HIGH SALIENCE / RESEARCH / E-SIGNATURE TEARDOWN
TEARDOWN 18 · PUBLISHED SEPTEMBER 26, 2026 · DATASET INCLUDED
100 Questions, Eighteenth Category: E-Signature, Where DocuSign Is the Default Pick, Adobe Is the Pick for PDF Work, and Dropbox Sign Is the Way Out
Eighteenth category, same method: 100 e-signature software queries, ChatGPT with web search on, every answer coded by two independent AI readers working from a published protocol, Google's top ten as a control. DocuSign is the default: named in 67 answers, picked as the answer's own choice in 62, and picked in 19 of the 20 direct advice questions. Adobe Acrobat Sign is picked in 48, most often on a condition: your work is PDF-heavy, or you already use Adobe. When the question is how to replace DocuSign, the pick is usually Dropbox Sign. And Google put adobe.com in its top ten for one question out of 100, while ChatGPT cited it in 35 answers.
01Method
Same query structure, same coding, one new category.
Queries: 100 e-signature software queries built from the same templates as the earlier teardowns: 30 category, 30 comparison, 20 alternative and 20 recommendation. The full list is in the dataset.
Surface: ChatGPT with web search forced on, logged out, United States, English, via the DataForSEO scraper, one run per query, collected September 26, 2026.
Control: Google's top ten organic results for the same queries in the same window, via the DataForSEO SERP API at depth 20 and truncated to the first ten organic results.
Coding: every answer was coded by two independent AI readers (Claude agents working blind from a written protocol), with a third settling disagreements. They were not people. Each brand named was coded picked (the answer's own verdict: "my pick", "choose X if", a shortlist it tells you to act on, the #1 of its ranking), recommended (assigned to a stated case or fit, such as "best for small teams", without being the answer's verdict), listed (named as an option, no fit given), passing (named but not offered as an option) or anchor (the brand being replaced in an "alternatives" query), against a 45-brand dictionary fixed after collection, before the final coding run (every change is listed in DICTIONARY_CHANGES.md), under codebook v2.0. "Recommended" in the tables includes picked brands. The two readers agreed on 96.1% of brand codes in this teardown (98.8% at the recommended level). Cited URLs were deduplicated to their domain and classed as first-party or third-party. The third reader decided 16 of the 410 brand codes in this teardown. A rules-based first pass (the codebook v1.6 rules) agreed with the final codes on 95.9 percent at the recommended level; only the reader codes are published. The readers also coded six brand mentions that no dictionary alias matched (named by meaning or only by a web address); those rows are in the dataset.
Collection note: the ChatGPT answers and the Google controls were collected on September 26, 2026 through the DataForSEO standard queue, with raw responses saved exactly as returned (the raw files carry UTC timestamps, early September 27). No task failed and none was re-run. Six answers came back as a single sentence that announces a comparison and stops, with no sources; they are kept as returned and counted as answered. After collection and before the final coding run, two vendor domains were added to the dictionary, dropboxsign.com for Dropbox Sign and authentisign.com for Authentisign, which moved five citation events from third-party to first-party and changed no brand mention. Adobe Acrobat Sign also matches "Adobe Acrobat", because answers often name Acrobat for its built-in signing; in 8 answers that is the only match and the product named is the PDF editor (Acrobat Pro, Acrobat Reader or Fill & Sign), and the readers coded it as Adobe, picked in 6 and recommended in 2. Without those 8 answers Adobe would be named in 53, recommended in 53 and picked in 42, just behind Dropbox Sign's 55, 54 and 44. Three aliases that are also ordinary words or names (Signable, Ironclad, Clio) match only when capitalized. Both dictionaries and the list of changes ship with the dataset.
One run per query, so this is a teardown, not the benchmark. Frequencies describe this window only. Absence means not observed in this sample, never zero visibility.
02Findings
One default, one conditional pick, one exit, and a reading list Google does not rank.
| Brand | Appears in | Recommended in | Picked in | Picked share of appearances |
|---|---|---|---|---|
| DocuSign | 67 | 65 | 62 | 93% |
| Adobe Acrobat Sign | 61 | 61 | 48 | 79% |
| Dropbox Sign | 55 | 54 | 44 | 80% |
| PandaDoc | 44 | 44 | 35 | 80% |
| SignNow | 32 | 32 | 25 | 78% |
| SignWell | 19 | 18 | 17 | 89% |
| Zoho Sign | 14 | 14 | 11 | 79% |
Each linked brand has its own page: how ChatGPT recommends every brand in this dataset, with positioning labels, head-to-head results and sources.
