Meal Delivery Services AI Visibility Ranking Trends - November 2026

Answer capsule

The November 2026 Meal Delivery Services benchmark compares 10 companies across 658 AI answers that met its inclusion rules. Factor leads with 526 recommendations (79.94% of answers). At least one tracked company was recommended in 621 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 Meal Delivery Services

Industry leaderboard

Questions This Section Answers

• How do Meal Delivery Services rank by recorded AI recommendations in November 2026?

The leaderboard orders companies by how many recorded answers affirmatively recommended them. That count is a reach measure, not a quality score: a company can appear often yet be endorsed less often, and the two are reported separately.

Ties matter because equal recommendation counts share a rank, so adjacent positions may not imply a strict ordering. Mentions, recommendations, shortlist placements and first-place placements answer different questions, and placements sit inside recommendations rather than adding to them.

Key findings

Tracked-company answer coverage

Questions This Section Answers

• How often did the November 2026 Meal Delivery Services answer sample recommend any tracked company?

621 distinct answers recommended at least one tracked company. Counting each company recommendation separately gives 3707, 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 one. Because a single answer can endorse several companies, company-level totals exceed the number of answers; summing them would double-count answers.

A small share of answers recommended no tracked company, and those may still have named companies outside this comparison. Coverage therefore describes the reviewed answers, not the whole meal-delivery market.

Reach and affirmative recommendation

Factor ranks 1 by recommendation count. Mentions: 582 (88.45%); recommendations: 526 (79.94%). Top 3 placements: 272 (41.34%); first-place placements: 85 (12.92%).

Wording about the company: 531 positive, 51 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 90.4%. The net framing score was 0.91 (defined in Methodology).

56 mentions had no recorded recommendation. Of recorded recommendations, 51.71% were Top 3 and 16.16% were first-place.

Factor's profile separates appearance from endorsement: it was mentioned in most answers and recommended in most of those, leaving a modest set of mentions without a recorded recommendation. Ranking first by recommendation count reflects that volume, not a claim of superiority.

Placement figures are subsets of the recommendations, so shortlist and first-place counts should be read within that base rather than as separate wins.

Recommendation order and placement

Placement describes where a recommended company appeared in an answer's ordering. Shortlist placements are a subset of recommendations, and first-place placements are a subset of shortlists, so the categories nest rather than accumulate.

The recommendation-to-mention ratio compares endorsements with appearances in the recorded answers. It is not a conversion rate, and a high ratio on a smaller mention base deserves caution when read as a strength.

Classified framing in context

Framing classifies the wording attached to each mention as positive, neutral or negative. Across the tracked companies, negative wording was not recorded, and neutral wording formed a minority of mentions.

This describes how the answers phrased their references, not customer sentiment or company quality. Positive wording does not explain why a recommendation was or was not recorded, and the classification should not be read as reputation.

Company results in detail

Factor

Questions This Section Answers

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

Factor ranks 1 by recommendation count. Mentions: 582 (88.45%); recommendations: 526 (79.94%). Top 3 placements: 272 (41.34%); first-place placements: 85 (12.92%).

Wording about the company: 531 positive, 51 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 90.4%. The net framing score was 0.91 (defined in Methodology).

56 mentions had no recorded recommendation. Of recorded recommendations, 51.71% were Top 3 and 16.16% were first-place.

From October 2026 to November 2026, Factor's mention count fell from 594 to 582, while its recommendation count fell from 532 to 526. The recommendation rate was 78.58% and 79.94% respectively.

Factor leads on recommendation count, with mentions and endorsements closely aligned and few appearances lacking a recommendation. Its placements are frequent relative to its recommendation base, and first-place results form a smaller subset of those shortlists.

Wording was overwhelmingly positive with no negative mentions recorded. The month-to-month comparison shows slightly lower mention and recommendation counts alongside a marginally higher recommendation rate; the separate samples do not explain that movement.

