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 61 → 70 of 72
Salesforce · 2 categories · RankedSalesforce Revenue Intelligence
73Judge labels
5First choices
18Negative labels
14 / 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.
Best standing
8% in Revenue intel for enterprise buyers
Rank 10 of 76 in the mid-market standingcriticized challenger
0 of 14 models made it the first choice on the direct prompt; 29% of its 21 labels there were negative.
What the models named instead of Salesforce Revenue Intelligence →By buyer segmentRead the same way at every buyer size.
Small business73 of 75
0%17 labels
criticized challenger
Mid-market10 of 76
2%21 labels
criticized challenger
Enterprise2 of 73
8%32 labels
accepted challenger
In revenue intel · 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 Salesforce Revenue Intelligence 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 |
|---|---|---|---|---|---|---|---|
| Revenue intelligence and forecasting | Sales | 2% | 10 of 76 | 29% | 21 | criticized challenger | ▲+1Since September 2026: 2% → 2%, +1 point. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Territory and quota planning | Revenue operations | 0% | 102 of 123 | 0% | 1 | under 10 labels · led by CaptivateIQ Planning at 36% | newNew since September 2026: not ranked then, 0% now. |
Movement
Since September 2026, Salesforce Revenue Intelligence held within the floor in all two categories: no change cleared 11 points.
Best category · Revenue intel · by segment
Mid-market▲+1Since September 2026: 2% → 2%, +1 point. Inside the 11-point floor: within noise. Read over the models both editions asked.
2%from 2% in September 2026
Inside the floor by 10 pointsRank 13 → 11 of 68
Enterprise▲+3Since September 2026: 2% → 5%, +3 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
5%from 2% in September 2026
Inside the floor by 8 pointsRank 6 → 3 of 66
All categories · Mid-market
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| Revenue intel | 2% | 2% | ▲+1Since September 2026: 2% → 2%, +1 point. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 13 → 10 of 76 |
| Territory planning | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 102 of 123, 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 Salesforce Revenue Intelligence 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 Salesforce Revenue Intelligence 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 | 1 | 1 | 0 | 0 | 2 |
| Gemini 3.5 Flash | 0 | 2 | 0 | 1 | 3 |
| Perplexity Sonar | 0 | 2 | 0 | 0 | 2 |
| Grok 4.20 | 0 | 1 | 1 | 0 | 2 |
| Mistral Small | 0 | 0 | 0 | 1 | 1 |
| DeepSeek V4 Flash | 0 | 1 | 1 | 0 | 2 |
| Llama 4 Maverick | 0 | 0 | 1 | 0 | 1 |
| Qwen 3.7 Flash | 0 | 0 | 0 | 1 | 1 |
| Kimi K2 | 0 | 0 | 0 | 1 | 1 |
| GLM 4.7 FlashX | 0 | 0 | 0 | 0 | 0 |
| MiniMax M2.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-6 Luna | 0 | 2 | 1 | 0 | 3 |
| Muse Glimmer 30B | 0 | 2 | 0 | 1 | 3 |
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
Direct14 labels1
Paraphrase11 labelsNone
Comparative16 labels1not counted in share
Budget-constrained11 labels4
Scale-constrained11 labelsNone
Negative10 labelsNone
First choiceAlternativeMentionNegative73 labels in all, every segment counted; 5 of the 6 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.
“my default pick is: 1) Salesforce Revenue Intelligence if you already live in Salesforce” GPT-5.4 mini · Revenue intel · budget prompt · first choice
“Try Salesforce's native forecasting and pipeline tools first. Revenue Intelligence adds analytics and forecast features” GPT-6 Luna · Revenue intel · paraphrase prompt · alternative
“If you are a heavily customized Salesforce shop, keeping your data native inside Sales Cloud avoids security reviews” Gemini 3.5 Flash · Revenue intel · scale prompt · alternative
“Check whether its native forecasting and Revenue Intelligence features meet your needs before buying another layer.” GPT-6 Luna · Revenue intel · direct 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.
