Willing Appears in 5.7% of AI Answers. Here's Our Five-Step Plan to Improve Its AI Visibility.

Mark HuntleyBy Mark HuntleyFounder and CEO
9 minutes read

Key Takeaways

  • Willing was mentioned in 5.7% of benchmark answers but recommended in only 0.34%, showing a gap between visibility and endorsement.
  • Most mentions were neutral, which suggests the company is being named without being positioned as the preferred choice.
  • The latest monthly sample showed a sharp rise in mentions, but recommendations remained near zero.
  • The plan focuses on fact-checking, third-party citation review, owned-page updates, and content built around buyer questions.

Answer Capsule

In November 2026, Willing appeared in 17 of 298 AI answers included in the Online Estate Planning and Wills benchmark (5.70%). It received 1 recommendation (0.34%), with 1 Top 3 placement and 0 first-place recommendations. A mention means the company appeared in an answer; a recommendation means the answer affirmatively endorsed it.

Our plan compares the company with its competitors, checks conflicting AI claims against reliable sources, and identifies website pages, third-party sources and buyer questions to address. The historical results show how the figures changed across available months. Different monthly samples limit those comparisons, and conflicting AI claims require verification before corrections are proposed.

Current AI visibility

Questions This Section Answers

  • How do Willing mentions, recommendations and placements compare with its Online Estate Planning and Wills peers?

Willing recorded 17 mentions (5.70%) and 1 recommendation (0.34%) across 298 answers included in the benchmark. Top 3 placements numbered 1; first-place recommendations numbered 0. Framing among its mentions was 1 positive, 16 neutral and 0 negative.

Rank

Company

Mentions

Mention rate

Recommendations

Recommendation rate

Top 3

Top 3 rate

#1

#1 rate

1

LegalZoom

296

99.33%

253

84.90%

230

77.18%

84

28.19%

2

Trust & Will

289

96.98%

250

83.89%

238

79.87%

108

36.24%

3

Quicken WillMaker & Trust

238

79.87%

221

74.16%

157

52.68%

11

3.69%

4

FreeWill

214

71.81%

194

65.10%

80

26.85%

45

15.10%

5

Rocket Lawyer

207

69.46%

183

61.41%

25

8.39%

1

0.34%

6

GoodTrust

49

16.44%

41

13.76%

2

0.67%

0

0.00%

7

Fabric

15

5.03%

14

4.70%

8

2.68%

1

0.34%

8

Tomorrow

7

2.35%

6

2.01%

0

0.00%

0

0.00%

9

Wealth.com

24

8.05%

1

0.34%

0

0.00%

0

0.00%

9

Willing

17

5.70%

1

0.34%

1

0.34%

0

0.00%

Willing appears in a small share of the answers reviewed, and affirmative recommendations are rarer still. Most of its mentions carry neutral wording, so the company is being named without being endorsed. That gap between being seen and being chosen is the central issue this report addresses.

The leading competitors are named in nearly every answer and recommended in most of them. Willing's single recommendation and single shortlist placement sit far below that pattern. Closing this gap is not a matter of volume alone; the wording around the company matters as much as the frequency of its appearance.

What changed since last month

Questions This Section Answers

  • How did Willing counts and coverage differ across the available monthly snapshots?

Metric

Jul 2026

Aug 2026

Sep 2026

Oct 2026

Nov 2026

Mentions

0 / 297 (0.00%)

4 / 307 (1.30%)

6 / 338 (1.78%)

1 / 324 (0.31%)

17 / 298 (5.70%)

Recommendations

0 / 297 (0.00%)

3 / 307 (0.98%)

3 / 338 (0.89%)

0 / 324 (0.00%)

1 / 298 (0.34%)

Top 3 recommendations

0 / 297 (0.00%)

1 / 307 (0.33%)

0 / 338 (0.00%)

0 / 324 (0.00%)

1 / 298 (0.34%)

#1 recommendations

0 / 297 (0.00%)

0 / 307 (0.00%)

0 / 338 (0.00%)

0 / 324 (0.00%)

0 / 298 (0.00%)

From October 2026 to November 2026, Willing's mention count rose from 1 to 17, while its recommendation count rose from 0 to 1. The recommendation rate was 0.00% and 0.34% respectively.

The monthly record shows a sharp rise in mentions in the latest sample, while recommendations stayed close to zero. The earlier months were mostly quiet, with occasional small clusters of recommendations. The latest month is the first with a substantial mention count.

These are separate samples, and the answers included differ from month to month. The movement in mentions and the near-absence of recommendations should be read as two observations, not as one explaining the other. Whether the higher visibility persists is something only further monthly tracking can show.

AI recommendation trend

Observed recommendation rate (%), Jul 2026 to Nov 2026

0%0.25%0.5%0.75%1%Jul 2026Aug 2026Sep 2026Oct 2026Nov 20260.00%Jul 2026: 0.00%0.98%Aug 2026: 0.98%0.89%Sep 2026: 0.89%0.00%Oct 2026: 0.00%0.34%Nov 2026: 0.34%
  • Willing0.34%

Separate selected monthly samples. Missing points are unavailable, not zero. Provider/prompt equivalence is unverified; rate movement does not demonstrate causation.

