Network Solutions Appears in 16.9% of AI Answers. Here's Our Five-Step Plan to Improve Its AI Visibility.

Mark HuntleyBy Mark HuntleyFounder and CEO
10 minutes read

Key Takeaways

  • Network Solutions is mentioned more often than it is recommended, which is the main visibility gap.
  • The November sample shows 105 mentions and just 1 recommendation, with no first-place recommendations.
  • Priority work starts with a baseline scorecard, fact review, and verification of cited external sources.
  • The company’s own blog pages and common buyer questions are the main content areas to brief next.

Answer Capsule

In November 2026, Network Solutions appeared in 105 of 622 AI answers included in the Domain Registrars benchmark (16.88%). It received 1 recommendation (0.16%), 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 Network Solutions mentions, recommendations and placements compare with its Domain Registrars peers?

Network Solutions recorded 105 mentions (16.88%) and 1 recommendation (0.16%) across 622 answers included in the benchmark. Top 3 placements numbered 1; first-place recommendations numbered 0. Framing among its mentions was 1 positive, 87 neutral and 17 negative.

Rank

Company

Mentions

Mention rate

Recommendations

Recommendation rate

Top 3

Top 3 rate

#1

#1 rate

1

Porkbun

491

78.94%

380

61.09%

330

53.05%

118

18.97%

2

Namecheap

615

98.87%

376

60.45%

328

52.73%

121

19.45%

3

Squarespace

358

57.56%

146

23.47%

61

9.81%

10

1.61%

4

Dynadot

221

35.53%

130

20.90%

37

5.95%

1

0.16%

5

GoDaddy

586

94.21%

127

20.42%

76

12.22%

10

1.61%

6

IONOS

155

24.92%

45

7.23%

14

2.25%

4

0.64%

7

Name.com

466

74.92%

18

2.89%

10

1.61%

3

0.48%

8

Domain.com

615

98.87%

13

2.09%

1

0.16%

0

0.00%

9

Network Solutions

105

16.88%

1

0.16%

1

0.16%

0

0.00%

Network Solutions appears in a modest share of the answers reviewed, yet almost none of those appearances carry an affirmative recommendation. The company is named far more often than it is endorsed, and its single shortlist placement sits within that thin recommendation base rather than adding to it. For a registrar competing against names that are recommended routinely, this is the central commercial problem: being seen is not the same as being chosen.

The framing of mentions leans heavily neutral, with negative wording outweighing positive. That pattern suggests answers treat Network Solutions as a known option rather than a preferred one. The agency would treat the recommendation gap, not the mention count, as the priority to investigate and address.

What changed since last month

Questions This Section Answers

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

Metric

Oct 2026

Nov 2026

Mentions

121 / 645 (18.76%)

105 / 622 (16.88%)

Recommendations

2 / 645 (0.31%)

1 / 622 (0.16%)

Top 3 recommendations

0 / 645 (0.00%)

1 / 622 (0.16%)

#1 recommendations

0 / 645 (0.00%)

0 / 622 (0.00%)

Only months with verified results are shown. Monthly sample coverage is listed in Methodology.

From October 2026 to November 2026, Network Solutions' mention count fell from 121 to 105, while its recommendation count fell from 2 to 1. The recommendation rate was 0.31% and 0.16% respectively.

Between the two reporting months, both the mention count and the recommendation count moved downward, and a shortlist placement appeared where none had been recorded before. The first-place count stayed at zero in both months. These are separate selected samples, so the movement describes what was recorded rather than a trend with an established cause.

The comparability limit matters here: a different answer total does not explain why counts or rates changed. The agency would track the next months before drawing conclusions, and would focus on whether recommendations begin to appear at all.

AI recommendation trend

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

  • Network Solutions-0.15 pp
    Oct 20260.31%
    Nov 20260.16%

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 Network Solutions?

AI answers contained 0 conflicting claims about Network Solutions: 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.

No conflicting claims about Network Solutions were recorded in the captured answers, so there is no fact-check queue to work through at present. That is a clean starting position, but it is also a thin one: with so few claims to examine, the measurement work should establish a baseline the client can compare against as answer coverage grows.

A visibility comparison against the recommended competitors would show where Network Solutions is named but not endorsed, and a standing list of claims to verify would keep future fact-checking orderly. The agency would set both up as proposed work, with each record assigned an owner and an evidence requirement.

Step 2. Make the website consistent

Questions This Section Answers

  • Which recorded claim differences about Network Solutions 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 results are available for this part of the analysis, so there are no disputed topics to brief against yet. The agency would not treat that absence as confirmation that the website is accurate; it means the comparison has not been run.

Where claims do surface later, both sides of any apparent conflict would be quoted from AI answers rather than treated as verified company facts. The entity, date and source would be resolved first, since different dates can explain an apparent conflict. Only then would a conditional page brief be proposed, and any correction would require current primary-source verification.

