Chatbots AI Visibility Ranking Trends - November 2026

Answer capsule

The November 2026 Chatbots benchmark compares 10 companies across 253 AI answers that met its inclusion rules. Intercom leads with 92 recommendations (36.36% of answers). At least one tracked company was recommended in 129 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 Chatbots

Industry leaderboard

Questions This Section Answers

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

The leaderboard orders companies by how many answers affirmatively recommended them, so it measures recorded endorsement rather than mere appearance. A company can be named often without being recommended, which is why mention counts and recommendation counts answer different questions.

Ties are genuine equalities in recommendation counts, not near-misses to be broken by other columns. Placement figures sit inside recommendations: a first-place result is also a shortlist result, and both are subsets of the recommendation total.

Key findings

Tracked-company answer coverage

Questions This Section Answers

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

129 distinct answers recommended at least one tracked company. Counting each company recommendation separately gives 370, because an answer can recommend several companies. Answers with no tracked recommendation may still have recommended companies outside this comparison.

Every included answer named at least one tracked company, but only about half recommended one. That gap separates presence from endorsement: being discussed is not the same as being put forward.

Because a single answer can recommend several companies, company-level recommendation totals exceed the number of answers carrying any recommendation. Overlapping coverage therefore describes how often companies share answers, not how much of the market any one company holds.

Reach and affirmative recommendation

Intercom ranks 1 by recommendation count. Mentions: 201 (79.45%); recommendations: 92 (36.36%). Top 3 placements: 67 (26.48%); first-place placements: 29 (11.46%).

Wording about the company: 96 positive, 105 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 45.8%. The net framing score was 0.48 (defined in Methodology).

109 mentions had no recorded recommendation. Of recorded recommendations, 72.83% were Top 3 and 31.52% were first-place.

Intercom leads on recommendation count, but its mentions far outnumber its recommendations. Many answers named the company without endorsing it, so reach and affirmative recommendation should be read as separate measures.

The recommendation-to-mention ratio captures that difference within a company's own mentions. A high ratio on a small mention base is less stable than the same ratio on a large one, and the printed counts should be checked alongside any ratio.

Recommendation order and placement

Placement describes where a recommended company appeared in an answer's ordering. Top-three and first-place counts are nested within recommendations, so they refine the recommendation picture rather than adding new wins.

A company can be recommended frequently yet rarely placed first, while another with fewer recommendations may sit near the top of the order more often. These are different readings of the same recorded answers, not evidence of customer preference or conversion.

Classified framing in context

Framing records the wording used around a company in the selected answers: positive, neutral or negative. It is a description of language, not a measure of reputation, customer sentiment or product quality.

Most mentions here are neutral or positive, and neutral wording does not explain why a recommendation was or was not recorded. Negative wording appears for only one company, and its presence should be read as a recorded classification rather than a cause of other results.

Company results in detail

Intercom

Questions This Section Answers

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

Intercom ranks 1 by recommendation count. Mentions: 201 (79.45%); recommendations: 92 (36.36%). Top 3 placements: 67 (26.48%); first-place placements: 29 (11.46%).

Wording about the company: 96 positive, 105 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 45.8%. The net framing score was 0.48 (defined in Methodology).

109 mentions had no recorded recommendation. Of recorded recommendations, 72.83% were Top 3 and 31.52% were first-place.

From October 2026 to November 2026, Intercom's mention count fell from 374 to 201, while its recommendation count fell from 294 to 92. The recommendation rate was 67.43% and 36.36% respectively.

Intercom holds the top recommendation count, supported by the widest mention reach in the set. Its wording is entirely positive or neutral, with no negative mentions recorded.

Its recommendation-to-mention ratio is moderate: many answers named the company without endorsing it. Among its recommendations, most were shortlisted and a substantial minority placed first, showing that endorsement often came with prominent ordering.

Tidio

Questions This Section Answers

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

Tidio ranks 2 by recommendation count. Mentions: 176 (69.57%); recommendations: 91 (35.97%). Top 3 placements: 58 (22.92%); first-place placements: 21 (8.30%).

Wording about the company: 95 positive, 81 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 51.7%. The net framing score was 0.54 (defined in Methodology).

85 mentions had no recorded recommendation. Of recorded recommendations, 63.74% were Top 3 and 23.08% were first-place.

From October 2026 to November 2026, Tidio's mention count fell from 321 to 176, while its recommendation count fell from 267 to 91. The recommendation rate was 61.24% and 35.97% respectively.

Tidio ranks second by recommendation count in this month's answers. Mentions and recommendations both appear frequently, and every recorded mention carried positive or neutral wording, with none negative. The share of mentions that also included an affirmative endorsement is a property of the recorded answers, not of customers or sales.

Among its recommendations, most were shortlist placements and a smaller subset were first-place placements. The October-to-November comparison shows lower mention and recommendation counts alongside a lower recommendation rate; because these are separate selected samples, the figures do not establish why the change occurred.

