.5 Flash	0	0	1	1
Perplexity Sonar	0	0	0	0
Grok 4.20	0	0	0	0
Mistral Small	0	0	1	1
DeepSeek V4 Flash	1	0	0	1
Llama 4 Maverick	0	1	0	1
Qwen 3.7 Flash	0	0	0	0
Kimi K2	0	0	1	1
GLM 4.7 FlashX	1	0	1	2
MiniMax M2.5	0	0	0	0
GPT-6 Luna	0	0	0	0
Muse Glimmer 30B	0	1	0	1

By framing

Which of the six questions produced the naming. By model says how often; this says asked what. The first-choice count on the right carries the marks of the models that produced it.

FramingLabels by classFirst choices

Direct0 labelsNone

Paraphrase3 labelsNone

Comparative10 labelsNone

Budget-constrained0 labelsNone

Scale-constrained1 labelNone

Negative16 labelsNone

First choiceAlternativeMentionNegative30 labels in all, every segment counted; 0 of the 0 first choices count toward share, since the comparative and negative framings do not. The bar is one segment per label class, to scale within the framing.

What the models said for it

Verbatim evidence the judge attached to positive labels.

“Strong transformation logic, good for complex data quality rules.” DeepSeek V4 Flash · DMP · comparative prompt · alternative

“Look at integration tools like Fivetran, Airbyte, ADF, Talend.” GPT-5.4 mini · DMP · comparative prompt · alternative

“Talend (open\u2011source) or Informatica (enterprise)” GLM 4.7 FlashX · DMP · comparative prompt · alternative

And against it

Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.

“Tools like Talend, Collibra, Oracle, SAP, Informatica, or Ataccama are great for broad data governance but can be overkill, expensive, and complex for pure CRM hygiene needs.” GLM 4.7 FlashX · CRM data quality · negative prompt · soft negative

“Large, complex enterprise data quality platforms (e.g., Talend, Collibra, Informatica, Ataccama) may be overkill for small to mid-sized businesses.” Mistral Small · CRM data quality · negative prompt · soft negative

“Avoid enterprise suites (Informatica, Talend) unless you have complex multi-system needs.” Kimi K2 · CRM data quality · scale prompt · soft negative

“without the enterprise-level price tag of tools like Informatica or Talend” Gemini 3.5 Flash · CRM data quality · paraphrase prompt · soft negative

Named alongside

The products named in the same answers as Talend, over the 30 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Talend was named but was not.

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ProductSame answerTook the first choice insteadHead to head

Informatica Data Quality17 of 302Not among the top eight

Ataccama ONE12 of 300Not among the top eight

DemandTools12 of 300Not among the top eight

Collibra Data Quality11 of 300Not among the top eight

Collibra9 of 300Not among the top eight

ZoomInfo9 of 300Not among the top eight

Informatica Intelligent Data Management Cloud8 of 305Not among the top eight

Cleanlist8 of 304Not among the top eight

Alation8 of 300Not among the top eight

Oracle Enterprise Data Quality8 of 300Not among the top eight

A head-to-head page exists where both products are among a category's top eight. The other rows are the same fact without a page behind them, so they link to the product instead.

What carried it into the answer

The sites and pages cited by the answers that named Talend. A fact about retrieval, not a lever on the model.

Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 26 of the 30 answers that named Talend and are not a share of its labels.

Domains cited

cleanlist.ai17

cognism.com16

g2.com14

clearout.io11

integrate.io10

findymail.com9

pipeline.zoominfo.com9

worldmetrics.org8

blog.hubspot.com6

gitnux.org6

No domain is on file for Talend, so its own site is not marked.

Pages cited

cleanlist.ai/blog/2026-03-27-data-quality-tools17

cognism.com/blog/data-quality-management-tools15

clearout.io/blog/crm-data-cleaning-solutions11

findymail.com/blog/crm-data-quality9

integrate.io/blog/top-10-data-cleansing-tools9

g2.com/categories/data-quality/f/crm8

cognism.com/blog/data-quality-software7

g2.com/categories/data-quality7

Pages are listed as the models cited them.

Search and answers

Where Talend stands in Google search beside where it stands in the models' answers.

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In search

Google, US estimates

Searches for its name, Google: 2,900 a month (“talend”)
AI search demand for its name, est.: 235 a month
Its own site: No site of its own on file, so no site figures

In answers

This edition

Share of first choices

rank 99 of 99 in CRM data quality

Segment leader

43%

Insycle

First choices: 0 across its categories
Named in: 30 answers
Its own site cited: No site on file to match

Search figures are US estimates from DataForSEO, read September 28, 2026; AI search demand is its modeled, directional estimate, not a count of queries to any assistant. The answers are this edition's. Two measurements side by side: neither is read as the cause of the other.

Follow Talend

An email the morning each edition publishes: where this product moved, where it held, and by how much against the noise floor. One address, confirmed by a click; a stop link in every email.

Already following? Everything you follow, with a stop for each.

Is this your product?

Claim this page

Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when Talend's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as Talend, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.

What a new claim receivesHide what a new claim receives

A new claim receives the current edition's vendor brief for Talend by email, built from the raw record of the edition. It shows:

where Talend is named, by buyer and by framing, and which cells hold its first choices;
the claims the models make when they name it, ranked, with the strongest and the weakest quoted;
its vocabulary against the segment leader's, and the pages the models cited;
who was chosen in the answers that did not name Talend, and every reason the record gives;
a battlecard for each top rival: the head-to-head split, why they win, and the reservation quoted against them;
one page of published figures cleared to show a buyer.