Out of 100 answers, codebook v2.0. "Picked" means the answer itself chose the brand as its verdict, overall or for a case. "Recommended" means the answer assigned the brand to a stated case or fit, and includes picked brands. "Appears" adds brands named as an option with no fit. The brand being replaced in an "alternatives" query is excluded from all columns.
DocuSign is the default pick
DocuSign is named in 67 of 100 answers, recommended in 65 and picked as the answer's own choice in 62. All 20 direct advice questions produced a pick, and DocuSign was among the picks in 19; the exception is a freelancer sending a few contracts a month, where the pick is Dropbox Sign. It is named in 51 of the 72 questions that do not mention it, and picked in 46. Behind it: Adobe Acrobat Sign, named in 61 answers and picked in 48; Dropbox Sign, 55 and 44; PandaDoc, 44 and 35; SignNow, 32 and 25. SignWell is picked in 17 of the 19 answers that name it.
Adobe is the pick for PDF work
Adobe Acrobat Sign has the widest gap in the category between being recommended and being picked: recommended in 61 answers, picked in 48. In 12 of the 13 answers that recommend it without picking it, the fit it is given is PDF work or an existing Adobe setup, as in "best if you already use Adobe", and 38 of its 48 picks carry the same condition, as in "Choose Adobe if PDF-heavy". Dropbox Sign has the next widest gap, recommended in 54 and picked in 44; when it is described but not picked, the label is usually simple or low-cost signing. Adobe's second place also rests on the alias "Adobe Acrobat": in 8 answers the only Adobe product named is the Acrobat PDF editor, and without them Adobe is named in 53 answers and picked in 42, behind Dropbox Sign.
Industry questions still go to DocuSign
Twenty questions name an industry or a type of buyer: real estate, law, healthcare, insurance, accounting, construction, government, nonprofits, HR, property management, sales and freelancers. Every one of them produced a pick. DocuSign is picked in all 20 and Adobe Acrobat Sign in 18. Eleven of the 20 pick only from DocuSign, Adobe, Dropbox Sign and PandaDoc. An industry specialist is picked in four: dotloop and SkySlope in both real estate questions, Clio for a law firm, Proposify for a sales team sending proposals. The accountants answer puts SafeSend first on its shortlist, with TaxDome and Canopy further down; all three are tax and practice tools outside the dictionary.
Replacing DocuSign means Dropbox Sign
Ten of the 20 alternative questions ask how to replace DocuSign, including cheaper, free, simpler, open source, self-hosted and developer versions of the question. Dropbox Sign is picked in 7 of those 10, Adobe Acrobat Sign and Zoho Sign in 4 each. The open source and self-hosted questions go to DocuSeal, Documenso and OpenSign. In the head-to-heads, 25 of 30 answers pick every brand named. One picks a single side, DocuSign over Adobe Sign for real estate. The other four were not real answers: the model replied with one sentence announcing a comparison and stopped. Across all 100 questions, 11 answers pick nothing from the dictionary: those four, two more one-sentence replies, and five full answers. Four of those describe the options without a verdict; the fifth, on the free way to sign a PDF, picks PDF24, which is not in the dictionary.
Picked without ranking
Of the 308 picks, 229 were for brands whose own website did not rank in Google's top ten for the question, 74 percent. Adobe is the extreme case. Google put adobe.com in its top ten for one of the 100 questions, and for none of the 48 where ChatGPT picked Adobe Acrobat Sign. ChatGPT cited adobe.com in 35 answers, 30 of them to questions that do not mention Adobe, and picked Adobe in 30 of the 35. Dropbox Sign's own site ranked for 3 of its 44 picks. Google's own top ten is 70 percent third-party pages; among the earlier teardowns only payroll gave vendor sites a larger share.
