Spodek Law Group Appears in 19.7% 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

  • Spodek Law Group is mentioned often in benchmark answers, but only a small share of those mentions become recommendations.
  • When the firm is recommended, it tends to place strongly, including top-three and first-place positions.
  • The main issue is the gap between being named and being endorsed, not weak ranking.
  • The plan focuses on verifying conflicting claims, reviewing cited sources, and building content from observed buyer questions.

Answer Capsule

In November 2026, Spodek Law Group appeared in 12 of 61 AI answers included in the Criminal Defense Lawyers benchmark (19.67%). It received 3 recommendations (4.92%), with 3 Top 3 placements and 3 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 Spodek Law Group mentions, recommendations and placements compare with its Criminal Defense Lawyers peers?

Spodek Law Group recorded 12 mentions (19.67%) and 3 recommendations (4.92%) across 61 answers included in the benchmark. Top 3 placements numbered 3; first-place recommendations numbered 3. Framing among its mentions was 4 positive, 8 neutral and 0 negative.

Rank

Company

Mentions

Mention rate

Recommendations

Recommendation rate

Top 3

Top 3 rate

#1

#1 rate

1

Kraut Law Group

23

37.70%

13

21.31%

11

18.03%

7

11.48%

2

The Rodriguez Law Group

6

9.84%

6

9.84%

4

6.56%

1

1.64%

3

Esfandi Law Group

5

8.20%

4

6.56%

1

1.64%

1

1.64%

4

Goldstein Mehta

6

9.84%

3

4.92%

3

4.92%

3

4.92%

4

Spodek Law Group

12

19.67%

3

4.92%

3

4.92%

3

4.92%

4

Wallin & Klarich

7

11.48%

3

4.92%

3

4.92%

3

4.92%

7

The Cochran Firm

7

11.48%

2

3.28%

2

3.28%

1

1.64%

8

Greg Hill & Associates

1

1.64%

1

1.64%

1

1.64%

0

0.00%

9

Chambers Law Firm

4

6.56%

0

0.00%

0

0.00%

0

0.00%

9

Monder Criminal Lawyer Group

0

0.00%

0

0.00%

0

0.00%

0

0.00%

Spodek Law Group appears in roughly one in five benchmark answers, which puts its reach well above most listed firms, yet only a small share of those mentions carry an affirmative recommendation. That gap between being named and being endorsed is the central visibility issue. The firm is seen often but rarely chosen.

Placement is not the problem. Every recommendation the firm received also placed it in the top three and in first place, so when an answer does endorse the firm it endorses it strongly. The work ahead is widening endorsement rather than improving rank. We would build a scorecard that tracks mentions and recommendations separately so the client can see this distinction clearly.

What changed since last month

Questions This Section Answers

  • How did Spodek Law Group counts and coverage differ across the available monthly snapshots?

Metric

Jul 2026

Aug 2026

Sep 2026

Oct 2026

Nov 2026

Mentions

40 / 136 (29.41%)

45 / 176 (25.57%)

49 / 173 (28.32%)

28 / 129 (21.71%)

12 / 61 (19.67%)

Recommendations

38 / 136 (27.94%)

37 / 176 (21.02%)

37 / 173 (21.39%)

21 / 129 (16.28%)

3 / 61 (4.92%)

Top 3 recommendations

33 / 136 (24.26%)

33 / 176 (18.75%)

31 / 173 (17.92%)

18 / 129 (13.95%)

3 / 61 (4.92%)

#1 recommendations

16 / 136 (11.76%)

21 / 176 (11.93%)

22 / 173 (12.72%)

13 / 129 (10.08%)

3 / 61 (4.92%)

From October 2026 to November 2026, Spodek Law Group's mention count fell from 28 to 12, while its recommendation count fell from 21 to 3. The recommendation rate was 16.28% and 4.92% respectively.

The recorded results moved sharply between the October and November samples, with both mentions and recommendations lower in November. The recommendation rate also fell. Because the two months drew on different answer samples, the movement should be read as an observed change in the selected answers, not as evidence of a cause or a trend.

What matters for planning is that the November sample shows a thin base of endorsement relative to mentions. We would treat the monthly figures as separate snapshots and avoid drawing conclusions from one comparison. A fresh scorecard over a consistent sample would give the client a steadier basis for judging progress.

AI recommendation trend

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

0%10%20%30%40%Jul 2026Aug 2026Sep 2026Oct 2026Nov 202627.94%Jul 2026: 27.94%21.02%Aug 2026: 21.02%21.39%Sep 2026: 21.39%16.28%Oct 2026: 16.28%4.92%Nov 2026: 4.92%
  • Spodek Law Group4.92%

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 Spodek Law Group?

AI answers contained 1 conflicting claim about Spodek Law Group: 0 critical, 0 high, 0 medium, 1 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.

The benchmark captured a single conflicting claim about the firm, rated low severity, so fact-checking is a small and bounded task rather than an urgent repair. The rating signals where to look first; it does not establish that the firm or any publisher made an error.

A visibility comparison alongside a short list of claims to verify would let the client set priorities with clear eyes. We would pair the mention-and-recommendation scorecard with a fact-review register that records each disputed point, its source and its review status, so effort goes where the evidence actually points.