Step 3. Align the external narrative

Questions This Section Answers

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

Cited page selected for review

Citation appearances in all captured answers

Answers mentioning the company

Conflicting claims linked to this page

https://cloudflare.com/application-services/solutions/low-cost-domain-names/

121

16

0

https://en.wikipedia.org/wiki/Network_Solutions

2

1

0

https://gartner.com/reviews/product/network-solutions-domains

2

1

0

https://larryludwig.com/network-solutions-review/

2

1

0

https://facebook.com/NetworkSolutions/

1

1

0

https://instagram.com/networksolutionsbrand/

1

1

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 selected for review are a mixed set: a Cloudflare resource page, the Wikipedia entry, a Gartner review page, an independent review blog and the company's own social profiles. Citation volume is concentrated on the Cloudflare page, but a citation does not establish that the source influenced the answer, and none of these pages is linked to a conflicting claim.

The agency would check each page's current contents before proposing anything, then prepare evidence-backed requests only where a specific, verifiable improvement is identified. Publisher control and publisher error are not assumed; a request may reasonably end in a no-change decision.

Step 4. Optimize priority company pages

Questions This Section Answers

  • Which observed Network Solutions website pages should receive review briefs?

Company website page

Citation appearances in all captured answers

Benchmark answers citing the page

Recommending answers citing the page

https://networksolutions.com/blog/best-domain-name-providers/

32

30

0

https://networksolutions.com/blog/cheapest-domain-registars/

26

18

0

https://networksolutions.com/blog/how-to-buy-a-domain-name/

20

20

0

https://networksolutions.com/blog/how-much-does-domain-name-cost/

16

15

0

https://networksolutions.com/blog/is-my-domain-name-available/

10

10

0

https://networksolutions.com/domains

7

7

0

https://networksolutions.com/blog/what-is-a-domain-registrar/

5

5

0

https://networksolutions.com/blog/alternatives-to-godaddy-website-builder/

4

0

0

The company's website was cited 158 times across 35 distinct page addresses; the table shows 8 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.

The company's own blog carries most of its citation appearances, with the domain cost and provider-comparison articles drawing the most attention. Notably, none of the selected pages appears in an answer that recommends the company, which fits the wider pattern of being cited without being endorsed. A cited page is not automatically a page that accompanied a recommendation.

The agency would prepare page briefs for the priority articles using approved facts and the questions buyers actually ask, checking existing coverage before proposing anything new. The briefs would aim to make the pages more useful to readers, with any effect on answer outcomes measured separately rather than promised.

Step 5. Publish around buyer questions

Questions This Section Answers

  • Which observed buyer questions support content briefs for Network Solutions?

Question observed in the research

Benchmark answers to this question

Company mentions

Company recommendations

How do I create my own domain?

1

1

1

How can I purchase a domain name?

2

2

0

What is the best domain name service?

2

2

0

What is the best domain website?

5

2

0

What is the best website for domain names?

2

2

0

.studio domain

1

1

0

Are domains the same price everywhere?

1

1

0

Can you actually buy a domain name?

1

1

0

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

The recorded questions cluster around practical buying decisions: how to purchase a domain, what a domain costs, whether prices differ between providers, and which service is best. Network Solutions is mentioned in answers to most of these questions but recommended in only one, the question about creating a domain. These are recorded answer observations, not search volume or proof of missing content.

The agency would check existing coverage first, then draft buyer-question briefs for the gaps that remain, using approved facts and plain answers. The goal is content that helps a buyer decide, not content that repeats the company's own marketing claims.

Our 90-day action plan

Questions This Section Answers

  • How should the agency sequence the proposed Network Solutions 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, each with an owner, an evidence requirement and a review status. The second month produces approved page briefs and justified publisher requests, with confirmed edits, no-change decisions, requests and responses recorded separately.

The third month delivers buyer-content briefs and a fresh scorecard. Completed work would be reported separately from measured answer outcomes, with comparability limits stated alongside. Nothing in the plan guarantees a visibility gain; the plan makes the work auditable and the results honest.

Methodology

Questions This Section Answers

  • How are Network Solutions 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 622 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 5394 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

Oct 2026

645

6

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

Nov 2026

622

6

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

Reliable results for July 2026 are unavailable. This is a gap in the history, not a result of zero. Reliable results for August 2026 are unavailable. This is a gap in the history, not a result of zero. Reliable results for September 2026 are unavailable. This is a gap in the history, not a result of zero.

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

The report covers a single month, and the exact dates when the original answers were collected have not been verified. A company counts as recommended only when an answer endorses it with positive wording, and shortlist and first-place counts sit inside those recommendations rather than adding to them. Answers can mention several companies, so company counts cannot be summed into distinct answers.

Monthly samples differ, so comparisons show how recorded results changed, not why. The current contents of cited pages and any disputed claims still need independent verification.

Our first three priorities

First, establish the baseline scorecard and a standing fact-review register, so the near-absence of recommendations is tracked deliberately rather than noticed late. Second, prepare page briefs for the priority blog articles, using approved facts and the buyer questions recorded in the research, after checking what those pages already cover.

Third, review the selected external sources for current accuracy before any publisher request is made, and keep ambiguous matches out of the correction queue. Buyer-question content follows once existing coverage is confirmed. Each step produces reviewable work; none of it promises a change in how answers treat the company.

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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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