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Step 1. Measure

Questions This Section Answers

  • What should the agency measure and verify first for Willing?

AI answers contained 0 conflicting claims about Willing: 0 critical, 0 high, 0 medium, 0 low. Of these, 0 were rated critical or high priority; the critical claims are included in that total. These ratings help prioritize fact-checking. They do not establish that a company or publisher made an error.

A visibility comparison would place Willing's appearance and recommendation pattern beside the leading competitors in a single scorecard, so the client can see where the gap is widest. That gives a shared starting point for setting priorities rather than relying on impressions.

The captured answers contained no conflicting claims about Willing to fact-check. That is a clean result, but it is a statement about this sample only. A scoped fact-review register would still be worth maintaining, so that any claim appearing in future answers can be checked against primary sources before anyone acts on it.

Step 2. Make the website consistent

Questions This Section Answers

  • Which recorded claim differences about Willing should be verified before proposed page edits?

No results are available for this part of the analysis.

Both columns quote AI answers, not verified company facts. Resolve the entity, date and source before deciding whether a correction is warranted; different dates can explain an apparent conflict.

No disputed claims about Willing surfaced in this round, so there is nothing to correct on the website at present. The useful work is preparatory: confirming the company's core facts, such as entity details, dates and service descriptions, against primary sources so that any future conflict can be resolved quickly.

Where a claim does appear later, the first step is to establish which entity it refers to and when it was made. Page briefs should be drafted only after that check, and only where the verified facts support a change. Ambiguous matches would stay out of the correction queue.

Step 3. Align the external narrative

Questions This Section Answers

  • Which cited third-party pages are relevant to fact review for Willing?

Cited page selected for review

Citation appearances in all captured answers

Answers mentioning the company

Conflicting claims linked to this page

https://cnbc.com/select/best-online-will-makers/

251

14

0

https://ncoa.org/product-resources/estate-planning/best-online-will-makers/

218

10

0

https://freewill.com/

140

9

0

https://trustandwill.com/

91

3

0

https://redcross.org/donations/ways-to-donate/planned-giving/make-a-will.html

45

3

0

https://smartasset.com/estate-planning/best-online-will-maker

23

3

0

These pages were selected because they relate to the company in the captured answers. Their current contents still need checking before any correction request. A page linked to a conflicting claim is not necessarily its cause, and the same answer may contribute to more than one row.

The cited pages most associated with Willing in the captured answers are third-party comparison and roundup articles, alongside competitor sites. Their current contents have not been checked, and a citation does not show that a page influenced an answer.

The proposed work is a focused review of the most relevant of these pages, checking what they currently say about Willing and whether anything is inaccurate or out of date. Where a genuine gap or error is confirmed, the agency would prepare an evidence-backed request to the publisher. Publishers control their own pages, so requests are framed as offers of accurate information, not demands.

Step 4. Optimize priority company pages

Questions This Section Answers

  • Which observed Willing website pages should receive review briefs?

No results are available for this part of the analysis.

The company's website was cited 0 times across 0 distinct page addresses; the table shows 0 pages selected for review. Zeros in the answer columns mean no matching answers were recorded. A cited page is not automatically a page that accompanied a recommendation.

No Willing page was cited in the captured answers, so there is no owned-page citation pattern to interpret yet. That absence is worth noting but should not be read as a verdict on the site's content.

Page briefs would be built from approved company facts and the questions buyers actually ask, then checked against what the site already covers. The aim is to give the site clear, verifiable answers that a reader or an AI system can use with confidence. Any brief would name its evidence source and require sign-off before publication.

Step 5. Publish around buyer questions

Questions This Section Answers

  • Which observed buyer questions support content briefs for Willing?

Question observed in the research

Benchmark answers to this question

Company mentions

Company recommendations

Who is the best person to write your will?

1

1

1

How much does a typical estate plan cost?

1

1

0

What is the best website to make a will?

5

1

0

best online power of attorney

1

1

0

best online will maker

2

1

0

best online will makers

1

1

0

best way to make a will online

1

1

0

best will maker

1

1

0

These are recorded answer observations, not search volume, verified demand, or proof of missing website content.

The recorded questions cluster around choosing a will maker, comparing costs and making a will online. Willing was mentioned in answers to several of these questions but recommended in only one. The pattern suggests the company is visible at the consideration stage without being the endorsed choice.

Content briefs would address these buyer questions directly, starting with a check of existing coverage so that new pages are proposed only where a real gap exists. Each brief would pair the question with approved facts and a clear, plain answer. These observations are recorded answer content, not evidence of search demand.

Our 90-day action plan

Questions This Section Answers

  • How should the agency sequence the proposed Willing work and judge completion?