Zendesk Chat

Questions This Section Answers

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

Zendesk Chat ranks 3 by recommendation count. Mentions: 152 (60.08%); recommendations: 70 (27.67%). Top 3 placements: 46 (18.18%); first-place placements: 19 (7.51%).

Wording about the company: 74 positive, 78 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 46.1%. The net framing score was 0.49 (defined in Methodology).

82 mentions had no recorded recommendation. Of recorded recommendations, 65.71% were Top 3 and 27.14% were first-place.

From October 2026 to November 2026, Zendesk Chat's mention count fell from 249 to 152, while its recommendation count fell from 192 to 70. The recommendation rate was 44.04% and 27.67% respectively.

Zendesk Chat occupies a clear third position, with recommendation and mention counts below the two leaders but well above the rest of the field. Its framing is positive or neutral throughout.

Its recommendation-to-mention ratio is close to Intercom's, suggesting a similar balance between being named and being endorsed. Placement within recommendations is also comparable, with a meaningful share of first-place results.

Freshdesk

Questions This Section Answers

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

Freshdesk ranks 4 by recommendation count. Mentions: 76 (30.04%); recommendations: 27 (10.67%). Top 3 placements: 13 (5.14%); first-place placements: 1 (0.40%).

Wording about the company: 28 positive, 48 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 35.5%. The net framing score was 0.37 (defined in Methodology).

49 mentions had no recorded recommendation. Of recorded recommendations, 48.15% were Top 3 and 3.70% were first-place.

From October 2026 to November 2026, Freshdesk's mention count fell from 129 to 76, while its recommendation count fell from 87 to 27. The recommendation rate was 19.95% and 10.67% respectively.

Freshdesk ranks fourth on recommendations, but its mention reach is comparatively modest and its recommendation-to-mention ratio is lower than the leading group. Framing is positive or neutral.

First-place placements are rare relative to its recommendations, so its endorsements tend to appear on the shortlist rather than at the top of the ordering. This is a placement pattern, not a statement about product standing.

LiveChat (Text S.A. (formerly LiveChat Software S.A.)

Questions This Section Answers

• What do the November 2026 AI answer results show about LiveChat (Text S.A. (formerly LiveChat Software S.A.) mentions, recommendations and placement?

LiveChat (Text S.A. (formerly LiveChat Software S.A.) ranks 5 by recommendation count. Mentions: 105 (41.50%); recommendations: 26 (10.28%). Top 3 placements: 18 (7.11%); first-place placements: 11 (4.35%).

Wording about the company: 30 positive, 75 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 24.8%. The net framing score was 0.29 (defined in Methodology).

79 mentions had no recorded recommendation. Of recorded recommendations, 69.23% were Top 3 and 42.31% were first-place.

From October 2026 to November 2026, LiveChat (Text S.A. (formerly LiveChat Software S.A.)'s mention count fell from 154 to 105, while its recommendation count fell from 119 to 26. The recommendation rate was 27.29% and 10.28% respectively.

LiveChat has substantial mention reach but a comparatively low recommendation-to-mention ratio, meaning many answers named it without endorsing it. Framing is positive or neutral.

Among the recommendations it did receive, a large share were shortlisted and a notable share placed first. Its profile therefore combines wide visibility with selective endorsement and strong ordering when endorsement occurs.

Ada

Questions This Section Answers

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

Ada ranks 6 by recommendation count. Mentions: 48 (18.97%); recommendations: 21 (8.30%). Top 3 placements: 12 (4.74%); first-place placements: 4 (1.58%).

Wording about the company: 21 positive, 27 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 43.8%. The net framing score was 0.44 (defined in Methodology).

27 mentions had no recorded recommendation. Of recorded recommendations, 57.14% were Top 3 and 19.05% were first-place.

From October 2026 to November 2026, Ada's mention count fell from 53 to 48, while its recommendation count fell from 40 to 21. The recommendation rate was 9.17% and 8.30% respectively.

Ada records a mid-table recommendation count on a relatively small mention base, giving it a recommendation-to-mention ratio close to the leading group. Framing is positive or neutral.

Its placement profile is more modest: a majority of recommendations were shortlisted, but first-place results were less common. The smaller base means these proportions should be read with appropriate caution.

ManyChat

Questions This Section Answers

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

ManyChat ranks 6 by recommendation count. Mentions: 73 (28.85%); recommendations: 21 (8.30%). Top 3 placements: 15 (5.93%); first-place placements: 10 (3.95%).

Wording about the company: 24 positive, 43 neutral, 6 negative mentions. The proportion of mentions that also included a recommendation was 28.8%. The net framing score was 0.25 (defined in Methodology).

52 mentions had no recorded recommendation. Of recorded recommendations, 71.43% were Top 3 and 47.62% were first-place.

