Small business▲+4Since September 2026: 2% → 6%, +4 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
6%from 2% in September 2026
Inside the floor by 7 pointsRank 9 → 6 of 65
5 categories · Named, not rankedCoffee
19Judge labels
5First choices
1Negative labels
9 / 14Models named it
5Categories
October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10-05.2, every buyer segment counted.
Standing
7 labels, too few to rank
A product needs 10 labels in a category before a share or quadrant is stated. Coffee was named 7 times in CDP and 4 other categories, where Segment led with 49%. The labels and the evidence are below, counted exactly.
By buyer segmentRead the same way at every buyer size.
Small business7 of 78
5%7 labels
under the label threshold
Mid-market26 of 61
0%2 labels
under the label threshold
Enterprisenot named
0%
No model named it for this buyer.
In cdp · 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 Coffee 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 |
|---|---|---|---|---|---|---|---|
| Customer data platforms | GTM data and infrastructure | 0% | 26 of 61 | 0% | 2 | under 10 labels · led by Segment at 49% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Revenue intelligence and forecasting | Sales | 0% | 68 of 76 | 50% | 2 | under 10 labels · led by Clari Copilot at 28% | newNew since September 2026: not ranked then, 0% now. |
| Conversational intelligence and call recording | Sales | 0% | 57 of 91 | 0% | 1 | under 10 labels · led by Avoma at 41% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Sales engagement platforms | Sales | 0% | 33 of 66 | 0% | 1 | under 10 labels · led by Apollo.io at 35% | newNew since September 2026: not ranked then, 0% now. |
| Web analytics | GTM data and infrastructure | 0% | 41 of 91 | 0% | 1 | under 10 labels · led by Google Analytics 4 at 57% |
Movement
Since September 2026, Coffee held within the floor in all five categories: no change cleared 11 points.
Best category · CDP · 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 25 → 26 of 57
All categories · Mid-market
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| CDP | 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 25 → 26 of 61 |
| Revenue intel | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 68 of 76, unchanged |
| Conversation intel | 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 37 → 57 of 91 |
| Sales engagement | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 33 of 66, unchanged |
| Web analytics | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 41 of 91, 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 Coffee 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 Coffee 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 | 1 | 0 | 0 | 1 |
| 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 4.1 Fast | 0 | 0 | 0 | 0 | 0 |
| Mistral Small | 0 | 0 | 0 | 0 | 0 |
| DeepSeek V4 Flash | 0 | 0 | 1 | 1 | 2 |
| Llama 4 Maverick | 0 | 1 | 1 | 0 | 2 |
| Qwen 3.7 Flash | 0 | 0 | 0 | 0 | 0 |
| Kimi K2 | 0 | 0 | 0 | 0 | 0 |
| GLM 4.7 FlashX | 0 | 2 | 0 | 0 | 2 |
| MiniMax M2.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-6 Luna | 0 | 0 | 0 | 0 | 0 |
| Muse Glimmer 30B | 0 | 0 | 0 | 0 | 0 |
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
Direct3 labels1
Paraphrase3 labelsNone
Comparative0 labelsNone
Budget-constrained8 labels4
Scale-constrained0 labelsNone
Negative5 labelsNone
First choiceAlternativeMentionNegative19 labels in all, every segment counted; 5 of the 5 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.
“Coffee - suitable for mid-sized B2B teams that want an AI agent to handle data entry and keep pipeline data accurate.” Llama 4 Maverick · Revenue intel · paraphrase prompt · alternative
“Agent-led platforms – That automatically capture emails, calls, and calendar events (Coffee, Sybill)” GLM 4.7 FlashX · Sales engagement · negative prompt · alternative
“Coffee identifies not just the visiting company but the specific named individuals inside it” Claude Haiku 4.5 · Web analytics · direct prompt · alternative
“Coffee CRM offers seat-based pricing with no usage meters, making it easy to budget.” GLM 4.7 FlashX · CDP · budget 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.
“Newer entrants (e.g., Coffee, DevRev): ... smaller customer bases, fewer enterprise references, and maturing features.” DeepSeek V4 Flash · Revenue intel · negative prompt · soft negative
Named alongside
The products named in the same answers as Coffee, over the 19 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Coffee was named but was not.ShowHide
Named alongside
The products named in the same answers as Coffee, over the 19 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Coffee 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 Coffee. 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 19 of the 19 answers that named Coffee and are not a share of its labels.
Domains cited
coffee.aiYour site19
pipeline.zoominfo.com9
g2.com8
brevo.com7
cdp.com7
forbes.com6
cloudtalk.io5
nvecta.com5
mailmodo.com4
prospeo.io4
Fifty-five of the seventy-four domain citations in answers naming Coffee came from somebody else's page.
Pages cited
Pages are listed as the models cited them.
What it publishes
ShowHide
What it publishes
ShowHideAddresses on coffee.ai
3,754
subdomains included
Content
3,613
counted in the table below
Documentation
113
Product · Integration
3 · 0
| Kind | Pages | Last 90 days | 2025-10 to 2026-09 | Latest | Categories named |
|---|---|---|---|---|---|
| Blog | 2,628 | 96 | 2026-09-28 | CRM, Enrichment | |
| Comparison | 923 | 59 | 2026-09-25 | CRM, ABM | |
| Podcast or video | 36 | undated | CRM | ||
| Glossary or explainer | 14 | 0 | 2026-06-01 | Enrichment, ABM | |
| Template or tool | 12 | 0 | 2026-05-11 | CRM, Enrichment |
Most recent
- 2026-09-28Building a crm data lake a practitioners build guide blog
- 2026-09-28Ai and crm how to consolidate your sales stack blog
- 2026-09-28Building data lake from crm blog
- 2026-09-28Ai sales stack consolidation blog
- 2026-09-27How to improve crm data quality with ai agents without chaos blog
- 2026-09-27Clari competitors for pipeline management how to choose blog
How it is countedHide how it is counted
Every page coffee.ai exposes, subdomains included. Kind is read from the address and title. The last 90 days, the latest date and the twelve months count pages by when they were published, from the site's feeds, a date in the address, or the page's own publication date, read from up to a hundred of its most recently changed pages; a page that says only when it last changed is counted in its kind but not in when, so the recent counts are a floor, and a kind none of whose pages gives a publication date reads undated. Of its titles that name a category, most name CRM (1430); 25 name its categories the models place it in. Read September 29, 2026.
Names read as Coffee
What the judge wrote, as written, with how often. The vendor table decides that these count as Coffee; a claim can dispute any of them.
Coffee.ai 2Coffee CRM 1
Follow Coffee
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
Coffee is its own company.ShowHide
The company
Coffee is its own company.
ShowHideIn its own words
Stated by the vendor, not checked- Positioning
- AI CRM Agent that automates data entry, contact enrichment, and pipeline intelligence for sales teams
- For
- sales teams
- Price stated
- Starting at $10/month per user. coffee.ai
- Starting price
- 10 coffee.ai
- Free plan or trial
- 14-day free trial available, no credit card required. coffee.ai
- Certifications
- SOC 2, Type 2GDPRHIPAACASA for Google Apps
- Customers named
- ProWest ElectricStoryPath AIDistyl AIRevenueBaseFanstakeAI Growth Agent
- Not stated on the pages read
- Integrations, hosting
What Coffee's own pages state, read October 5, 2026: coffee.ai, coffee.ai, coffee.ai/pricing, coffee.ai/security, coffee.ai/products/coffee-crm. A claimed page can correct any of them.
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 Coffee'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 Coffee, 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 Coffee by email, built from the raw record of the edition. It shows:
- where Coffee 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 Coffee, 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.