Proposal software
Asked as “proposal software”, and as “sales proposal and quote document tool”, on behalf of a mid-market B2B software company. 23 first choices recorded across the direct, paraphrase, budget and scale prompts, six models each.
Standing · first-choice share
65%
Clear leader
65PandaDoc17Better Proposals09DealHub09others
65% of first choices, clear leader.
The 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 rateLabelsQuadrantSince September 2026
Show the four products at 0%, ordered by negative rate
The floor is 12 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 can't be told apart from repeat variation, and both are shown. Each index measures its own floor from its own repeat, over its own categories, so the floor differs from one index to the next. How the floor is measured
Bars are the share of first choices, 0 to 100Every product with at least 10 labels here. Every product name links to its product page.
All six head-to-head pages: the top four products, each against each
One product takes 65% of first choices here, so the chart would put seven markers in one corner and one at the far edge. The two measurements it plots are columns in the standing above: share, and the negative label rate. Zero products carry a negative rate above 25% in this category.
What they warned about
Five of six models held their first choice under the paraphrase. Gemini 3.1 Pro changed. 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.
Proposify14%
4 of 28 labels negative · 4 of 6 models
“Proposify is an incredibly popular and powerful tool, but it frequently receives complaints from users regarding its page editor.” Gemini 3.1 Pro, negative prompt
PandaDoc9%
3 of 32 labels negative · 3 of 6 models
“PandaDoc is a fantastic tool with a great free tier, but you must look very closely at its premium pricing structures.” Gemini 3.1 Pro, negative prompt
Bidsketch100%
2 of 2 labels negative · 2 of 6 models
“Tools like Bidsketch were pioneers in the proposal space but have not kept pace with modern design expectations.” Gemini 3.1 Pro, negative prompt
Better Proposals6%
1 of 16 labels negative · 1 of 6 models
“Better Proposals for complex quoting. ... its product setup is relatively basic” GPT-5.6 Sol, negative prompt
What they cite
Six of the six models returned a source list in this edition: six return the pages they cited.
Sites the answers cite
30 of 36 answers in this category came back with a source list, from 6 of 6 models: citations where the model returns them, or the search results it consulted. 501 links across 149 sites, every framing counted. Ranked by the number of answers carrying the site or page. None of the 36 answers across every segment cited this index's own page for the category.
vendor site · Proposify23 answers · 34 citations · 6 models
vendor site · PandaDoc19 answers · 35 citations · 5 models
vendor site · Qwilr18 answers · 27 citations · 5 models
vendor site · GetAccept17 answers · 22 citations · 5 models
vendor site · SiftHub12 answers · 12 citations · 4 models
vendor site · Better Proposals11 answers · 14 citations · 5 models
8 answers · 11 citations · 3 models
vendor site · Oneflow8 answers · 8 citations · 3 models
8 answers · 8 citations · 3 models
vendor site · Zapier8 answers · 8 citations · 3 models
7 answers · 9 citations · 3 models
vendor site · Responsive7 answers · 8 citations · 5 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.
14 answers · 3 models
12 answers · 4 models
8 answers · 3 models
8 answers · 3 models
8 answers · 3 models
7 answers · 3 models
7 answers · 3 models
7 answers · 2 models
7 answers · 3 models
6 answers · 2 models
Search against answers
Each company's standing in the answers beside its site's footprint in Google search, one row a site: the products the models named on it with their shares, and the share they add up to; monthly searches on Google, and DataForSEO's estimate of AI search demand (modeled from search signals, directional, not a count of queries to any assistant), for the most-searched of the company's and its products' names (the name is in each row's hover text); estimated monthly organic visits to the site; and its best position in Google's top ten for “best proposal software”, “proposal software”. US estimates from DataForSEO and Google's Ads Transparency Center. A small company's site, or a mid-sized company's site for its flagship, is marked company; a product on a large parent's site (Google, Microsoft) has no site figures. A column with no figures for this category is left out, and an empty cell means none were seen, not none exist. Two measurements side by side: neither is read as the cause of the other.