PandaDoc writes the comparisons
Across 100 answers there were 302 citation events to 92 domains. Vendors' own sites took 191 of them, 63 percent, and 44 answers cited nothing but vendor pages. docusign.com is the most-cited domain, in 40 answers, followed by pandadoc.com in 37 and adobe.com in 35. PandaDoc's citations work differently from the others: 27 of its 37 are in answers to questions that never mention PandaDoc, and 25 cite its blog, mainly two pages, a guide to the best electronic signature software (17 answers) and a DocuSign versus Adobe Sign versus HelloSign comparison (15). PandaDoc is picked in 28 of the 37 answers that cite it. pandadoc.com is also in Google's top ten for 40 of the questions, more than any other vendor. The most-cited third parties are small comparison sites: dupple.com in 6 answers, five of them to the same page, and esigncompare.com in 5, neither in Google's top ten for any of them. Review sites took 5 percent of citations. Reddit is in Google's top ten for 86 of the 100 questions, yet Reddit and Wikipedia have zero ChatGPT citations, as in every earlier teardown.
Seventy-three of the 302 citation events involved a domain that also sat in Google's top ten for that query, 24 percent.
0318 categories, side by side
Same rulebook, every category so far.
| Measure (codebook v2.0) | Project management, Sept 8 | CRM, Sept 17 | Email marketing, Sept 17 | Help desk, Sept 17 | Accounting, Sept 17 | Payment processing, Sept 17 | Payroll, Sept 21 | HR software, Sept 26 | Applicant tracking, Sept 26 | Password managers, Sept 26 | Endpoint security, Sept 26 | Business intelligence, Sept 26 | Data warehouse and ETL, Sept 26 | Ecommerce platforms, Sept 26 | Website builders, Sept 26 | Scheduling, Sept 26 | Video conferencing, Sept 26 | E-signature, Sept 26 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Recommendations per category answer (average) | 5.9 | 4.3 | 5.0 | 5.5 | 4.3 | 4.2 | 4.6 | 5.0 | 4.5 | 3.4 | 4.7 | 5.0 | 4.5 | 4.3 | 4.3 | 3.4 | 4.0 | 4.6 |
| Answers with no recommended dictionary brand | 1 of 100 | 5 of 100 | 1 of 100 | 1 of 100 | 0 of 100 | 5 of 100 | 1 of 100 | 6 of 100 | 5 of 100 | 3 of 100 | 3 of 100 | 3 of 100 | 2 of 100 | 3 of 100 | 0 of 100 | 5 of 100 | 1 of 100 | 6 of 100 |
| Answers with no pick (the answer's own verdict) | 2 of 100 | 11 of 100 | 2 of 100 | 4 of 100 | 9 of 100 | 22 of 100 | 19 of 100 | 17 of 100 | 12 of 100 | 7 of 100 | 7 of 100 | 5 of 100 | 3 of 100 | 7 of 100 | 2 of 100 | 8 of 100 | 8 of 100 | 11 of 100 |
| Most-recommended brand: appears / recommended | Asana 73 / 73 | HubSpot 75 / 74 | Mailchimp 58 / 56 | Zendesk 70 / 69 | QuickBooks 75 / 73 | Stripe 70 / 68 | Gusto 73 / 73 | Rippling 58 / 57 | Workable 53 / 52 | Bitwarden 84 / 82 | Microsoft Defender 68 / 67 | Power BI 75 / 73 | Snowflake 50 / 50 | Shopify 75 / 75 | Wix 70 / 70 | Calendly 57 / 56 | Zoom 76 / 73 | DocuSign 67 / 65 |
| Most-picked brand: appears / picked | Asana 73 / 70 | HubSpot 75 / 69 | Mailchimp 58 / 44 | Zendesk 70 / 61 | QuickBooks 75 / 65 | Stripe 70 / 54 | Gusto 73 / 61 | Rippling 58 / 50 | Workable 53 / 47 | Bitwarden 84 / 78 | Microsoft Defender 68 / 62 | Power BI 75 / 69 | Snowflake 50 / 46 | Shopify 75 / 69 | Wix 70 / 62 | Calendly 57 / 51 | Zoom 76 / 63 | DocuSign 67 / 62 |
| Head-to-head queries recommending every named brand | 30 of 30 | 28 of 30 | 30 of 30 | 29 of 30 | 26 of 30 | 28 of 30 | 30 of 30 | 28 of 30 | 29 of 30 | 28 of 30 | 30 of 30 | 29 of 30 | 28 of 30 | 28 of 30 | 30 of 30 | 29 of 30 | 30 of 30 | 26 of 30 |
