Small businessgoneNot named this edition; 0% in September 2026.
0%from 0% in September 2026
Inside the floor by 11 pointsNot ranked
Google · 2 categories · Named, not rankedGoogle Dialogflow CX
16Judge labels
0First choices
3Negative labels
11 / 14Models named it
2Categories
October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10-05.2, every buyer segment counted.
Standing
6 labels, too few to rank
A product needs 10 labels in a category before a share or quadrant is stated. Google Dialogflow CX was named 6 times in Support chatbots and 1 other category, where Intercom Fin AI Agent led with 41%. The labels and the evidence are below, counted exactly.
By buyer segmentRead the same way at every buyer size.
Small businessnot named
0%
No model named it for this buyer.
Mid-market51 of 114
0%4 labels
under the label threshold
Enterprise19 of 113
0%8 labels
under the label threshold
In support chatbots · 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 Google Dialogflow CX 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 |
|---|---|---|---|---|---|---|---|
| Chatbots and conversational AI for support | Customer | 0% | 51 of 114 | 25% | 4 | under 10 labels · led by Intercom Fin AI Agent at 41% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| AI voice agents | Customer | 0% | 78 of 103 | 50% | 2 | under 10 labels · led by Retell AI at 27% |
Movement
Since September 2026, Google Dialogflow CX held within the floor in all two categories: no change cleared 11 points.
Best category · Support chatbots · by segment
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 30 → 48 of 109
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 50 → 18 of 105
All categories · Mid-market
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| Support chatbots | 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 30 → 51 of 114 |
| AI voice agents | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 78 of 103, 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 Google Dialogflow CX 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 Google Dialogflow CX 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 | 1 | 1 |
| GPT-5.4 mini | 0 | 0 | 0 | 0 | 0 |
| Gemini 3.5 Flash | 0 | 0 | 0 | 0 | 0 |
| Perplexity Sonar | 0 | 0 | 1 | 0 | 1 |
| Grok 4.20 | 0 | 0 | 0 | 0 | 0 |
| Mistral Small | 0 | 0 | 1 | 0 | 1 |
| 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 | 1 | 0 | 0 | 1 |
| GLM 4.7 FlashX | 0 | 0 | 0 | 0 | 0 |
| MiniMax M2.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-6 Luna | 0 | 0 | 0 | 1 | 1 |
| Muse Glimmer 30B | 0 | 1 | 0 | 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
Paraphrase2 labelsNone
Comparative8 labels1not counted in share
Budget-constrained1 labelNone
Scale-constrained1 labelNone
Negative4 labelsNone
First choiceAlternativeMentionNegative16 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.
“Google Dialogflow CX — Good for Google Cloud shops” Kimi K2 · AI voice agents · scale prompt · alternative
“Advanced NLU with structured flows for voice and IVR.” Muse Glimmer 30B · Support chatbots · 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.
“That's a reason to check patch status, permissions, and past configuration changes—not an automatic reason to reject Dialogflow.” GPT-6 Luna · Support chatbots · negative prompt · soft negative
“their higher latency and SLA gaps may impact conversation quality” Claude Haiku 4.5 · AI voice agents · negative prompt · soft negative
Named alongside
The products named in the same answers as Google Dialogflow CX, over the 16 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Google Dialogflow CX was named but was not.ShowHide
Named alongside
The products named in the same answers as Google Dialogflow CX, over the 16 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Google Dialogflow CX 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 Google Dialogflow CX. 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 16 of the 16 answers that named Google Dialogflow CX and are not a share of its labels.
Domains cited
botpress.com6
capterra.com5
yellow.ai5
zendesk.com5
retellai.com4
cloudtalk.io3
comm100.com3
cxtoday.com3
g2.com3
gartner.com3
Forty of the forty domain citations in answers naming Google Dialogflow CX came from somebody else's page.
Pages cited
Pages are listed as the models cited them.
Follow Google Dialogflow CX
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
Google is the company behind Google Dialogflow CX.ShowHide
The company
Google is the company behind Google Dialogflow CX.
ShowHideOn record
Wikidata- Website
- google.com
- Headquarters
- Mountain View, California, United States
- Founded
- 1998
- Ownership
- Part of Alphabet Inc.
- Also from Google
- Adometry, Attribution 360, BigQuery, Firebase, Google ADH, Google Ad Manager, Google AdMob, Google AdSense and 81 more
Fetched September 14, 2026, with a correction applied. These describe the company, not the product's standing, and a claimed page can dispute any of them. · Wikidata
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 Google Dialogflow CX'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 Google Dialogflow CX, 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 Google Dialogflow CX by email, built from the raw record of the edition. It shows:
- where Google Dialogflow CX 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 Google Dialogflow CX, 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.