| Company and products | Share | Own site cited | Name searches, Google | AI search demand, est. | Organic visits | Paid search a month, est. | Google ads, last 30 days | Best Google position |
|---|---|---|---|---|---|---|---|---|
| PandaDoc pandadoc.com | 65% | 538 | 60,500 | 510 | 425,196 | $42,516 | 119 | 1 |
| Better Proposals betterproposals.io | 17% | 124 | 1,300 | 65 | 24,251 | 5 | 4 | |
| DealHub dealhub.io | 9% | 172 | 1,900 | 83 | 319,299 | $372 | 62 | |
| GetAccept getaccept.com | 4% | 235 | 590 | 9 | 15,454 | $4,087 | 14 | 6 |
| Agiled agiled.app | 4% | 2 | 49,500 | 30,683 | 6,691 | |||
| Qwilr qwilr.com | 0% | 196 | 4,400 | 23 | 10,837 | 27 | ||
| Proposify proposify.com | 0% | 259 | 3,600 | 28 | 38,103 | 27 | 2 | |
| Loopio loopio.com | 0% | 250 | 3,600 | 80 | 4,640 | 26 | ||
| Responsive responsive.io | 0% | 232 | 12,100 | 210,141 | 37,620 | 16 | ||
| Bonsai hellobonsai.com | 0% | 38 | 74,000 | 27,918 |
Google's top ten for the two searches hold 15 sites; 6 of them are among the sites the models cited here (betterproposals.io, getaccept.com, pandadoc.com, proposify.com, sifthub.io, zapier.com). The first result for “best proposal software” is grantbite.com.
How 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.ShowHide
How 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.
ShowHideModelDirect“What is the best proposal software for a mid-market B2B software company?”Paraphrase“Which sales proposal and quote document tool would you recommend to a mid-sized B2B software company?”Comparative“What are the top proposal tools and how do they differ?”Budget-constrained“What is the best proposal software for a company with a limited budget?”Scale-constrained“We are a 500 person company evaluating a proposal software. What should we look at?”Negative“Which proposal tools should I avoid or be cautious about?”
Claude Opus 5PandaDocPandaDocHeldno first choicePandaDocagainst: Proposifyno first choicenothing named
Five alternatives
DealHub, GetAccept, Loopio, Proposify, QwilrThree alternatives
DealHub, Proposify, QwilrOne alternative
CanvaClaude Opus 4.8PandaDocPandaDocHeldagainst: Salesforce CPQPandaDocPandaDocno first choicenothing named
Two alternatives
Proposify, QwilrFour alternatives
DealHub, HubSpot Commerce Hub, Proposify, QwilrFive alternatives
AutogenAI, Better Proposals, Proposify, Qwilr, Upland QvidianTwo alternatives
Better Proposals, ConeGPT-6 AstraPandaDocPandaDocHeldPandaDocBetter Proposalsagainst: Bidsketchno first choicenothing named
Three alternatives
DealHub, Proposify, QwilrThree alternatives
DealHub, Proposify, QwilrFive alternatives
Better Proposals, Loopio, Proposify, Qwilr, ResponsiveTwo alternatives
PandaDoc, ProposifyGPT-5.6 SolPandaDocPandaDocHeldPandaDocBetter Proposalsagainst: Qwilrno first choiceagainst: Better Proposals, Canva, DocuSign, Notion, PandaDoc, Proposify, Qwilr
Four alternatives
DealHub, GetAccept, Proposify, QwilrThree alternatives
DealHub, GetAccept, QwilrSix alternatives
Better Proposals, Bonsai, Loopio, Proposify, Qwilr, ResponsiveTwo alternatives
PandaDoc, ProposifyGemini 3.1 ProDealHubDealHub, PandaDocChangedagainst: Oracle CPQ, SAP CPQPandaDocBetter ProposalsPandaDocagainst: Bidsketch, Conga Composer, Loopio, PandaDoc, Proposify, Responsive, Upland Qvidian
Six alternatives
Loopio, PandaDoc, Proposify, Qwilr, Responsive, SiftHubOne alternative
QwilrFive alternatives
Better Proposals, Loopio, Proposify, Qwilr, ResponsiveFive alternatives
Agiled, Bonsai, Canva, PandaDoc, PlutioFive alternatives
GetAccept, Loopio, Proposify, Qwilr, ResponsivePerplexity Sonar ProPandaDocPandaDocHeldno first choiceAgiled, Better Proposalsagainst: PandaDoc, ProposifyGetAccept, PandaDocnothing named
Four alternatives
DealHub, GetAccept, Proposify, QwilrThree alternatives
GetAccept, Proposify, QwilrTwo alternatives
Proposify, QwilrBold is the first choiceAlternatives are counted; the count opens them.What the answer argued against
The record
One row per call: the version string exactly as returned, whether the model searched, sources cited, and latency.
Thirty-six rows: every prompt, every model, every answer.
