Medical Bills AI Visibility Ranking Trends - November 2026

Answer capsule

The November 2026 Medical Bills benchmark compares 6 companies across 62 AI answers that met its inclusion rules. Dollar For leads with 16 recommendations (25.81% of answers). At least one tracked company was recommended in 16 answers; some answers recommended several companies.

The rankings distinguish being mentioned from receiving an affirmative recommendation, then examine placement and the wording used about each company. Earlier monthly results show how counts and rates changed, with each month using its own answer total. These results describe the answers reviewed, not product quality or customer satisfaction. Differences between monthly samples limit comparisons and do not establish why a result changed.

For the strategic interpretation of this benchmark, read CiteWorks Studio's analysis of How AI Search Is Recommending Medical Bills

Industry leaderboard

Questions This Section Answers

• How do Medical Bills rank by recorded AI recommendations in November 2026?

The leaderboard orders companies by how many answers affirmatively recommended them, not by how often they appeared. A company can be mentioned frequently yet recommended rarely, so the recommendation count and the mention rate answer different questions.

Ties reflect equal recommendation counts, not shared wording or placement. Placement figures are nested inside recommendations: a first-place result is also a shortlist result, and both sit within the recommendation total rather than adding to it.

Key findings

Tracked-company answer coverage

Questions This Section Answers

• How often did the November 2026 Medical Bills answer sample recommend any tracked company?

16 distinct answers recommended at least one tracked company. Counting each company recommendation separately gives 36, because an answer can recommend several companies. Answers with no tracked recommendation may still have recommended companies outside this comparison.

Every qualified answer mentioned at least one tracked company, but only a minority recommended one. That gap separates presence from endorsement: being named in an answer is not the same as being put forward as a choice.

Because a single answer can recommend several companies, company-level recommendation totals exceed the number of answers containing a recommendation. Answers without a tracked recommendation may still have named companies outside this comparison, so coverage here is bounded by the tracked set.

Reach and affirmative recommendation

Dollar For ranks 1 by recommendation count. Mentions: 55 (88.71%); recommendations: 16 (25.81%). Top 3 placements: 1 (1.61%); first-place placements: 0 (0.00%).

Wording about the company: 16 positive, 39 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 29.1%. The net framing score was 0.29 (defined in Methodology).

39 mentions had no recorded recommendation. Of recorded recommendations, 6.25% were Top 3 and 0.00% were first-place.

Dollar For leads on recommendation count while also appearing in most answers, yet most of its mentions carried no recommendation. Reach and endorsement therefore diverge: high visibility did not translate into affirmative backing in the recorded wording.

A tie in recommendation counts is a tie, not a hidden winner. Placement and framing are read separately from the recommendation total, since neither is implied by appearing often.

Recommendation order and placement

Placement describes where a recommended company sat in an answer's ordering. Shortlist and first-place results are subsets of recommendations, so they should be read as position within endorsement rather than as extra wins.

Several companies recorded recommendations without any shortlist placement, and one recorded a shortlist placement from a small recommendation base. Sparse bases make such ratios fragile, so placement shares are best read alongside the underlying counts.

Classified framing in context

Framing classifies the wording surrounding each mention as positive, neutral or negative. Most mentions across companies were neutral, with positive wording concentrated among the more frequently recommended names and no negative wording recorded.

Framing is not customer sentiment or a measure of company quality, and neutral wording does not explain why a recommendation was or was not recorded. It describes how the selected answers phrased their references.

Company results in detail

Dollar For

Questions This Section Answers

• What do the November 2026 AI answer results show about Dollar For mentions, recommendations and placement?

Dollar For ranks 1 by recommendation count. Mentions: 55 (88.71%); recommendations: 16 (25.81%). Top 3 placements: 1 (1.61%); first-place placements: 0 (0.00%).

Wording about the company: 16 positive, 39 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 29.1%. The net framing score was 0.29 (defined in Methodology).

39 mentions had no recorded recommendation. Of recorded recommendations, 6.25% were Top 3 and 0.00% were first-place.

From October 2026 to November 2026, Dollar For's mention count rose from 33 to 55, while its recommendation count fell from 27 to 16. The recommendation rate was 58.70% and 25.81% respectively.

