Language Learning Software AI Visibility Ranking Trends - November 2026

Answer capsule

The November 2026 Language Learning Software benchmark compares 10 companies across 529 AI answers that met its inclusion rules. Duolingo leads with 473 recommendations (89.41% of answers). At least one tracked company was recommended in 509 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 Language Learning Software

Industry leaderboard

Questions This Section Answers

• How do Language Learning Software rank by recorded AI recommendations in November 2026?

The leaderboard orders companies by how many answers affirmatively recommended them, so it measures recorded endorsement volume rather than overall quality. A company can appear in many answers without being recommended, and recommendation counts can tie. Placement figures sit inside recommendations: shortlist and first-place results are subsets, not separate wins, and should be read alongside mention and recommendation rates rather than added to them.

Key findings

Tracked-company answer coverage

Questions This Section Answers

• How often did the November 2026 Language Learning Software answer sample recommend any tracked company?

509 distinct answers recommended at least one tracked company. Counting each company recommendation separately gives 2359, because an answer can recommend several companies. Answers with no tracked recommendation may still have recommended companies outside this comparison.

Nearly every qualified answer named at least one tracked company, and most recommended more than one. That overlap means company totals cannot be summed into a market share, because a single answer may endorse several products. The small remainder with no tracked recommendation may still have named companies outside this comparison, so coverage describes these answers only.

Reach and affirmative recommendation

Duolingo ranks 1 by recommendation count. Mentions: 517 (97.73%); recommendations: 473 (89.41%). Top 3 placements: 356 (67.30%); first-place placements: 234 (44.23%).

Wording about the company: 473 positive, 39 neutral, 5 negative mentions. The proportion of mentions that also included a recommendation was 91.5%. The net framing score was 0.91 (defined in Methodology).

44 mentions had no recorded recommendation. Of recorded recommendations, 75.26% were Top 3 and 49.47% were first-place.

Mention records that a company appeared in an answer; recommendation records an affirmative endorsement. Duolingo leads on recommendation count, but its mentions exceed its recommendations, and a minority of mentions carried no recommendation. Placement figures are nested within recommendations, so first-place counts are a subset of shortlist counts rather than an additional measure of reach.

Recommendation order and placement

Placement describes where a recommended company sat in the answer's ordering. Shortlist and first-place counts are subsets of recommendations, so they cannot be added to recommendation totals or compared as if they shared a separate base. Recommendation-to-mention ratios vary widely across companies, and the smaller bases near the bottom of the table warrant caution when reading a strong ratio.

Classified framing in context

Framing classifies the wording used about each company in the selected answers. Positive wording dominates for every tracked company, with neutral mentions forming the bulk of the remainder and negative mentions rare. This describes answer language, not customer sentiment or company quality, and it does not explain why recommendations occurred or did not.

Company results in detail

Duolingo

Questions This Section Answers

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

Duolingo ranks 1 by recommendation count. Mentions: 517 (97.73%); recommendations: 473 (89.41%). Top 3 placements: 356 (67.30%); first-place placements: 234 (44.23%).

Wording about the company: 473 positive, 39 neutral, 5 negative mentions. The proportion of mentions that also included a recommendation was 91.5%. The net framing score was 0.91 (defined in Methodology).

44 mentions had no recorded recommendation. Of recorded recommendations, 75.26% were Top 3 and 49.47% were first-place.

From October 2026 to November 2026, Duolingo's mention count rose from 512 to 517, while its recommendation count rose from 461 to 473. The recommendation rate was 85.53% and 89.41% respectively.

Duolingo leads the recommendation count and appears in almost every qualified answer, giving it the broadest reach in this sample. Its recommendation-to-mention ratio is high but not the highest, and roughly half of its recommendations placed first. Positive framing dominates its mentions, with neutral wording a small minority and negative wording rare.

Babbel

Questions This Section Answers

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

Babbel ranks 2 by recommendation count. Mentions: 473 (89.41%); recommendations: 448 (84.69%). Top 3 placements: 379 (71.64%); first-place placements: 108 (20.42%).

Wording about the company: 448 positive, 22 neutral, 3 negative mentions. The proportion of mentions that also included a recommendation was 94.7%. The net framing score was 0.94 (defined in Methodology).

25 mentions had no recorded recommendation. Of recorded recommendations, 84.60% were Top 3 and 24.11% were first-place.

From October 2026 to November 2026, Babbel's mention count rose from 465 to 473, while its recommendation count rose from 439 to 448. The recommendation rate was 81.45% and 84.69% respectively.