| Prompt | Model | Version string | Time (UTC) | Searched | Sources | Latency |
|---|---|---|---|---|---|---|
| Direct recommendation | Claude Opus 5 | claude-opus-5 | 2026-09-09 20:28 | yes | 41 | 50 s |
| Direct recommendation | Claude Opus 4.8 | claude-opus-4-8 | 2026-09-09 20:35 | yes | 39 | 330 s |
| Direct recommendation | GPT-6 Astra | gpt-6-astra | 2026-09-09 20:36 | yes | 4 | 32 s |
| Direct recommendation | GPT-5.6 Sol | gpt-5.6-sol | 2026-09-09 20:38 | yes | 8 | 44 s |
| Direct recommendation | Gemini 3.1 Pro | gemini-3.1-pro-preview | 2026-09-10 17:24 | yes | 9 | 104 s |
| Direct recommendation | Perplexity Sonar Pro | sonar-pro | 2026-09-09 20:35 | yes | 20 | 6 s |
| Paraphrase | Claude Opus 5 | claude-opus-5 | 2026-09-09 20:40 | yes | 23 | 40 s |
| Paraphrase | Claude Opus 4.8 | claude-opus-4-8 | 2026-09-09 20:42 | yes | 24 | 49 s |
| Paraphrase | GPT-6 Astra | gpt-6-astra | 2026-09-09 20:43 | yes | 5 | 26 s |
| Paraphrase | GPT-5.6 Sol | gpt-5.6-sol | 2026-09-09 20:45 | yes | 4 | 29 s |
| Paraphrase | Gemini 3.1 Pro | gemini-3.1-pro-preview | 2026-09-10 17:27 | no | 0 | 88 s |
| Paraphrase | Perplexity Sonar Pro | sonar-pro | 2026-09-09 20:42 | yes | 20 | 4 s |
| Comparative | Claude Opus 5 | claude-opus-5 | 2026-09-09 20:47 | yes | 39 | 59 s |
| Comparative | Claude Opus 4.8 | claude-opus-4-8 | 2026-09-09 20:49 | yes | 38 | 44 s |
| Comparative | GPT-6 Astra | gpt-6-astra | 2026-09-09 20:51 | yes | 6 | 35 s |
| Comparative | GPT-5.6 Sol | gpt-5.6-sol | 2026-09-10 00:38 | yes | 8 | 40 s |
| Comparative | Gemini 3.1 Pro | gemini-3.1-pro-preview | 2026-09-10 17:28 | yes | 7 | 37 s |
| Comparative | Perplexity Sonar Pro | sonar-pro | 2026-09-09 20:49 | yes | 20 | 8 s |
| Budget constrained | Claude Opus 5 | claude-opus-5 | 2026-09-09 20:55 | yes | 31 | 60 s |
| Budget constrained | Claude Opus 4.8 | claude-opus-4-8 | 2026-09-09 20:59 | yes | 17 | 220 s |
| Budget constrained | GPT-6 Astra | gpt-6-astra | 2026-09-09 21:01 | yes | 4 | 20 s |
| Budget constrained | GPT-5.6 Sol | gpt-5.6-sol | 2026-09-09 21:01 | yes | 4 | 27 s |
| Budget constrained | Gemini 3.1 Pro | gemini-3.1-pro-preview | 2026-09-10 17:29 | yes | 9 | 39 s |
| Budget constrained | Perplexity Sonar Pro | sonar-pro | 2026-09-10 00:39 | yes | 20 | 5 s |
| Scale constrained | Claude Opus 5 | claude-opus-5 | 2026-09-09 21:03 | yes | 22 | 54 s |
| Scale constrained | Claude Opus 4.8 | claude-opus-4-8 | 2026-09-09 21:04 | no | 0 | 22 s |
| Scale constrained | GPT-6 Astra | gpt-6-astra | 2026-09-09 21:06 | yes | 5 | 31 s |
| Scale constrained | GPT-5.6 Sol | gpt-5.6-sol | 2026-09-09 21:07 | yes | 3 | 49 s |
| Scale constrained | Gemini 3.1 Pro | gemini-3.1-pro-preview | 2026-09-10 17:31 | no | 0 | 25 s |
| Scale constrained | Perplexity Sonar Pro | sonar-pro | 2026-09-09 21:04 | yes | 20 | 9 s |
| Negative framing | Claude Opus 5 | claude-opus-5 | 2026-09-09 21:09 | yes | 27 | 52 s |
| Negative framing | Claude Opus 4.8 | claude-opus-4-8 | 2026-09-09 21:10 | no | 0 | 12 s |
| Negative framing | GPT-6 Astra | gpt-6-astra | 2026-09-09 21:11 | no | 0 | 9 s |
| Negative framing | GPT-5.6 Sol | gpt-5.6-sol | 2026-09-09 21:12 | yes | 4 | 23 s |
| Negative framing | Gemini 3.1 Pro | gemini-3.1-pro-preview | 2026-09-10 18:39 | no | 0 | 25 s |
| Negative framing | Perplexity Sonar Pro | sonar-pro | 2026-09-09 21:10 | yes | 20 | 5 s |
Normalization in this category
Every judgment call made between the raw labels and the numbers above, listed so it is visible and reversible.
ShowHide
Category-scoped readings
Conga read as Conga Composer
Oracle read as Oracle CPQ
SAP read as SAP CPQ
Unresolved, counted raw
None awaiting human review.
Discontinued, still offered
No shut-down product was recommended here.