Dollar For recorded the most recommendations and appeared in the large majority of answers, but most of its mentions were neutral and carried no endorsement. Its recommendation-to-mention ratio shows that visibility far exceeded affirmative backing in the recorded wording.

Placement within its recommendations was rare, with almost none reaching the shortlist and none first. Between the two months, mentions rose while recommendations fell; the samples differ, so the comparison shows the recorded change without establishing why.

Goodbill

Questions This Section Answers

• What do the November 2026 AI answer results show about Goodbill mentions, recommendations and placement?

Goodbill ranks 2 by recommendation count. Mentions: 36 (58.06%); recommendations: 11 (17.74%). Top 3 placements: 2 (3.23%); first-place placements: 2 (3.23%).

Wording about the company: 11 positive, 25 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 30.6%. The net framing score was 0.31 (defined in Methodology).

25 mentions had no recorded recommendation. Of recorded recommendations, 18.18% were Top 3 and 18.18% were first-place.

From October 2026 to November 2026, Goodbill's mention count rose from 14 to 36, while its recommendation count fell from 13 to 11. The recommendation rate was 28.26% and 17.74% respectively.

Goodbill combined a substantial mention presence with a moderate recommendation count, and its recommendation-to-mention ratio was among the higher ones recorded. Its placements were unusual in that every shortlist result was also a first-place result.

Wording around it was positive or neutral, never negative. Mentions rose between the two months while recommendations eased slightly; because the monthly samples differ, that comparison describes the recorded shift rather than a cause.

FAIR Health

Questions This Section Answers

• What do the November 2026 AI answer results show about FAIR Health mentions, recommendations and placement?

FAIR Health ranks 3 by recommendation count. Mentions: 36 (58.06%); recommendations: 7 (11.29%). Top 3 placements: 0 (0.00%); first-place placements: 0 (0.00%).

Wording about the company: 7 positive, 29 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 19.4%. The net framing score was 0.19 (defined in Methodology).

29 mentions had no recorded recommendation. Of recorded recommendations, 0.00% were Top 3 and 0.00% were first-place.

From October 2026 to November 2026, FAIR Health's mention count rose from 23 to 36, while its recommendation count fell from 16 to 7. The recommendation rate was 34.78% and 11.29% respectively.

FAIR Health appeared as often as Goodbill but drew fewer recommendations, giving it a lower recommendation-to-mention ratio. Its mentions were overwhelmingly neutral, and it recorded no shortlist or first-place placements at all.

Its recommendation count fell between the two months even as mentions rose. The samples are separate, so the divergence is a recorded comparison, not evidence of a mechanism or of lost standing.

CareRoute

Questions This Section Answers

• What do the November 2026 AI answer results show about CareRoute mentions, recommendations and placement?

CareRoute ranks 4 by recommendation count. Mentions: 30 (48.39%); recommendations: 2 (3.23%). Top 3 placements: 1 (1.61%); first-place placements: 0 (0.00%).

Wording about the company: 2 positive, 28 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 6.7%. The net framing score was 0.07 (defined in Methodology).

28 mentions had no recorded recommendation. Of recorded recommendations, 50.00% were Top 3 and 0.00% were first-place.

From October 2026 to November 2026, CareRoute's mention count rose from 18 to 30, while its recommendation count fell from 5 to 2. The recommendation rate was 10.87% and 3.23% respectively.

CareRoute appeared in roughly half of the answers but was recommended in only a few, producing a low recommendation-to-mention ratio. Nearly all of its mentions were neutral, with little positive wording recorded.

Its single shortlist placement came from a very small recommendation base, so that share should be read with caution. Mentions rose while recommendations fell across the two months, a comparison limited by differing samples.

Clearity Health

Questions This Section Answers

• What do the November 2026 AI answer results show about Clearity Health mentions, recommendations and placement?

Clearity Health ranks 5 by recommendation count. Mentions: 0 (0.00%); recommendations: 0 (0.00%). Top 3 placements: 0 (0.00%); first-place placements: 0 (0.00%).

Wording about the company: 0 positive, 0 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was Unavailable. The net framing score was Unavailable (defined in Methodology).

0 mentions had no recorded recommendation. Of recorded recommendations, Unavailable were Top 3 and Unavailable were first-place.