| Head-to-head queries picking every named brand | 30 of 30 | 23 of 30 | 29 of 30 | 29 of 30 | 25 of 30 | 19 of 30 | 21 of 30 | 21 of 30 | 29 of 30 | 27 of 30 | 29 of 30 | 29 of 30 | 28 of 30 | 27 of 30 | 29 of 30 | 29 of 30 | 26 of 30 | 25 of 30 |
| Recommendation-intent queries with a dictionary recommendation | 19 of 20 | 18 of 20 | 20 of 20 | 20 of 20 | 20 of 20 | 19 of 20 | 20 of 20 | 18 of 20 | 20 of 20 | 19 of 20 | 19 of 20 | 20 of 20 | 20 of 20 | 19 of 20 | 20 of 20 | 19 of 20 | 19 of 20 | 20 of 20 |
| Recommendation-intent queries with a pick | 19 of 20 | 18 of 20 | 20 of 20 | 20 of 20 | 19 of 20 | 18 of 20 | 20 of 20 | 18 of 20 | 20 of 20 | 19 of 20 | 19 of 20 | 20 of 20 | 20 of 20 | 19 of 20 | 20 of 20 | 19 of 20 | 19 of 20 | 20 of 20 |
| Recommended mentions where the brand does not rank in Google's top 10 | 398 of 468 (85%) | 269 of 387 (70%) | 313 of 419 (75%) | 350 of 445 (79%) | 206 of 368 (56%) | 294 of 360 (82%) | 202 of 383 (53%) | 310 of 405 (77%) | 333 of 388 (86%) | 218 of 304 (72%) | 273 of 369 (74%) | 355 of 401 (89%) | 360 of 426 (85%) | 313 of 376 (83%) | 324 of 376 (86%) | 241 of 325 (74%) | 298 of 349 (85%) | 282 of 368 (77%) |
| Picked mentions where the brand does not rank in Google's top 10 | 349 of 416 (84%) | 226 of 330 (68%) | 270 of 370 (73%) | 291 of 380 (77%) | 141 of 279 (51%) | 170 of 222 (77%) | 113 of 246 (46%) | 232 of 311 (75%) | 261 of 311 (84%) | 163 of 241 (68%) | 231 of 319 (72%) | 292 of 336 (87%) | 303 of 365 (83%) | 227 of 285 (80%) | 262 of 309 (85%) | 200 of 276 (72%) | 227 of 271 (84%) | 229 of 308 (74%) |
| Google top 10 that is third-party pages | 746 of 1,000 (75%) | 710 of 1,000 (71%) | 720 of 1,000 (72%) | 714 of 1,000 (71%) | 743 of 1,000 (74%) | 787 of 1,000 (79%) | 653 of 1,000 (65%) | 820 of 1,000 (82%) | 871 of 1,000 (87%) | 866 of 1,000 (87%) | 778 of 1,000 (78%) | 823 of 999 (82%) | 777 of 1,000 (78%) | 868 of 1,000 (87%) | 906 of 1,000 (91%) | 780 of 999 (78%) | 873 of 1,000 (87%) | 697 of 1,000 (70%) |
| Citation events to vendors' own sites | 216 of 362 (60%) | 136 of 320 (42%) | 193 of 367 (53%) | 152 of 345 (44%) | 125 of 302 (41%) | 161 of 301 (53%) | 192 of 314 (61%) | 167 of 325 (51%) | 139 of 311 (45%) | 201 of 292 (69%) | 149 of 266 (56%) | 190 of 274 (69%) | 197 of 267 (74%) | 194 of 277 (70%) | 189 of 331 (57%) | 137 of 296 (46%) | 170 of 280 (61%) | 191 of 302 (63%) |
| Answers citing only vendor pages | 50 of 100 | 40 of 100 | 37 of 100 | 27 of 100 | 34 of 100 | 47 of 100 | 49 of 100 | 34 of 100 | 30 of 100 | 65 of 100 | 44 of 100 | 60 of 100 | 60 of 100 | 55 of 100 | 41 of 100 | 42 of 100 | 52 of 100 | 44 of 100 |
| Share of citations in the 10 most-cited domains | 54% | 40% | 42% | 45% | 55% | 58% | 55% | 46% | 44% | 72% | 58% | 62% | 60% | 61% | 54% | 35% | 54% | 57% |
| Citation events whose domain is in Google's top 10 | 83 of 362 (23%) | 83 of 320 (26%) | 97 of 367 (26%) | 80 of 345 (23%) | 99 of 302 (33%) | 98 of 301 (33%) | 134 of 314 (43%) | 85 of 325 (26%) | 59 of 311 (19%) | 78 of 292 (27%) | 72 of 266 (27%) | 44 of 274 (16%) | 54 of 267 (20%) | 56 of 277 (20%) | 51 of 331 (15%) | 63 of 296 (21%) | 43 of 280 (15%) | 73 of 302 (24%) |
| Reddit and Wikipedia citations | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
All columns are coded under codebook v2.0 by two independent AI readers per answer; the project management column is the September 8 dataset recoded under it. Each teardown is one run per query in its own window, so differences between columns mix category with collection date.