HelloFresh

Questions This Section Answers

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

HelloFresh ranks 2 by recommendation count. Mentions: 579 (87.99%); recommendations: 514 (78.12%). Top 3 placements: 411 (62.46%); first-place placements: 198 (30.09%).

Wording about the company: 514 positive, 65 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 88.8%. The net framing score was 0.89 (defined in Methodology).

65 mentions had no recorded recommendation. Of recorded recommendations, 79.96% were Top 3 and 38.52% were first-place.

From October 2026 to November 2026, HelloFresh's mention count fell from 591 to 579, while its recommendation count fell from 517 to 514. The recommendation rate was 76.37% and 78.12% respectively.

HelloFresh sits just behind the leader on recommendation count, but its placement profile is distinctive: a large share of its recommendations were shortlisted, and a substantial portion reached first place. That pattern separates it from companies with similar reach but weaker ordering.

Framing was mostly positive with some neutral mentions and none negative. Its recommendation rate edged higher while counts dipped slightly between the two months, a comparison the separate samples cannot explain.

CookUnity

Questions This Section Answers

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

CookUnity ranks 3 by recommendation count. Mentions: 553 (84.04%); recommendations: 509 (77.36%). Top 3 placements: 299 (45.44%); first-place placements: 123 (18.69%).

Wording about the company: 513 positive, 40 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 92.0%. The net framing score was 0.93 (defined in Methodology).

44 mentions had no recorded recommendation. Of recorded recommendations, 58.74% were Top 3 and 24.17% were first-place.

From October 2026 to November 2026, CookUnity's mention count rose from 546 to 553, while its recommendation count rose from 487 to 509. The recommendation rate was 71.94% and 77.36% respectively.

CookUnity combines strong reach with a high recommendation-to-mention ratio, meaning most appearances carried an endorsement. Its shortlist and first-place placements are frequent within its recommendation base, giving it a notable ordering presence alongside its volume.

Framing was largely positive with a small neutral remainder. Both mention and recommendation counts rose across the two months, and the recommendation rate increased; the changed samples do not establish why.

Home Chef

Questions This Section Answers

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

Home Chef ranks 4 by recommendation count. Mentions: 507 (77.05%); recommendations: 445 (67.63%). Top 3 placements: 268 (40.73%); first-place placements: 34 (5.17%).

Wording about the company: 447 positive, 60 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 87.8%. The net framing score was 0.88 (defined in Methodology).

62 mentions had no recorded recommendation. Of recorded recommendations, 60.22% were Top 3 and 7.64% were first-place.

From October 2026 to November 2026, Home Chef's mention count rose from 473 to 507, while its recommendation count rose from 407 to 445. The recommendation rate was 60.12% and 67.63% respectively.

Home Chef's reach is solid, and most of its mentions carried a recommendation. Its shortlist placements are common within that base, but first-place placements are comparatively rare, so its ordering presence is concentrated in lower positions.

Wording was mostly positive with a neutral minority and no negatives. Both counts and the recommendation rate rose between the two months, a recorded comparison whose cause the separate samples cannot identify.

EveryPlate

Questions This Section Answers

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

EveryPlate ranks 5 by recommendation count. Mentions: 459 (69.76%); recommendations: 402 (61.09%). Top 3 placements: 109 (16.57%); first-place placements: 9 (1.37%).

Wording about the company: 419 positive, 40 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 87.6%. The net framing score was 0.91 (defined in Methodology).

57 mentions had no recorded recommendation. Of recorded recommendations, 27.11% were Top 3 and 2.24% were first-place.

From October 2026 to November 2026, EveryPlate's mention count fell from 472 to 459, while its recommendation count fell from 422 to 402. The recommendation rate was 62.33% and 61.09% respectively.

EveryPlate's mentions usually carried a recommendation, but its placement profile is thin: shortlist placements are a modest fraction of its recommendations, and first-place results are rare. Reach and endorsement are stronger than ordering presence here.