From October 2026 to November 2026, Clearity Health's mention count stayed at 0, while its recommendation count stayed at 0. The recommendation rate was 0.00% and 0.00% respectively.

Clearity Health recorded no mentions and no recommendations in the selected answers, so its placement counts are also zero. These are measured results rather than missing observations.

With no mentions, ratios that require a nonzero base are undefined, and its framing score is unavailable. The absence describes this answer set only and does not establish anything about the company beyond it.

Granted Health

Questions This Section Answers

• What do the November 2026 AI answer results show about Granted Health mentions, recommendations and placement?

Granted Health ranks 5 by recommendation count. Mentions: 3 (4.84%); recommendations: 0 (0.00%). Top 3 placements: 0 (0.00%); first-place placements: 0 (0.00%).

Wording about the company: 0 positive, 3 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 0.0%. The net framing score was 0.00 (defined in Methodology).

3 mentions had no recorded recommendation. Of recorded recommendations, Unavailable were Top 3 and Unavailable were first-place.

From October 2026 to November 2026, Granted Health's mention count stayed at 3, while its recommendation count fell from 1 to 0. The recommendation rate was 2.17% and 0.00% respectively.

Granted Health appeared in only a few answers, all with neutral wording, and received no recommendations. Its recommendation-to-mention ratio is therefore zero, and its placement counts are zero as well.

Its mention count held steady between the two months while its single earlier recommendation did not recur. With such a small base, the figures are best read as sparse recorded results rather than a trend.

Earlier ranking snapshot context

Questions This Section Answers

• How do the available Medical Bills snapshots from July 2026 to November 2026 differ in recommendation coverage and measurement scope?

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

Each month is a separate sample of AI answers with differing coverage, so counts and rates are not directly comparable across months. A company's rank can shift because its own results changed, because other companies' results changed, or because the sample differed.

Smaller answer totals in a given month do not by themselves explain a company's lower counts or rates. The history shows recorded movement; it does not establish rank stability or equivalent sampling.

What the November Rankings Show

The November results answer distinct questions. Reach asks how often a company appeared; recommendation asks whether an answer affirmatively endorsed it; placement asks where an endorsed company sat in the ordering; framing asks how the wording read. A company can be highly visible yet rarely recommended, or recommended without reaching the top of an answer.

Because these measures use overlapping answer sets and nested subsets, they should not be combined into a single score or read as customer behavior. The recorded differences describe the selected answers, not company quality or the reasons behind any recommendation.

Methodology

Questions This Section Answers

• How were the November 2026 Medical Bills AI visibility measures counted, and what do they not establish?

This benchmark has partial coverage: 1 of 3 planned question categories contributed usable observations; 2 contributed none. This describes question-category coverage, not demonstrated platform outages. Findings apply to the available answer set.

The month in the title is the reporting period. The exact dates when the original AI answers were collected have not been verified.

Each company is counted at most once in each answer that meets the benchmark rules. A recommendation requires both an affirmative endorsement and positive wording. Mention, recommendation, Top 3 and first-place rates use the full benchmark answer total. Top 3 and first-place results are included within recommendations, not added to them.

The recommendation-to-mention ratio divides recommendations by mentions. It describes AI answer wording, not customer conversion. Net framing is positive minus negative mentions, divided by all mentions, on a scale from -1 to +1. It does not measure customer satisfaction or company quality.

Market: US; 6 tracked companies. AI services represented: Copilot, Gemini, Google AI Mode, Google AI Overviews.

Research screening totals (answer observations can include repeated questions):

The source does not provide a reader-facing definition of “reserved”; that screening label is reported without inferring a reason for exclusion. Only the included benchmark answers form the rate denominator.

One answer can mention or recommend several companies. Adding company totals would therefore count some answers more than once. The results describe the AI answers reviewed, not independently verified facts about the companies or their products.

Monthly sample coverage:

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

Coverage is partial: only one of the planned question categories contributed usable answers, and findings apply to that available set. The reporting month labels the period, but exact collection dates were not verified, and the monthly samples differ in size and services covered.

Each company is counted at most once per answer, and a recommendation requires both affirmative endorsement and positive wording. Placement results are nested within recommendations. Ratios and framing scores describe answer wording, not customers, sales or company quality, and the results are not independently verified facts about the companies.