Babbel holds second place by recommendation count with a high recommendation-to-mention ratio. Its distinctive feature is placement: a large majority of its recommendations landed in the shortlist, though first-place finishes were a smaller share than Duolingo's. Framing is overwhelmingly positive, with few neutral or negative mentions.

Pimsleur

Questions This Section Answers

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

Pimsleur ranks 3 by recommendation count. Mentions: 430 (81.29%); recommendations: 416 (78.64%). Top 3 placements: 264 (49.91%); first-place placements: 28 (5.29%).

Wording about the company: 416 positive, 13 neutral, 1 negative mentions. The proportion of mentions that also included a recommendation was 96.7%. The net framing score was 0.97 (defined in Methodology).

14 mentions had no recorded recommendation. Of recorded recommendations, 63.46% were Top 3 and 6.73% were first-place.

From October 2026 to November 2026, Pimsleur's mention count rose from 406 to 430, while its recommendation count rose from 388 to 416. The recommendation rate was 71.99% and 78.64% respectively.

Pimsleur ranks third and records the highest recommendation-to-mention ratio among the top companies, meaning most of its mentions carried an endorsement. Its shortlist share is substantial, but first-place finishes are comparatively rare. Framing is almost entirely positive, with very few neutral mentions and a single negative one.

italki

Questions This Section Answers

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

italki ranks 4 by recommendation count. Mentions: 323 (61.06%); recommendations: 303 (57.28%). Top 3 placements: 85 (16.07%); first-place placements: 29 (5.48%).

Wording about the company: 303 positive, 20 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 93.8%. The net framing score was 0.94 (defined in Methodology).

20 mentions had no recorded recommendation. Of recorded recommendations, 28.05% were Top 3 and 9.57% were first-place.

From October 2026 to November 2026, italki's mention count rose from 274 to 323, while its recommendation count rose from 251 to 303. The recommendation rate was 46.57% and 57.28% respectively.

italki sits fourth by recommendation count with a strong recommendation-to-mention ratio. Its placements skew toward the shortlist rather than first place, and its first-place share is modest. Framing is positive across its mentions with no negative wording recorded, and neutral mentions form a small minority.

Busuu

Questions This Section Answers

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

Busuu ranks 5 by recommendation count. Mentions: 275 (51.98%); recommendations: 259 (48.96%). Top 3 placements: 91 (17.20%); first-place placements: 8 (1.51%).

Wording about the company: 259 positive, 15 neutral, 1 negative mentions. The proportion of mentions that also included a recommendation was 94.2%. The net framing score was 0.94 (defined in Methodology).

16 mentions had no recorded recommendation. Of recorded recommendations, 35.14% were Top 3 and 3.09% were first-place.

From October 2026 to November 2026, Busuu's mention count rose from 246 to 275, while its recommendation count rose from 235 to 259. The recommendation rate was 43.60% and 48.96% respectively.

Busuu ranks fifth, with a recommendation-to-mention ratio close to the leaders. Its shortlist placements are a meaningful share of recommendations, but first-place finishes are rare. Positive framing dominates its mentions, with neutral wording a small fraction and a single negative mention recorded.

Rosetta Stone

Questions This Section Answers

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

Rosetta Stone ranks 6 by recommendation count. Mentions: 199 (37.62%); recommendations: 163 (30.81%). Top 3 placements: 55 (10.40%); first-place placements: 4 (0.76%).

Wording about the company: 164 positive, 35 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 81.9%. The net framing score was 0.82 (defined in Methodology).

36 mentions had no recorded recommendation. Of recorded recommendations, 33.74% were Top 3 and 2.45% were first-place.

From October 2026 to November 2026, Rosetta Stone's mention count fell from 230 to 199, while its recommendation count fell from 186 to 163. The recommendation rate was 34.51% and 30.81% respectively.

Rosetta Stone ranks sixth and stands out for a comparatively low recommendation-to-mention ratio, meaning a larger share of its mentions carried no endorsement. Neutral framing is more prominent here than for most peers. Its placements are mostly shortlist entries, with first-place finishes uncommon.

Memrise

Questions This Section Answers

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

Memrise ranks 7 by recommendation count. Mentions: 150 (28.36%); recommendations: 129 (24.39%). Top 3 placements: 32 (6.05%); first-place placements: 2 (0.38%).

Wording about the company: 129 positive, 20 neutral, 1 negative mentions. The proportion of mentions that also included a recommendation was 86.0%. The net framing score was 0.85 (defined in Methodology).

