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 75 → 85 of 87
Oracle · 1 category · Named, not rankedOracle Enterprise Data Quality
12Judge labels
0First choices
6Negative labels
7 / 14Models named it
1Category
October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10-05.2, every buyer segment counted.
Standing
3 labels, too few to rank
A product needs 10 labels in a category before a share or quadrant is stated. Oracle Enterprise Data Quality was named 3 times in CRM data quality, where Insycle led with 43%. The labels and the evidence are below, counted exactly.
By buyer segmentRead the same way at every buyer size.
Small business94 of 96
0%5 labels
under the label threshold
Mid-market87 of 99
0%3 labels
under the label threshold
Enterprise26 of 103
0%4 labels
under the label threshold
In crm data quality · each standing computed within its segment · bars are 0 to 100 · the accent bar is the product's own best reading
Standing by category
Every category where a model named Oracle Enterprise Data Quality 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% | 87 of 99 | 33% | 3 | under 10 labels · led by Insycle at 43% | newNew since September 2026: not ranked then, 0% now. |
Movement
Since September 2026, Oracle Enterprise Data Quality held within the floor in its one category: no change cleared 11 points.
Best category · CRM data quality · by segment
Mid-marketnewNew since September 2026: not ranked then, 0% now.
0%from 0% in September 2026
Inside the floor by 11 pointsRank 81 of 90, unchanged
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 31 → 24 of 93
All categories · Mid-market
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| CRM data quality | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 87 of 99, 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 Oracle Enterprise Data Quality across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.ShowHide
By model
How each model treated Oracle Enterprise Data Quality across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.
ShowHide| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-5.4 mini | 0 | 0 | 0 | 0 | 0 |
| Gemini 3.5 Flash | 0 | 0 | 0 | 0 | 0 |
| Perplexity Sonar | 0 | 0 | 0 | 0 | 0 |
| Grok 4.20 | 0 | 0 | 0 | 0 | 0 |
| Mistral Small | 0 | 0 | 0 | 0 | 0 |
| DeepSeek V4 Flash | 0 | 0 | 0 | 0 | 0 |
| Llama 4 Maverick | 0 | 0 | 0 | 0 | 0 |
| Qwen 3.7 Flash | 0 | 0 | 0 | 0 | 0 |
| Kimi K2 | 0 | 0 | 0 | 0 | 0 |
| GLM 4.7 FlashX | 0 | 0 | 1 | 1 | 2 |
| MiniMax M2.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-6 Luna | 0 | 0 | 0 | 0 | 0 |
| Muse Glimmer 30B | 0 | 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
Paraphrase0 labelsNone
Comparative4 labels1not counted in share
Budget-constrained0 labelsNone
Scale-constrained0 labelsNone
Negative8 labelsNone
First choiceAlternativeMentionNegative12 labels in all, every segment counted; 0 of the 1 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.
No positive label carried a quote.
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.
“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
Named alongside
The products named in the same answers as Oracle Enterprise Data Quality, over the 12 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Oracle Enterprise Data Quality was named but was not.ShowHide
Named alongside
The products named in the same answers as Oracle Enterprise Data Quality, over the 12 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Oracle Enterprise Data Quality was named but was not.
ShowHideProductSame answerTook the first choice insteadHead to head
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 Oracle Enterprise Data Quality. 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 12 of the 12 answers that named Oracle Enterprise Data Quality and are not a share of its labels.
Domains cited
cognism.com12
cleanlist.ai11
g2.com9
integrate.io8
pipeline.zoominfo.com8
clearout.io6
gitnux.org6
au.pcmag.com4
cleansmartlabs.com4
findymail.com4
Seventy-two of the seventy-two domain citations in answers naming Oracle Enterprise Data Quality came from somebody else's page.
Pages cited
Pages are listed as the models cited them.
Names read as Oracle Enterprise Data Quality
What the judge wrote, as written, with how often. The vendor table decides that these count as Oracle Enterprise Data Quality; a claim can dispute any of them.
Oracle 2
Follow Oracle Enterprise Data Quality
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.
The company
Oracle Corporation is the company behind Oracle Enterprise Data Quality.ShowHide
The company
Oracle Corporation is the company behind Oracle Enterprise Data Quality.
ShowHideOn record
Wikidata- Website
- oracle.com
- Headquarters
- Bengaluru, India
- Founded
- 1977
- Employees
- about 162,000 (2025)
- Ownership
- Public, ORCL on Nasdaq
- Also from Oracle
- Oracle ATG, Oracle Analytics, Oracle Autonomous Data Warehouse, Oracle BI, Oracle BlueKai, Oracle CDX, Oracle CPQ, Oracle CRM and 46 more
Fetched September 14, 2026. These describe the company, not the product's standing, and a claimed page can dispute any of them. · Wikidata · LinkedIn · Crunchbase
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 Oracle Enterprise Data Quality'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 Oracle Enterprise Data Quality, 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 Oracle Enterprise Data Quality by email, built from the raw record of the edition. It shows:
- where Oracle Enterprise Data Quality 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 Oracle Enterprise Data Quality, 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.