Step 2. Make the website consistent

Questions This Section Answers

  • Which recorded claim differences about Spodek Law Group should be verified before proposed page edits?

Review topic

Severity

Recorded AI claim A

Recorded AI claim B

office location

low

195 Montague St, 14th floor, Brooklyn

233 Broadway, New York, NY

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.

The one recorded conflict concerns an office location, with answers citing different addresses. Both entries are quotations from AI answers, not verified company facts, and a difference in dates or entity naming could account for the apparent disagreement.

We would verify the firm's current office details against primary sources before drafting anything. If a page brief proves warranted, it would state only approved facts and would be held until verification is complete. Until then the item stays in the review register rather than the correction queue.

Step 3. Align the external narrative

Questions This Section Answers

  • Which cited third-party pages are relevant to fact review for Spodek Law Group?

Cited page selected for review

Citation appearances in all captured answers

Answers mentioning the company

Conflicting claims linked to this page

https://google.com/searchviewer/10?svid=CAwSHBIaCgNwdnESE0Nnd3ZaeTh4YUcwME9HeG9jekkYCg

21

4

1

https://google.com/searchviewer/10?svid=CAwSHRIbCgNwdnESFENnMHZaeTh4TVdzMGN6QnFOR013GAo

3

2

1

https://google.com/searchviewer/10?svid=CAwSGxIZCgNwdnESEkNnc3ZaeTh4ZEdSc01tZDRjdxgK

3

1

1

https://google.com/searchviewer/10?svid=CAwSGxIZCgNwdnESEkNnc3ZaeTh4ZEdReWRuUnVjdxgK

2

1

1

https://howardgreenberglaw.com/

2

1

1

https://neilruskinlawfirm.com/

2

1

1

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.

Several cited pages were selected because they relate to the firm in captured answers, and some carry the conflicting location claim. A page linked to a claim is not necessarily its cause, and the same answer can touch more than one page, so these links are starting points for review rather than conclusions.

We would check the current contents of each selected page before making any request, then approach publishers only where a specific, evidence-backed change is justified. Requests would be logged with their responses so the client can see what was asked and what came back.

Step 4. Optimize priority company pages

Questions This Section Answers

  • Which observed Spodek Law Group 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 website citation results were available for this part of the analysis, so there is no page-level evidence to interpret here. That absence limits what can be said about the firm's own pages and should not be read as a finding about their quality or coverage.

We would begin with a page brief process built on approved facts and the questions buyers actually ask, checking existing coverage before proposing anything new. Briefs would name the audience question each page answers and the evidence behind each claim, giving writers a clear and defensible starting point.

Step 5. Publish around buyer questions

Questions This Section Answers

  • Which observed buyer questions support content briefs for Spodek Law Group?

Question observed in the research

Benchmark answers to this question

Company mentions

Company recommendations

spodek law group reviews

2

2

1

criminal lawyers nyc

1

1

1

todd spodek

1

1

1

How do I find a lawyer in New York?

1

1

0

How much does a lawyer cost for a fraud case?

1

1

0

best criminal defense attorney nyc

1

1

0

best law firms nyc

1

1

0

criminal defense attorney brooklyn

1

1

0

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

The recorded questions cluster around the firm's own name and reviews, New York criminal defense searches, and practical concerns such as finding a lawyer and fraud-case costs. These are answer observations, not search volume or proof that the website lacks matching content.

We would turn the strongest of these into content briefs, checking existing pages first so new work fills genuine gaps. Briefs would address the buyer's question directly, use approved facts, and avoid claims the firm cannot support. Review-related questions deserve particular care because they sit close to reputation.

Our 90-day action plan

Questions This Section Answers

  • How should the agency sequence the proposed Spodek Law Group 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. This gives later work a documented foundation.

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 adds buyer-content briefs and a fresh scorecard. Completed work would be reported apart from measured answer outcomes, and no visibility gain would be promised.

Methodology

Questions This Section Answers

  • How are Spodek Law Group 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 61 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 274 captured answers and 1840 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

136

4

Copilot, Gemini, Google AI Mode, Google AI Overviews

Aug 2026

176

5

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

Sep 2026

173

6

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

Oct 2026

129

6

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

Nov 2026

61

5

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

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 the answers were collected have not been verified. Rates rest on the answers that met the benchmark's inclusion rules, and a company counts as recommended only when an answer endorses it with positive wording. Top-three and first-place results sit inside those recommendations rather than adding to them.

Answers can mention several firms, so company counts do not sum to distinct answers. Monthly samples differ, so comparisons show how recorded results changed, not why. Cited pages and disputed claims still need independent verification.

Our first three priorities

First, verify the office-location conflict against primary sources and keep it in the review register until resolved; it is low severity and does not justify rushed edits. Second, prepare page briefs grounded in approved facts and the buyer questions observed, checking existing coverage before proposing new pages.

Third, review the selected cited pages and make publisher requests only where current evidence supports a specific change. Running alongside these, the scorecard should keep mentions and recommendations distinct so the client can judge whether endorsement is widening, without treating any movement as a guaranteed result.

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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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