Levin & Perconti Appears in 1.4% of AI Answers. Here's Our Five-Step Plan to Improve Its AI Visibility.

Answer Capsule

In November 2026, Levin & Perconti appeared in 2 of 138 AI answers included in the Nursing Home Abuse Lawyers benchmark (1.45%). It received 2 recommendations (1.45%), with 1 Top 3 placement and 1 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 Levin & Perconti mentions, recommendations and placements compare with its Nursing Home Abuse Lawyers peers?

Levin & Perconti recorded 2 mentions (1.45%) and 2 recommendations (1.45%) across 138 answers included in the benchmark. Top 3 placements numbered 1; first-place recommendations numbered 1. Framing among its mentions was 2 positive, 0 neutral and 0 negative.

Levin & Perconti appears in a small share of the benchmark answers, and when it appears it is usually endorsed rather than merely named. That is a narrow but clean footprint: the firm is not a frequent reference point, yet the answers that do include it tend to treat it favorably.

The gap to the leading firms is wide, so the practical question is not how to close it quickly but where a modest gain is realistic. The firm's strongest showing is in first-place recommendations, which suggests that when an answer does select it, the selection is decisive rather than incidental.

We would treat this as a starting position to protect and extend, not a deficit to fix overnight. The first step is a scorecard that tracks mentions, recommendations and placement separately so the firm can see which measure moves as work is delivered.

What changed since last month

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• How did Levin & Perconti counts and coverage differ across the available monthly snapshots?

From October 2026 to November 2026, Levin & Perconti's mention count fell from 5 to 2, while its recommendation count fell from 5 to 2. The recommendation rate was 3.14% and 1.45% respectively.

The monthly record shows a steady narrowing of the firm's presence across the selected samples, with the most recent month the lowest of the five. Mentions and recommendations moved together, so the firm was not simply being named more often without endorsement.

The samples differ from month to month, and a smaller answer total does not by itself explain the movement in counts or rates. We would present the trend as an observed pattern and keep the comparability limit beside it rather than offering a cause.

For planning, the useful takeaway is that the firm's recent position is thin enough that a few answers could shift the picture either way. We would establish a fresh baseline before proposing any corrective work, so later comparisons rest on a clearly dated starting point.

Step 1. Measure

Questions This Section Answers

• What should the agency measure and verify first for Levin & Perconti?

AI answers contained 0 conflicting claims about Levin & Perconti: 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 Levin & Perconti were recorded in the captured answers, which means there is no obvious factual dispute to chase. That is a favorable starting point, but it also means the firm's visibility problem is about presence and framing rather than correcting errors.

A visibility comparison would show where the firm appears relative to the firms that dominate the answers, and a claims list would record any statements that warrant checking. Together they give the client a short, ordered set of priorities instead of a broad mandate.

We would propose building both as working documents with named owners, so each item carries a status and an evidence requirement before anyone acts on it.

Step 2. Make the website consistent

Questions This Section Answers

• Which recorded claim differences about Levin & Perconti 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.

This part of the analysis returned no results, so there are no disputed topics to brief against yet. Rather than inventing page work, we would start by confirming which company entity, dates and sources the answers refer to, since an apparent conflict can dissolve once those are pinned down.

Where a genuine question survives that check, we would prepare a conditional page brief that relies only on approved facts and leaves the disputed point open until primary sources are reviewed. The brief would describe what the page should cover, not assert which version is correct.

This keeps the firm from rewriting pages on the strength of an AI statement alone.

Step 3. Align the external narrative

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• Which cited third-party pages are relevant to fact review for Levin & Perconti?

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, including search-viewer links, other law firm sites and directories. None of them carries a recorded conflicting claim about the firm, so there is no correction case to pursue on this evidence.

What remains useful is a source review: checking what each page currently says and whether it is a plausible place for the firm to be represented accurately. A citation does not show that a source shaped an answer, so we would treat these as leads to inspect rather than causes to fix.

Where a page does warrant a request, we would prepare an evidence-backed approach and record the response separately from any change in visibility.

Step 4. Optimize priority company pages

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• Which observed Levin & Perconti website pages should receive review briefs?

The company's website was cited 8 times across 7 distinct page addresses; the table shows 7 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 firm's own site was cited across several distinct pages, and a few of those citations coincided with answers that recommended the firm. That makes the owned pages a sensible place to concentrate effort, since they are the assets the firm fully controls.

The page list is varied: a facility page, a bed sore lawyer page, blog and FAQ content, and a Spanish-language version. We would write briefs for the pages most likely to support buyer questions, using approved facts and the questions actually observed, and check existing coverage before proposing anything new.

A citation is not proof that a page earned a recommendation, so the briefs would aim at clarity and completeness rather than mimicking what appears to have worked.

Step 5. Publish around buyer questions

Questions This Section Answers

• Which observed buyer questions support content briefs for Levin & Perconti?

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

The recorded questions are few but pointed: one about the top lawyer in Chicago and one about bed sore lawyers in Chicago. Both produced a mention and a recommendation for the firm, which suggests the firm already has some footing on these queries.

These are answer observations, not search volume or verified demand, so we would not build a content program on them alone. Instead we would use them as seeds for buyer-question briefs, checking whether the site already answers each question well before drafting anything new.

The briefs would specify the question, the audience, the approved facts to include and the existing page to improve or replace.

Our 90-day action plan

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• How should the agency sequence the proposed Levin & Perconti work and judge completion?

The first month would produce a baseline scorecard, a scoped fact-review register and a shortlist of pages and sources to examine. Each record would carry an owner, an evidence requirement and a review status, so nothing advances on assumption.

The second month would turn confirmed findings into approved page briefs and, where justified, publisher requests. Confirmed edits, no-change decisions, requests and responses would be logged separately so the client can see what was decided and why.

The final month would deliver buyer-content briefs and a fresh scorecard. Completed work would be reported apart from measured answer outcomes, with the comparability limits stated plainly.

Methodology

Questions This Section Answers

• How are Levin & Perconti 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 138 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 705 captured answers and 3780 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:

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. Visibility rates rest on the answers that met the benchmark's inclusion rules, and a company counts as recommended only when an answer both endorses it and uses positive wording.

An answer can mention several firms, so company counts cannot be added to reach a number of distinct answers. Monthly samples differ, and the comparisons show how recorded results changed rather than why. Cited pages and any disputed claims still need independent checking before action.

Our first three priorities

First, establish a dated baseline and a scorecard that keeps mentions, recommendations and placement distinct, so the firm can see which measure responds to which work. The recent monthly movement makes a clean starting point more valuable than an early push.

Second, review the cited pages and the firm's own priority pages against approved facts, and prepare briefs only where current contents have been checked. The facility and bed sore pages look like the most useful places to start.

Third, turn the observed buyer questions into content briefs after confirming existing coverage. Each of these is proposed work, and none of it should be presented as a guaranteed change in how often the firm appears.