Online Dating AI Visibility Ranking Trends - November 2026

Answer capsule

The November 2026 Online Dating benchmark compares 10 companies across 675 AI answers that met its inclusion rules. Hinge leads with 573 recommendations (84.89% of answers). At least one tracked company was recommended in 633 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 Online Dating

Industry leaderboard

Questions This Section Answers

• How do Online Dating 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 less often, so the recommendation count and the mention count answer different questions.

Ties are possible when recommendation counts are equal; near-equal counts should not be read as a settled ordering. Placement figures are nested inside recommendations, so first-place and shortlist results describe position within endorsements rather than additional wins.

Key findings

Tracked-company answer coverage

Questions This Section Answers

• How often did the November 2026 Online Dating answer sample recommend any tracked company?

633 distinct answers recommended at least one tracked company. Counting each company recommendation separately gives 3835, because an answer can recommend several companies. Answers with no tracked recommendation may still have recommended companies outside this comparison.

Almost every included answer named at least one tracked company, and most recommended at least one. Because a single answer can recommend several companies, the sum of company recommendations exceeds the number of answers carrying any recommendation.

This overlap means company totals should not be added into a market-wide count. Coverage describes which companies appeared in the reviewed answers, not overall market share or dominance.

Reach and affirmative recommendation

Hinge ranks 1 by recommendation count. Mentions: 661 (97.93%); recommendations: 573 (84.89%). Top 3 placements: 390 (57.78%); first-place placements: 242 (35.85%).

Wording about the company: 581 positive, 77 neutral, 3 negative mentions. The proportion of mentions that also included a recommendation was 86.7%. The net framing score was 0.87 (defined in Methodology).

88 mentions had no recorded recommendation. Of recorded recommendations, 68.06% were Top 3 and 42.23% were first-place.

Mention records that a company appeared in an answer; recommendation records an affirmative endorsement. Hinge's mentions exceeded its recommendations, so a substantial share of appearances carried no recorded endorsement.

The gap between the two measures is the point: reach describes presence, while recommendation describes support. Neither measure establishes why an answer endorsed a company or withheld endorsement.

Recommendation order and placement

Placement describes where a recommended company sat within an answer's ordering. Shortlist and first-place results are subsets of recommendations, not separate achievements, so they should not be added to recommendation counts.

A company with many recommendations can still have relatively few first-place placements, and the reverse pattern is also possible. These positions describe answer wording, not customer preference or conversion.

Classified framing in context

Framing classifies the wording surrounding a mention as positive, neutral or negative. It is a description of language in the selected answers, not a measure of customer sentiment, reputation or company quality.

Positive wording does not explain why a recommendation was or was not recorded. Neutral mentions are common for some companies, and a favorable framing score should be read alongside the recommendation and placement figures rather than in place of them.

Company results in detail

Hinge

Questions This Section Answers

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

Hinge ranks 1 by recommendation count. Mentions: 661 (97.93%); recommendations: 573 (84.89%). Top 3 placements: 390 (57.78%); first-place placements: 242 (35.85%).

Wording about the company: 581 positive, 77 neutral, 3 negative mentions. The proportion of mentions that also included a recommendation was 86.7%. The net framing score was 0.87 (defined in Methodology).

88 mentions had no recorded recommendation. Of recorded recommendations, 68.06% were Top 3 and 42.23% were first-place.

From October 2026 to November 2026, Hinge's mention count fell from 685 to 661, while its recommendation count fell from 576 to 573. The recommendation rate was 82.05% and 84.89% respectively.

Hinge leads the recommendation count and appears in nearly every included answer, giving it both broad reach and strong endorsement. Its first-place share is the most prominent among the tracked companies, though placements remain a subset of recommendations.

Most mentions carried positive wording, with few negative. The month-to-month comparison shows a lower mention count and a slightly lower recommendation count than the prior sample, while the recommendation rate rose; these are recorded changes in separate samples, not evidence of cause.

Bumble

Questions This Section Answers

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

Bumble ranks 2 by recommendation count. Mentions: 662 (98.07%); recommendations: 554 (82.07%). Top 3 placements: 276 (40.89%); first-place placements: 11 (1.63%).

Wording about the company: 562 positive, 93 neutral, 7 negative mentions. The proportion of mentions that also included a recommendation was 83.7%. The net framing score was 0.84 (defined in Methodology).

108 mentions had no recorded recommendation. Of recorded recommendations, 49.82% were Top 3 and 1.99% were first-place.

From October 2026 to November 2026, Bumble's mention count fell from 687 to 662, while its recommendation count rose from 552 to 554. The recommendation rate was 78.63% and 82.07% respectively.

Bumble sits just behind the leader in recommendations and appears in nearly all answers. Its shortlist placements are substantial, but first-place placements are rare relative to its recommendation total, so its endorsements cluster lower in the ordering.

Framing is mostly positive with a modest neutral share. The prior-month comparison shows fewer mentions alongside a slightly higher recommendation count and a higher recommendation rate, a pattern that should be read as recorded results rather than a demonstrated trend.