From October 2026 to November 2026, ManyChat's mention count fell from 99 to 73, while its recommendation count fell from 80 to 21. The recommendation rate was 18.35% and 8.30% respectively.

ManyChat shares a recommendation count with Ada but reaches more mentions, so its recommendation-to-mention ratio is lower. It is also the only company in the set with negative mentions recorded alongside positive and neutral ones.

Among its recommendations, a high share were shortlisted and nearly half placed first, indicating that when endorsement occurred it often came with prominent ordering.

Chatfuel

Questions This Section Answers

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

Chatfuel ranks 8 by recommendation count. Mentions: 29 (11.46%); recommendations: 10 (3.95%). Top 3 placements: 4 (1.58%); first-place placements: 3 (1.19%).

Wording about the company: 12 positive, 17 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 34.5%. The net framing score was 0.41 (defined in Methodology).

19 mentions had no recorded recommendation. Of recorded recommendations, 40.00% were Top 3 and 30.00% were first-place.

From October 2026 to November 2026, Chatfuel's mention count rose from 21 to 29, while its recommendation count fell from 17 to 10. The recommendation rate was 3.90% and 3.95% respectively.

Chatfuel records a modest recommendation count on a small mention base, with framing that is positive or neutral. Its recommendation-to-mention ratio sits in the middle of the field.

Placement within recommendations is mixed: fewer than half were shortlisted, and first-place results were uncommon. With limited counts, these proportions are best treated as indicative rather than stable.

Drift

Questions This Section Answers

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

Drift ranks 9 by recommendation count. Mentions: 33 (13.04%); recommendations: 6 (2.37%). Top 3 placements: 4 (1.58%); first-place placements: 0 (0.00%).

Wording about the company: 6 positive, 27 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 18.2%. The net framing score was 0.18 (defined in Methodology).

27 mentions had no recorded recommendation. Of recorded recommendations, 66.67% were Top 3 and 0.00% were first-place.

From October 2026 to November 2026, Drift's mention count fell from 68 to 33, while its recommendation count fell from 44 to 6. The recommendation rate was 10.09% and 2.37% respectively.

Drift records one of the lowest recommendation counts in the set despite a mention count above several peers, giving it the weakest recommendation-to-mention ratio. Framing is positive or neutral.

No first-place placements were recorded for Drift, so its recommendations appeared only on the shortlist. This is a measured placement result, not evidence about the company's products or prospects.

Landbot

Questions This Section Answers

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

Landbot ranks 9 by recommendation count. Mentions: 16 (6.32%); recommendations: 6 (2.37%). Top 3 placements: 3 (1.19%); first-place placements: 2 (0.79%).

Wording about the company: 6 positive, 10 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 37.5%. The net framing score was 0.38 (defined in Methodology).

10 mentions had no recorded recommendation. Of recorded recommendations, 50.00% were Top 3 and 33.33% were first-place.

From October 2026 to November 2026, Landbot's mention count fell from 25 to 16, while its recommendation count fell from 18 to 6. The recommendation rate was 4.13% and 2.37% respectively.

Landbot records a small recommendation count on the smallest mention base in the set, with framing that is positive or neutral. Its recommendation-to-mention ratio is mid-range.

Among its few recommendations, half were shortlisted and a third placed first. These proportions rest on very limited counts and should be read as descriptive of the recorded answers rather than as stable characteristics.

Earlier ranking snapshot context

Questions This Section Answers

• How do the available Chatbots 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.

The monthly snapshots come from separate answer samples, so counts and rates are comparable in form but not in sampling. A lower count in one month does not by itself show a change in standing.

Rank positions are also sample-specific: a company can hold its rank while its counts move, or shift rank as others move. The comparisons record what changed; they do not establish why.

What the November Rankings Show

These rankings answer several distinct questions. Reach asks how often a company was named at all. Recommendation asks how often an answer affirmatively endorsed it. Placement asks where that endorsement sat in the ordering. Framing asks what wording surrounded the name.

A company can be widely named yet rarely endorsed, or endorsed often but rarely placed first. Reading the columns together gives a fuller picture than any single count, while each remains a description of the recorded AI answers rather than of customers, sales or product quality.

Methodology

Questions This Section Answers

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

This benchmark has partial coverage: 2 of 3 planned question categories contributed usable observations; 1 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:

July 2026 measured a different set of companies, so it is excluded from this comparison. August 2026 measured a different set of companies, so it is excluded from this comparison.

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 some planned question categories contributed usable answers, and the exact collection dates are unverified. Findings describe the available answer set, not the full space of possible questions.

Each company is counted at most once per answer, and placement results are nested within recommendations rather than added to them. Rates use the full benchmark answer total, while the recommendation-to-mention ratio describes answer wording, not conversion. Net framing is a wording score, not a measure of customer satisfaction or company quality. Monthly samples differ, so comparisons show recorded change without establishing its cause.