04What this changes
Four things, in order.
Ranking and being picked are different jobs. adobe.com ranked for one question and was cited in 35 answers, and Adobe Acrobat Sign was picked in 48 answers without once ranking for the question asked. Measure the two separately.
Know which condition you are picked for. Adobe is picked in 48 answers, and 38 of those picks come with the same condition: PDF-heavy work or an existing Adobe setup. A brand the model ties to one condition is picked when the buyer fits it and described, not picked, when the buyer does not.
Someone is writing your comparison page. pandadoc.com was cited in 27 answers to questions that never mention PandaDoc, mostly through one best-of guide and one three-way comparison of its competitors. If a competitor publishes the page that compares you, that page is part of how the model describes you.
Own the exit from the leader. When buyers ask how to replace DocuSign, the model sends most of them to one brand: Dropbox Sign is picked in 7 of 10 answers. For a challenger, "DocuSign alternative" questions are where the choice is made.
05Limitations
What this teardown cannot tell you.
One run per query means answer variance is unmeasured; Benchmark 01 runs each query three times across three surfaces. The teardowns are collected on different days, so differences between categories mix the category with the date. The brand dictionary covers the general e-signature software market and deliberately excludes vertical tools, so their appearances are described in prose and not counted. The readers are AI models, not people: they follow a written protocol and agree with each other closely, but a shared blind spot would not show up as disagreement. The line between picked and recommended is a judgment, documented in the protocol with examples. Sentiment is not coded. No vendor-tool cross-check was read for this category. Google's control counts a brand as ranking only when its own domain is in the top ten; a listicle that features the brand does not count. One run per question, one day, United States, English, logged out. Answers vary between runs, so these are frequencies for this sample. Six of the 100 answers were one-sentence stubs with no content; they count as answered, so the no-pick and no-citation figures include them. Adobe's counts include 8 answers that name only the Acrobat PDF editor; without them Adobe is named in 53 answers and picked in 42. The share of Adobe picks that carry a PDF or Adobe condition (38 of 48) is counted from the readers' stated reasons, not from a separate code.
06Dataset
Check it, don't believe it.
Every number above can be recomputed from these files. CC BY 4.0: use them, cite the page.
- queries.csv: the 100 queries with intent labels.
- brands.csv: the 45-brand dictionary with aliases and canonical domains.
- mentions.csv: 410 coded brand mentions with position, type, a 0/1 picked column and whether the brand's domain was in Google's top ten.
- citations.csv: 302 citation events with domain class and Google overlap.
- observations.csv: one row per query with brand, recommendation, citation and control counts.
- dictionary-changes.md: the two domain additions made after collection, before the final coding run
- brands-original.csv: the dictionary as first drafted, before those additions
- coder-notes.md: coding method and reader agreement, the judgment calls that matter for this category, brands the readers added, and dictionary notes
- codebook.md: the rulebook, with dated amendments through v2.0.
- reader-protocol.md: the written protocol both readers coded against (codebook v2.0).
- picked_stats.json: the picked-level figures.
The earlier teardowns: Teardown 01, project management, Teardown 02, crm, Teardown 03, email marketing, Teardown 04, help desk, Teardown 05, accounting, Teardown 06, payment processing, Teardown 07, payroll, Teardown 08, hr software, Teardown 09, applicant tracking, Teardown 10, password managers, Teardown 11, endpoint security, Teardown 12, business intelligence, Teardown 13, data warehouse and etl, Teardown 14, ecommerce platforms, Teardown 15, website builders, Teardown 16, scheduling, Teardown 17, video conferencing.
Eighteen categories, and the reading list is still the story.
In e-signature the model reads the vendors' own sites, including one vendor's comparisons of its competitors and a vendor site Google barely ranks, and it picks brands on conditions: Adobe for PDF work, Dropbox Sign for leaving DocuSign. Finding out what the model is reading for your category, and which condition it picks you for, is the first thing a Category Salience Brief does, with a query set you approve first.