Period

Deliverable

Completion criterion

Days 1–30

Baseline scorecard, scoped fact-review register and page/source shortlist

Each record has an owner, evidence requirement and review status

Days 31–60

Approved page briefs and justified publisher requests

Separate confirmed edits, no-change decisions, requests and responses

Days 61–90

Buyer-content briefs and a fresh scorecard

Record work completed separately from measured answer outcomes and comparability limits

The first month establishes the baseline scorecard, a scoped fact-review register and a shortlist of pages and sources to examine. Each record would carry an owner, the evidence required and a review status, so progress is visible and nothing is acted on without verification.

The second month produces approved page briefs and justified publisher requests, with confirmed edits, no-change decisions and responses logged separately. The third month adds buyer-question content briefs and a fresh scorecard. Completed work would be reported separately from measured answer outcomes, since publication does not guarantee a change in visibility.

Methodology

Questions This Section Answers

  • How are Willing answer metrics and citation populations defined?

This report covers 2026-11. The exact dates when the original AI answers were collected have not been verified. The visibility rates use 298 answers that met the benchmark's inclusion rules. A company is recommended only when the answer both endorses it and uses positive wording. Top 3 and first-place counts are part of those recommendations, not extra recommendations.

An answer can mention or recommend several companies, so company counts cannot be added to find the number of distinct answers. The net sentiment score is positive minus negative mentions, divided by all company mentions; it describes answer wording, not customer satisfaction.

The wider citation analysis covers 800 captured answers and 6007 appearances of cited URLs. Citation appearances across all captured answers differ from the number of benchmark answers citing a page and the number that also recommend a company. The current contents of cited pages and disputed company claims still need independent verification.

Monthly sample coverage:

Reporting month

Answers included

AI services covered

Services

Jul 2026

297

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

Aug 2026

307

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

Sep 2026

338

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

Oct 2026

324

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

Nov 2026

298

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

The answer samples differ between months. These comparisons show how the recorded results changed; they do not establish why they changed.

The answers were collected under the benchmark's inclusion rules, and the exact collection dates have not been verified. A company counts as recommended only when an answer endorses it with positive wording; shortlist and first-place placements sit inside those recommendations rather than adding to them.

Answers can name several companies, so company counts do not sum to a number of answers. Monthly samples differ, and comparisons describe recorded movement without establishing its cause. Cited pages and any disputed claims still require independent verification.

Our first three priorities

The first priority is to keep the fact-review register current even though this round produced no conflicts, so that Willing's core facts are confirmed against primary sources and ready for any future discrepancy. The second is a focused review of the third-party comparison pages most associated with the company, followed by evidence-backed requests only where a real inaccuracy is confirmed.

The third is buyer-question content, starting with the will-maker and cost questions where Willing appears without being endorsed. Each piece would be briefed from approved facts and checked against existing coverage first. Together these give the client a verified foundation, a clearer external picture and content aimed at the moments where the choice is made.

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Understanding AI search visibility.

AI search experiences create answers by pulling information from many places online and summarizing it into a single response.

What Is AI Citation Intelligence?
AI citation intelligence is the process of measuring where AI platforms source their information and how frequently a brand is mentioned or referenced in AI-generated responses. Because LLMs synthesize across multiple sources, the sites and brands that appear repeatedly tend to influence how a topic or company is framed. This practice focuses on identifying which sources shape AI outputs and tracking brand visibility across different AI systems.
What Is Citation Architecture?
Citation architecture describes the set of sources that consistently inform how AI systems talk about a brand, product, or topic. LLMs draw from websites, articles, forums, and public discussion, and the sources they rely on most often become the backbone of their answers. Building strong citation architecture means ensuring that accurate, credible, high authority sources are the ones most likely to shape the way AI tools summarize and recommend a brand.
What Is Generative Engine Optimization?
Generative engine optimization (GEO) is the practice of improving the chances that AI systems use and cite your brand or content when generating answers. While traditional SEO is centered on ranking pages in search results, GEO focuses on how LLMs retrieve, interpret, and combine information when responding to a question. The objective is to strengthen the content and sources AI systems rely on, so your brand is treated as a trusted reference in AI responses.
What Is AI Share of Voice?
AI share of voice tracks how often a brand appears in AI-generated answers compared with competitors in the same category. It reflects visibility across AI platforms such as ChatGPT, Gemini, Claude, and Perplexity. Monitoring AI share of voice helps organizations see whether AI systems consistently include and recommend their brand for key queries or whether competitor brands are showing up more often.

About The Author

Mark Huntley

Mark Huntley

Founder and CEO

Mark Huntley, J.D. is founder of CiteWorks Studio, a strategic advisory focused on visibility, authority, and recommendation presence in AI-shaped search environments. His work centers on embedding-level GEO, vector optimization, and cosine gap engineering — helping brands align their digital presence with the retrieval systems that increasingly shape discovery, interpretation, and choice.

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