Revenue intelligence and forecasting
Asked as “revenue intelligence and forecasting platform”, and as “sales forecasting and pipeline analytics tool”, on behalf of a mid-market B2B software company. 55 first choices recorded across the direct, paraphrase, budget and scale prompts, six models each.
01The standing
Share is the count of first choices across the direct, paraphrase, budget and scale prompts, over all six models, for a mid-market B2B software company. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrant
Show the four products at 0%, ordered by negative rate
Bars are the share of first choices, 0 to 100Every product with at least 10 labels here. Every product name links to its vendor page.
Recommended versus criticized
Every product with at least 10 labels here, on both axes. The 30% line names a quadrant, not the verdict above: that one needs more than 40%.
Criticized challengerCriticized default
Negative label rate →
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13Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative40%
Key
01Avoma20%
Avoma20%02Clari Copilot18%
Clari Copilot18%03HubSpot Sales Hub16%
HubSpot Sales Hub16%04Gong9%
Gong9%05BoostUp7%
BoostUp7%06Pipedrive4%
Pipedrive4%07Revenue Grid2%
Revenue Grid2%08Salesloft2%
Salesloft2%09Revenue.io2%
Revenue.io2%10Salesforce Revenue Intelligence0%
Salesforce Revenue Intelligence0%11Aviso0%
Aviso0%12Chorus by ZoomInfo0%
Chorus by ZoomInfo0%13People.ai0%
People.ai0%02What they warned about
A high negative share on a product with few labels is a warning. A low share on a product with many labels is salience, not sentiment.
Clari Copilot35%
22 of 62 labels negative · 11 of 6 models · 4 hard negative
“Platforms to *Avoid* on a Limited Budget ... Clari \u2014 $100\u2013$200/user/month + $10K\u2013$75K implementation fees” DeepSeek V4 Flash, budget prompt
Gong31%
17 of 55 labels negative · 10 of 6 models · 3 hard negative
“**Avoid:** Enterprise platforms (Gong, Clari) unless you have 100+ reps and dedicated RevOps” Mistral Small, direct prompt
Chorus by ZoomInfo33%
6 of 18 labels negative · 6 of 6 models · 1 hard negative
“Avoid as a standalone; be cautious of transcription limits.” Gemini 3.5 Flash, negative prompt
People.ai33%
6 of 18 labels negative · 6 of 6 models · 1 hard negative
“Avoid if you are a small or non-enterprise team... Avoid it if your sales team is under 20 reps” Gemini 3.5 Flash, negative prompt
03What they cite
Citations exist only for the models that return a source list: four of the six in this edition.
Sites the answers cite
22 of 72 answers in this category came back with a source list, from 4 of 6 models: citations where the model returns them, or the search results it consulted. 6 of those lists are Google grounding redirects that name no site and are left out of the counts. 187 links across 85 sites, every framing counted. Ranked by the number of answers carrying the site or page. The other 2 models searched through a gateway that returned no source list on this edition.
vendor site · Oliv8 answers · 11 citations · 2 models
vendor site · ZoomInfo7 answers · 10 citations · 2 models
vendor site · Salesmotion7 answers · 7 citations · 2 models
6 answers · 8 citations · 2 models
vendor site · Zapier6 answers · 6 citations · 2 models
vendor site · Forecastio5 answers · 6 citations · 2 models
vendor site · MarketBetter5 answers · 5 citations · 2 models
4 answers · 6 citations · 2 models
vendor site · Clari4 answers · 5 citations · 1 model
vendor site · Tellius4 answers · 4 citations · 2 models
vendor site · Gartner3 answers · 4 citations · 2 models
3 answers · 4 citations · 2 models
Pages the answers cite
The ten pages named in the most answers, by full address. A page here is one the models returned with a recommendation, not one the index endorses.
8 answers · 2 models
7 answers · 2 models
5 answers · 2 models
4 answers · 2 models
4 answers · 2 models
4 answers · 2 models
4 answers · 2 models
3 answers · 1 model
3 answers · 2 models
3 answers · 1 model
04How they answered
Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.
ModelDirect“What is the best revenue intelligence and forecasting platform for a mid-market B2B company?”Paraphrase“Which sales forecasting and pipeline analytics tool would you recommend to a mid-sized B2B company?”Comparative“What are the top revenue intelligence platforms and how do they differ?”Budget-constrained“What is the best revenue intelligence and forecasting platform for a company with a limited budget?”Scale-constrained“We are a 500 person company evaluating a revenue intelligence and forecasting platform. What should we look at?”Negative“Which revenue intelligence platforms should I avoid or be cautious about?”
Claude Opus 5no first choiceno first choiceno first choiceno first choiceno first choicenothing named
Claude Opus 4.8no first choiceno first choiceno first choiceno first choiceno first choicenothing named
GPT-6 Astrano first choiceno first choiceno first choiceno first choiceno first choicenothing named
GPT-5.6 Solno first choiceno first choiceno first choiceno first choiceno first choicenothing named
Gemini 3.1 Prono first choiceno first choiceno first choiceno first choiceno first choicenothing named
Perplexity Sonar Prono first choiceno first choiceno first choiceno first choiceno first choicenothing named
Bold is the first choiceAlternatives are counted; the count opens them.What the answer argued against
05The record
One row per call: the version string exactly as returned, whether the model searched, sources cited, and latency. Full answer text is in the free responses file. Download the record
Zero rows: every prompt, every model, every answer.
| Prompt | Model | Version string | Time (UTC) | Searched | Sources | Latency |
|---|
Normalization in this category
Every judgment call made between the raw labels and the numbers above, listed so it is visible and reversible.
Category-scoped readings
HubSpot read as HubSpot Sales Hub
HubSpot (Sales Hub Professional) read as HubSpot Sales Hub
Salesforce read as Salesforce Revenue Intelligence
Unresolved, counted raw
Avature
Backstory \u2013 formerly People.ai
BoostUp AI
Chorus AI (by ZoomInfo)
Collective[i] / Intelligence.com
Discern
Einstein Copilot / EPM
Exec Vision
Forecast.io
Jirav
Mine
Nimitai
Outreach Commit
Recapped.io
Salesforce/Agentforce Sales
Zuuna
Discontinued, still offered
No shut-down product was recommended here.