Cooney & Conway AI Market Strategy Report - Mesothelioma Lawyers

Answer Capsule

Cooney & Conway holds a mid-tier position in AI-generated recommendations for mesothelioma lawyers, with 11.31% valid recommendation coverage in September 2026. The firm appears in 11.76% of qualified observations and converts most of that presence into recommendations, a stronger conversion pattern than several competitors with similar visibility. Its clearest strength is a concentrated pocket of recommendation power on Perplexity, where it reaches 66.67% valid recommendation coverage, while its clearest weakness is a top-three rate that lags behind its overall coverage. The biggest opportunity is converting its strong Perplexity presence into broader recommendation coverage across ChatGPT, Copilot, Gemini, and Google AI surfaces.

Who This Report Is For

This report is for marketing, business development, and firm leadership teams at Cooney & Conway who need to understand how AI systems currently recommend the firm in mesothelioma lawyer discovery queries.

Report Card

Executive Summary

Cooney & Conway holds a fourth-place position in the mesothelioma lawyer category with 11.31% valid recommendation coverage in September 2026, placing it behind Simmons Hanly Conroy, Weitz & Luxenberg, and Sokolove Law. The firm recorded 25 valid recommendations from 26 total mentions across 221 qualified observations, meaning nearly every appearance in AI responses converts into an actual recommendation. This conversion pattern is stronger than several competitors that appear more often but are recommended less consistently.

The firm's strongest cluster is the Brand Recommendation class covering best mesothelioma lawyer and top asbestos attorney queries, which accounts for all qualified observations in the current public series. Within that cluster, Cooney & Conway's most powerful platform signal comes from Perplexity, where the firm achieves 66.67% valid recommendation coverage and a 50.00% top-three rate, both far above its category-wide averages. The clearest platform gap is ChatGPT, where the firm appears in only 9.09% of observations despite that platform carrying substantial discovery volume.

Sentiment is overwhelmingly positive at 0.9615, with 25 positive mentions and only 1 neutral mention. No negative framing was recorded. The firm's average recommended rank of 3.04 indicates that when Cooney & Conway is recommended, it tends to appear near the top of the list but rarely as the single first choice, with a rank-one rate of just 1.81%.

The category context matters: Simmons Hanly Conroy dominates at 66.97% coverage, and the overall market has compressed since July 2026. Cooney & Conway declined from 16.8% in July to 11.3% in September, a 5.5-point drop that stayed within normal variation. The firm has stabilized since August, suggesting the decline was concentrated in the July-to-August window.

What Cooney & Conway Is Winning

Questions This Section Answers

• Where does Cooney & Conway convert its AI visibility into actual recommendations most efficiently?
• How strong is Cooney & Conway's Perplexity recommendation presence compared with its category-wide averages?
• What does the sentiment data say about how AI systems frame Cooney & Conway?

Cooney & Conway's clearest evidence-backed win is its recommendation conversion efficiency. The firm appears in 26 qualified observations and receives 25 valid recommendations, a conversion rate that outperforms several competitors. Sokolove Law, by contrast, appears in 70 observations but converts only 41 into valid recommendations, and Weitz & Luxenberg appears in 107 observations with 83 valid recommendations. Cooney & Conway nearly always gets recommended when it appears.

The firm's Perplexity performance is a second genuine strength. On that platform, Cooney & Conway achieves 66.67% valid recommendation coverage, 50.00% top-three rate, and 16.67% rank-one rate across 6 observations. This is the firm's strongest platform-specific showing and suggests a narrow but meaningful recommendation pocket that could be expanded.

Sentiment is also a clear positive. A net sentiment score of 0.9615 with zero negative mentions means that when AI systems discuss Cooney & Conway, the framing is consistently favorable. The firm has no negative visibility to repair.

Where Cooney & Conway Has the Clearest AI Visibility Gaps

Questions This Section Answers

• How does Cooney & Conway's recommendation coverage vary across AI platforms?
• How does the firm's top-of-list placement compare with its overall recommendation coverage?
• Which competitors are displacing Cooney & Conway in the middle tier?