OkCupid

Questions This Section Answers

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

OkCupid ranks 3 by recommendation count. Mentions: 563 (83.41%); recommendations: 505 (74.81%). Top 3 placements: 105 (15.56%); first-place placements: 12 (1.78%).

Wording about the company: 510 positive, 52 neutral, 1 negative mentions. The proportion of mentions that also included a recommendation was 89.7%. The net framing score was 0.90 (defined in Methodology).

58 mentions had no recorded recommendation. Of recorded recommendations, 20.79% were Top 3 and 2.38% were first-place.

From October 2026 to November 2026, OkCupid's mention count fell from 574 to 563, while its recommendation count rose from 495 to 505. The recommendation rate was 70.51% and 74.81% respectively.

OkCupid ranks third by recommendations with a comparatively high recommendation-to-mention ratio, meaning most of its appearances carried an endorsement. Its shortlist and first-place placements are modest, so recommendations rarely placed it near the top.

Wording is overwhelmingly positive with very few negative mentions. The prior-month comparison shows a lower mention count and a higher recommendation count, with the recommendation rate rising across separate samples.

Tinder

Questions This Section Answers

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

Tinder ranks 4 by recommendation count. Mentions: 641 (94.96%); recommendations: 500 (74.07%). Top 3 placements: 255 (37.78%); first-place placements: 67 (9.93%).

Wording about the company: 509 positive, 112 neutral, 20 negative mentions. The proportion of mentions that also included a recommendation was 78.0%. The net framing score was 0.76 (defined in Methodology).

141 mentions had no recorded recommendation. Of recorded recommendations, 51.00% were Top 3 and 13.40% were first-place.

From October 2026 to November 2026, Tinder's mention count fell from 661 to 641, while its recommendation count rose from 488 to 500. The recommendation rate was 69.52% and 74.07% respectively.

Tinder combines wide reach with a lower recommendation-to-mention ratio than several peers, so many appearances carried no endorsement. Its shortlist placements are relatively strong, and first-place placements are more common than for most companies below the top two.

Framing includes more neutral and negative mentions than the leaders. The prior-month comparison shows fewer mentions and more recommendations, with the recommendation rate higher; these are recorded differences between samples.

eharmony

Questions This Section Answers

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

eharmony ranks 5 by recommendation count. Mentions: 433 (64.15%); recommendations: 382 (56.59%). Top 3 placements: 111 (16.44%); first-place placements: 27 (4.00%).

Wording about the company: 382 positive, 38 neutral, 13 negative mentions. The proportion of mentions that also included a recommendation was 88.2%. The net framing score was 0.85 (defined in Methodology).

51 mentions had no recorded recommendation. Of recorded recommendations, 29.06% were Top 3 and 7.07% were first-place.

From October 2026 to November 2026, eharmony's mention count rose from 424 to 433, while its recommendation count rose from 362 to 382. The recommendation rate was 51.57% and 56.59% respectively.

eharmony appears in a substantial share of the recorded answers, and most of those mentions also carry an affirmative recommendation. Its shortlist and first-place placements are moderate, so endorsements sometimes appear near the top of an ordering.

Wording is largely positive with a small negative share. The prior-month comparison shows both mention and recommendation counts higher, alongside a higher recommendation rate, across separate monthly samples.

Match

Questions This Section Answers

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

Match ranks 6 by recommendation count. Mentions: 634 (93.93%); recommendations: 374 (55.41%). Top 3 placements: 122 (18.07%); first-place placements: 40 (5.93%).

Wording about the company: 376 positive, 243 neutral, 15 negative mentions. The proportion of mentions that also included a recommendation was 59.0%. The net framing score was 0.57 (defined in Methodology).

260 mentions had no recorded recommendation. Of recorded recommendations, 32.62% were Top 3 and 10.70% were first-place.

From October 2026 to November 2026, Match's mention count rose from 448 to 634, while its recommendation count rose from 365 to 374. The recommendation rate was 51.99% and 55.41% respectively.

Match appears in most answers but has one of the lowest recommendation-to-mention ratios among the tracked companies, so a large share of its appearances carried no endorsement. Its placements are moderate relative to its recommendation total.

Framing is notably more neutral than for peers, with fewer positive mentions. The prior-month comparison shows a much higher mention count and a slightly higher recommendation count, while the recommendation rate rose modestly; the change in reach and the change in rate should be read separately.

Grindr

Questions This Section Answers

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

Grindr ranks 7 by recommendation count. Mentions: 312 (46.22%); recommendations: 262 (38.81%). Top 3 placements: 10 (1.48%); first-place placements: 7 (1.04%).

Wording about the company: 263 positive, 46 neutral, 3 negative mentions. The proportion of mentions that also included a recommendation was 84.0%. The net framing score was 0.83 (defined in Methodology).

50 mentions had no recorded recommendation. Of recorded recommendations, 3.82% were Top 3 and 2.67% were first-place.

From October 2026 to November 2026, Grindr's mention count rose from 303 to 312, while its recommendation count rose from 248 to 262. The recommendation rate was 35.33% and 38.81% respectively.