“adding Salesforce Revenue Intelligence is often highly redundant and far less flexible” Gemini 3.5 Flash · Revenue intel · negative prompt · hard negative
“What to Avoid ... Requires Salesforce ecosystem” Kimi K2 · Revenue intel · budget prompt · hard negative
“Users find the steep learning curve daunting, struggling with complex setups and mobile UX challenges... Users find the product expensive” Muse Glimmer 30B · Revenue intel · negative prompt · soft negative
“highly dependent on data quality, as it amplifies whatever's already in your CRM” Claude Haiku 4.5 · Revenue intel · negative prompt · soft negative
Named alongside
The products named in the same answers as Salesforce Revenue Intelligence, over the 73 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Salesforce Revenue Intelligence was named but was not.ShowHide
Named alongside
The products named in the same answers as Salesforce Revenue Intelligence, over the 73 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Salesforce Revenue Intelligence 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 Salesforce Revenue Intelligence. 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 71 of the 73 answers that named Salesforce Revenue Intelligence and are not a share of its labels.
Domains cited
avoma.com39
demandbase.com34
pipeline.zoominfo.com33
cleverly.co27
zapier.com25
salesmotion.io24
marketsandmarkets.com21
tellius.com21
optif.ai19
salesforce.comYour site19
243 of the 262 domain citations in answers naming Salesforce Revenue Intelligence came from somebody else's page.
Pages cited
Pages are listed as the models cited them.
Search and answers
Where Salesforce Revenue Intelligence stands in Google search beside where it stands in the models' answers.ShowHide
Search and answers
Where Salesforce Revenue Intelligence stands in Google search beside where it stands in the models' answers.
ShowHideIn search
Google, US estimates- Searches for its name, Google
- 110 a month (“salesforce revenue intelligence”)
- AI search demand for its name, est.
- 2 a month
- Its own site
- It sits on Salesforce's site (salesforce.com), so there are no site figures for it alone
In answers
This editionShare of first choices
2%
rank 10 of 76 in revenue intel
Segment leader
28%
Clari Copilot
- First choices
- 5 across its categories
- Named in
- 73 answers
- Its own site cited
- in 71 of the answers that named it
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.
Names read as Salesforce Revenue Intelligence
What the judge wrote, as written, with how often. The vendor table decides that these count as Salesforce Revenue Intelligence; a claim can dispute any of them.
Salesforce 4Salesforce Revenue Intelligence (Einstein) 2Salesforce Revenue Intelligence / Agentforce Sales 2Salesforce Revenue Intelligence / Agentforce 1Salesforce Revenue Intelligence / Einstein 1
Follow Salesforce Revenue Intelligence
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
Salesforce is the company behind Salesforce Revenue Intelligence.ShowHide
The company
Salesforce is the company behind Salesforce Revenue Intelligence.
ShowHideOn record
Wikidata- Website
- salesforce.com
- Headquarters
- San Francisco, United States
- Founded
- 1999
- Employees
- about 35,000 (2019)
- Ownership
- Public, CRM on New York Stock Exchange
- Also from Salesforce
- Salesforce / Marketing Cloud Next / Agentforce Marketing, Salesforce Agentforce, Salesforce Agentforce / Einstein, Salesforce Agentforce Engagement, Salesforce Agentforce Marketing, Salesforce Agentforce SDR, Salesforce Agentforce Voice, Salesforce Agentforce for Marketing Cloud and 92 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
In its own words
Stated by the vendor, not checked- Free plan or trial
- Try Sales Cloud free for 30 days. No credit card, no installations. salesforce.com/sales/sales-intelligence
- Not stated on the pages read
- Positioning, who it is for, price, starting price, integrations, certifications, hosting, customers
What Salesforce Revenue Intelligence's own pages state, read September 28, 2026: salesforce.com/products/why-salesforce, salesforce.com/sales/sales-intelligence, salesforce.com/sales/revenue-intelligence, salesforce.com/platform/analytics-insights, salesforce.com/sales/revenue-cloud-billing. 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 Salesforce Revenue Intelligence'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 Salesforce Revenue Intelligence, 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 Salesforce Revenue Intelligence by email, built from the raw record of the edition. It shows:
- where Salesforce Revenue Intelligence 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 Salesforce Revenue Intelligence, 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.