The clearest gap is platform concentration. Cooney & Conway's category-wide coverage of 11.31% hides wide variation across surfaces. On Perplexity, the firm reaches 66.67% coverage, but on ChatGPT it falls to 9.09%, on Copilot to 10.53%, on Gemini to 4.55%, on AI Mode to 9.38%, and on AI Overviews to 11.11%. The firm is not absent from any platform, but it holds meaningful recommendation power on only one.

The second gap is top-of-list placement. Cooney & Conway's top-three rate of 7.24% is below its valid recommendation coverage of 11.31%, meaning the firm is often recommended in positions four through ten rather than in the first three slots. Its rank-one rate of 1.81% is particularly low. When AI systems recommend Cooney & Conway, they rarely put the firm first. Simmons Hanly Conroy, by contrast, holds a 41.63% rank-one rate, and Weitz & Luxenberg holds 11.31%.

The third gap is competitive displacement in the middle tier. Sokolove Law holds 18.55% coverage to Cooney & Conway's 11.31%, and Shrader & Associates, despite a significant decline from July, still holds 8.14%. The firm sits in a crowded band where small changes in prompt outcomes can shift relative position.

Biggest Opportunity

Questions This Section Answers

• How can Cooney & Conway translate its Perplexity recommendation strength into broader AI platform coverage?
• What should the firm prioritize to lift its ChatGPT performance toward its Perplexity rate?

The single clearest opportunity is converting Cooney & Conway's Perplexity recommendation strength into broader coverage across ChatGPT and Google AI surfaces. The firm already demonstrates that AI systems will recommend it strongly when the conditions are right, as shown by its 66.67% coverage on Perplexity. The gap is not whether the firm can be recommended, but whether the public evidence layer supports those recommendations consistently across platforms.

The priority should be identifying which sources Perplexity is drawing from when it recommends Cooney & Conway, then ensuring those same source types are visible and retrievable across ChatGPT, AI Mode, and AI Overviews. If the firm can lift its ChatGPT coverage from 9.09% toward even half of its Perplexity rate, the category-wide impact would be substantial.

Competitive Landscape

Questions This Section Answers

• Where does Cooney & Conway stand relative to the other nine tracked firms in the category?
• How does its top-three and rank-one placement compare with the leaders?

Simmons Hanly Conroy holds dominant recommendation-stage strength in the mesothelioma lawyer category, with Weitz & Luxenberg in a clear second position. Cooney & Conway sits in the middle tier alongside Sokolove Law and Shrader & Associates, with meaningful presence but limited top-of-list placement.

Average recommended rank covers rank-eligible recommendations only.

The table shows Cooney & Conway holding the fourth-highest top-three rate in the category, behind the three leaders. Its average recommended rank of 3.04 is competitive with Sokolove Law and better than Shrader & Associates, but the firm's rank-one rate of 1.81% trails Weitz & Luxenberg substantially and sits only slightly above the lower tier.

Prompt Evidence

Perplexity / Brand Recommendation Prompt: "Who is the best mesothelioma lawyer?" Result: Cooney & Conway was recommended in the top three in half of Perplexity observations, with one rank-one placement, its strongest platform showing.

ChatGPT / Brand Recommendation Prompt: "mesothelioma lawyers" Result: Cooney & Conway appeared in 9.09% of ChatGPT observations with a single recommendation at rank five, showing presence without top-of-list placement.

AI Overviews / Brand Recommendation Prompt: "new york mesothelioma lawyers" Result: Cooney & Conway achieved 11.11% valid recommendation coverage with a 2.02% rank-one rate, indicating consistent but mid-list placement on Google surfaces.

What CiteWorks Studio Would Do Next

Phase 1: AI Market Discovery Audit Map which prompts and surfaces currently return Cooney & Conway as a recommendation versus a passing mention, with particular focus on the gap between Perplexity strength and ChatGPT weakness.

Phase 2: Recommendation Readiness Plan Identify the source types and content themes that drive Cooney & Conway's strong Perplexity recommendations, then determine which of those signals are missing from other platforms.

Phase 3: Owned Answer Layer Buildout Strengthen owned content around the firm's track record, verdict history, and practice focus so AI systems have consistent, retrievable material to cite across all surfaces.

Phase 4: Citation / Authority Layer Development Build the external citation layer that supports third-party validation of Cooney & Conway as a recommended firm, focusing on the source types that appear to influence Perplexity and AI Overviews.