Grindr appears in fewer than half of the recorded answers, and most of its mentions also carry an affirmative recommendation. Its shortlist and first-place placements are very small, so endorsements rarely placed it near the top of an ordering.

Wording is mostly positive with few negative mentions. The prior-month comparison shows both mention and recommendation counts higher, with a higher recommendation rate across separate samples.

HER

Questions This Section Answers

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

HER ranks 8 by recommendation count. Mentions: 273 (40.44%); recommendations: 253 (37.48%). Top 3 placements: 13 (1.93%); first-place placements: 3 (0.44%).

Wording about the company: 254 positive, 19 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 92.7%. The net framing score was 0.93 (defined in Methodology).

20 mentions had no recorded recommendation. Of recorded recommendations, 5.14% were Top 3 and 1.19% were first-place.

From October 2026 to November 2026, HER's mention count rose from 266 to 273, while its recommendation count rose from 228 to 253. The recommendation rate was 32.48% and 37.48% respectively.

HER reaches a minority of answers but has a high recommendation-to-mention ratio, meaning most appearances carried an endorsement. Its shortlist and first-place placements are minimal, so recommendations seldom positioned it near the top.

Framing is positive with no negative mentions recorded. The prior-month comparison shows higher mention and recommendation counts and a higher recommendation rate; these are recorded results in separate samples, not evidence of cause.

Plenty of Fish

Questions This Section Answers

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

Plenty of Fish ranks 9 by recommendation count. Mentions: 279 (41.33%); recommendations: 218 (32.30%). Top 3 placements: 64 (9.48%); first-place placements: 22 (3.26%).

Wording about the company: 223 positive, 35 neutral, 21 negative mentions. The proportion of mentions that also included a recommendation was 78.1%. The net framing score was 0.72 (defined in Methodology).

61 mentions had no recorded recommendation. Of recorded recommendations, 29.36% were Top 3 and 10.09% were first-place.

From October 2026 to November 2026, Plenty of Fish's mention count fell from 282 to 279, while its recommendation count rose from 202 to 218. The recommendation rate was 28.77% and 32.30% respectively.

Plenty of Fish appears in a minority of the recorded answers, and most of its mentions also carry an affirmative recommendation. Its shortlist placements are moderate, and first-place placements are uncommon but present.

Wording includes a comparatively larger negative share alongside mostly positive framing. The prior-month comparison shows a slightly lower mention count and a higher recommendation count, with the recommendation rate rising across separate samples.

Coffee Meets Bagel

Questions This Section Answers

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

Coffee Meets Bagel ranks 10 by recommendation count. Mentions: 242 (35.85%); recommendations: 214 (31.70%). Top 3 placements: 8 (1.19%); first-place placements: 0 (0.00%).

Wording about the company: 217 positive, 25 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 88.4%. The net framing score was 0.90 (defined in Methodology).

28 mentions had no recorded recommendation. Of recorded recommendations, 3.74% were Top 3 and 0.00% were first-place.

From October 2026 to November 2026, Coffee Meets Bagel's mention count rose from 180 to 242, while its recommendation count rose from 150 to 214. The recommendation rate was 21.37% and 31.70% respectively.

Coffee Meets Bagel appears in a minority of the recorded answers, and most of its mentions also carry an affirmative recommendation. Its shortlist placements are very small and no first-place placements were recorded, so endorsements rarely positioned it near the top.

Wording is positive with no negative mentions recorded. The prior-month comparison shows higher mention and recommendation counts and a higher recommendation rate; these are recorded differences between separate samples.

Earlier ranking snapshot context

Questions This Section Answers

• How do the available Online Dating snapshots from August 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.

The monthly table shows separate selected samples, each with its own answer total and coverage. Counts and rates should be read together, since a rate depends on both the recommendation count and the answers included that month.

Rank positions are shown for context only. A changed count or rate between months does not demonstrate improvement, loss of standing or the effect of any intervention, and smaller answer totals do not explain why results moved.

What the November Rankings Show

Reach, recommendation, placement and framing answer different questions. Reach asks whether a company appeared; recommendation asks whether an answer affirmatively endorsed it; placement asks where an endorsement sat within an ordering; framing describes the wording around a mention. A company can be strong on one and weak on another.

The leaderboard orders by recommendation count, but the profiles show that high reach does not guarantee high endorsement, and high endorsement does not guarantee top placements. These are descriptions of the reviewed AI answers, not verified product facts, customer sentiment or commercial outcomes.

Methodology

Questions This Section Answers

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

This benchmark has partial coverage: 3 of 3 planned question categories contributed usable observations; 0 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; 10 tracked companies. AI services represented: ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity.

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.

The benchmark covers a partial set of answers, and the reporting month is a label rather than a verified collection date. Each company is counted at most once per answer, and placement results are nested within recommendations rather than added to them.

Recommendation-to-mention ratios and framing scores describe answer wording, not customer conversion, satisfaction or company quality. Monthly samples differ, so comparisons show recorded changes without establishing why they occurred. The results describe the AI answers reviewed, not independently verified facts about the companies.