21 mentions had no recorded recommendation. Of recorded recommendations, 24.81% were Top 3 and 1.55% were first-place.

From October 2026 to November 2026, Memrise's mention count fell from 161 to 150, while its recommendation count fell from 138 to 129. The recommendation rate was 25.60% and 24.39% respectively.

Memrise ranks seventh with a moderate recommendation-to-mention ratio. Shortlist placements account for a modest share of its recommendations, and first-place finishes are rare. Positive framing leads its mentions, with neutral wording a noticeable minority and a single negative mention recorded.

Lingoda

Questions This Section Answers

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

Lingoda ranks 8 by recommendation count. Mentions: 113 (21.36%); recommendations: 103 (19.47%). Top 3 placements: 39 (7.37%); first-place placements: 6 (1.13%).

Wording about the company: 103 positive, 10 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 91.2%. The net framing score was 0.91 (defined in Methodology).

10 mentions had no recorded recommendation. Of recorded recommendations, 37.86% were Top 3 and 5.83% were first-place.

From October 2026 to November 2026, Lingoda's mention count fell from 125 to 113, while its recommendation count fell from 115 to 103. The recommendation rate was 21.34% and 19.47% respectively.

Lingoda ranks eighth, and its recommendation-to-mention ratio is close to the leaders despite its lower overall reach. Shortlist placements form a meaningful portion of its recommendations, while first-place finishes are uncommon. Its mentions are predominantly positive, with neutral wording a small minority and no negative mentions.

Mango Languages

Questions This Section Answers

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

Mango Languages ranks 9 by recommendation count. Mentions: 57 (10.78%); recommendations: 46 (8.70%). Top 3 placements: 12 (2.27%); first-place placements: 3 (0.57%).

Wording about the company: 46 positive, 11 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 80.7%. The net framing score was 0.81 (defined in Methodology).

11 mentions had no recorded recommendation. Of recorded recommendations, 26.09% were Top 3 and 6.52% were first-place.

From October 2026 to November 2026, Mango Languages' mention count rose from 56 to 57, while its recommendation count stayed at 46. The recommendation rate was 8.53% and 8.70% respectively. The count was unchanged: the rate difference comes from dividing it by 539 answers in October 2026 and 529 in November.

Mango Languages ranks ninth with a comparatively low recommendation-to-mention ratio, so a notable share of its mentions carried no endorsement. Its placement counts are small in absolute terms, and the ratios derived from them rest on sparse bases. Framing is mostly positive, with neutral mentions forming a larger minority than for most peers.

Mondly

Questions This Section Answers

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

Mondly ranks 10 by recommendation count. Mentions: 28 (5.29%); recommendations: 19 (3.59%). Top 3 placements: 8 (1.51%); first-place placements: 3 (0.57%).

Wording about the company: 19 positive, 9 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 67.9%. The net framing score was 0.68 (defined in Methodology).

9 mentions had no recorded recommendation. Of recorded recommendations, 42.11% were Top 3 and 15.79% were first-place.

From October 2026 to November 2026, Mondly's mention count fell from 41 to 28, while its recommendation count fell from 28 to 19. The recommendation rate was 5.19% and 3.59% respectively.

Mondly ranks tenth and records the lowest recommendation-to-mention ratio in the table, meaning many of its mentions lacked an endorsement. Its placement counts are very small, so the shares derived from them should be read cautiously. Neutral framing is proportionally more prominent here than for any other tracked company.

Earlier ranking snapshot context

Questions This Section Answers

• How do the available Language Learning Software 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, so counts and rates are comparable in form but not drawn from identical answer sets. Rank order held steady across the displayed months, but that stability describes the recorded samples only. A changed count or rate does not by itself demonstrate improvement, decline or the effect of any intervention.

What the November Rankings Show

These measures answer different questions. Reach asks whether a company appeared at all; recommendation asks whether the answer affirmatively endorsed it; placement asks where an endorsement sat in the ordering; framing asks how the company was described. A company can be widely mentioned yet rarely recommended, or strongly endorsed within a smaller set of answers. Reading the measures together shows the shape of each company's presence without establishing why any pattern arose.

Methodology

Questions This Section Answers

• How were the November 2026 Language Learning Software 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.

These results cover a partial set of AI answers from several services, and the exact collection dates have not been verified. Each company is counted at most once per answer, and one answer may cover several companies, so totals should not be summed. Recommendation requires both affirmative endorsement and positive wording. Placement figures are nested within recommendations. Net framing describes answer wording, not customer satisfaction or company quality, and the samples differ between months.