Phase 5: Monthly AI Visibility and Recommendation Tracking Track whether improvements in the citation and answer layers move the firm from mid-list placement toward top-three and rank-one recommendations across ChatGPT, Copilot, and Google AI surfaces.

Why This Matters

Questions This Section Answers

• Why does Cooney & Conway's strong Perplexity showing fail to translate into category-wide visibility?
• What strategic shift is required to convert the firm's narrow platform strength into consistent recommendation coverage?

AI systems are becoming the first stop for buyers researching mesothelioma lawyers, and those systems are forming recommendations from a public evidence layer that firms can influence. Cooney & Conway has already proven it can be recommended strongly on one platform, but that strength does not yet translate across the surfaces where most discovery volume occurs.

Presence alone is not enough. The firm appears in AI responses and converts those appearances into recommendations at a high rate, but it rarely appears first and holds meaningful recommendation power on only one platform. The next move is targeted correction of the prompt, page, and citation layers to convert a narrow Perplexity strength into consistent category-wide recommendation coverage.

Core Metrics

Sentiment Score

Sentiment Score = (positive mentions × 1 + neutral mentions × 0 + negative mentions × -1) / total mentions

For Cooney & Conway, this calculation is (25 × 1 + 1 × 0 + 0 × -1) / 26, producing a net sentiment score of 0.9615.

This matters because unclassified mention counts are misleading. A firm can appear frequently in AI responses but be mentioned in neutral, cautionary, or comparison-anchor contexts that do not translate into buyer action. Share of voice is a diagnostic metric, not a business KPI. A positive recommendation, neutral reference, cautionary mention, and competitor-displaced mention are not equal, and counting all mentions as wins is bad measurement. Classified sentiment is required before interpreting AI visibility, because the difference between a recommendation and a passing reference determines whether presence converts into shortlist eligibility.

Sentiment by Platform

Methodology

1. This report is a benchmark-based analysis of Cooney & Conway's AI recommendation visibility in the mesothelioma lawyer category, drawn from the LLM Authority Index AI Market Discovery Index and CiteWorks Studio interpretation of that public data.
2. The reporting window is September 2026, with July 2026 referenced as the baseline for movement analysis and August 2026 used for intermediate context.
3. Six AI surface families were tracked: ChatGPT, Copilot, Gemini, Perplexity, Google AI Overviews, and Google AI Mode.
4. The public benchmark analyzed 221 qualified observations in September 2026, drawn from 428 source prompt-surface observations and 362 unique questions.
5. The competitor universe includes 10 tracked brands: Simmons Hanly Conroy, Weitz & Luxenberg, Sokolove Law, Cooney & Conway, Shrader & Associates, Kazan McClain, Nemeroff Law, Belluck & Fox, Galiher DeRobertis, and Goldberg Persky White.
6. The public benchmark used one qualified buyer-intent cluster in September 2026: Brand Recommendation, covering discovery and consideration queries. No qualified observations were captured in Pricing & Value or Multi-Brand Comparison clusters.
7. Stage 0 extraction retained prompt-level observations including query, AI surface, answer, brand outcome, recommendation placement, sentiment, and citations where exposed.
8. A mention is defined as any appearance of a tracked brand in an AI response, regardless of whether the brand is recommended.
9. A valid recommendation is defined as a clear, positive recommendation of the brand in response to a qualified prompt, distinct from a neutral reference or passing mention.
10. Small observation counts apply to several platforms in this dataset. Cooney & Conway's Perplexity metrics are based on 6 observations, and ChatGPT, Copilot, and Gemini metrics are based on 11, 19, and 22 observations respectively. Single prompts carry more weight at this scale.
11. Movement analysis identifies changes worth investigating. Month-over-month movement does not by itself establish the cause of those changes.
12. This public benchmark does not measure market share, attributable sales, every possible AI response, organic-search ranking, or private and sponsored channels. Source presence is evidence about the information environment, not proof that a source caused a recommendation.

Get Your AI Visibility Audit

The public benchmark shows where Cooney & Conway wins and loses in AI-generated recommendations, but it cannot show which specific prompts, competitor displacements, and evidence sources drive those outcomes. A company-level AI visibility audit maps those patterns into a prioritized strategy for converting mid-tier presence into consistent top-three recommendation placement across all AI surfaces.