Framing was predominantly positive with some neutral mentions. Counts and the recommendation rate declined slightly across the two months; that comparison is reported without attributing it to sample size or any other cause.

Green Chef

Questions This Section Answers

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

Green Chef ranks 6 by recommendation count. Mentions: 438 (66.57%); recommendations: 381 (57.90%). Top 3 placements: 71 (10.79%); first-place placements: 7 (1.06%).

Wording about the company: 400 positive, 38 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 87.0%. The net framing score was 0.91 (defined in Methodology).

57 mentions had no recorded recommendation. Of recorded recommendations, 18.64% were Top 3 and 1.84% were first-place.

From October 2026 to November 2026, Green Chef's mention count rose from 409 to 438, while its recommendation count rose from 339 to 381. The recommendation rate was 50.07% and 57.90% respectively.

Green Chef's recommendation-to-mention ratio is comparable to higher-ranked peers, but its placements are sparse: shortlist and first-place results form small subsets of its recommendations. The company appears and is endorsed more often than it is ordered highly.

Wording was mostly positive with a neutral minority. Both counts and the recommendation rate rose between the two months, a change the separate samples do not explain.

Purple Carrot

Questions This Section Answers

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

Purple Carrot ranks 7 by recommendation count. Mentions: 340 (51.67%); recommendations: 312 (47.42%). Top 3 placements: 27 (4.10%); first-place placements: 7 (1.06%).

Wording about the company: 327 positive, 13 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 91.8%. The net framing score was 0.96 (defined in Methodology).

28 mentions had no recorded recommendation. Of recorded recommendations, 8.65% were Top 3 and 2.24% were first-place.

From October 2026 to November 2026, Purple Carrot's mention count fell from 417 to 340, while its recommendation count fell from 390 to 312. The recommendation rate was 57.61% and 47.42% respectively.

Purple Carrot shows a high recommendation-to-mention ratio, meaning appearances usually carried an endorsement, yet its placement counts are low relative to that base. Endorsement frequency and ordering presence diverge sharply in this profile.

Framing was almost entirely positive with few neutral mentions. Counts and the recommendation rate fell between the two months; the recorded comparison does not establish why, and the differing samples are not an explanation.

Blue Apron

Questions This Section Answers

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

Blue Apron ranks 8 by recommendation count. Mentions: 310 (47.11%); recommendations: 252 (38.30%). Top 3 placements: 144 (21.88%); first-place placements: 48 (7.29%).

Wording about the company: 256 positive, 54 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 81.3%. The net framing score was 0.83 (defined in Methodology).

58 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, Blue Apron's mention count fell from 350 to 310, while its recommendation count fell from 300 to 252. The recommendation rate was 44.31% and 38.30% respectively.

Blue Apron's recommendation-to-mention ratio is lower than most peers, with a larger share of appearances lacking an endorsement. Among its recommendations, however, shortlist and first-place placements are relatively common, so ordering presence is stronger than its reach suggests.

Framing included a notable neutral share alongside positive wording. Counts and the recommendation rate declined across the two months, a comparison reported without causal attribution.

Marley Spoon

Questions This Section Answers

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

Marley Spoon ranks 9 by recommendation count. Mentions: 281 (42.71%); recommendations: 240 (36.47%). Top 3 placements: 148 (22.49%); first-place placements: 87 (13.22%).

Wording about the company: 245 positive, 36 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 85.4%. The net framing score was 0.87 (defined in Methodology).

41 mentions had no recorded recommendation. Of recorded recommendations, 61.67% were Top 3 and 36.25% were first-place.

From October 2026 to November 2026, Marley Spoon's mention count rose from 267 to 281, while its recommendation count rose from 235 to 240. The recommendation rate was 34.71% and 36.47% respectively.

Marley Spoon has moderate reach but a distinctive ordering profile: a large share of its recommendations were shortlisted, and many of those reached first place. Its placement intensity stands out relative to its mention volume.

Framing was mostly positive with some neutral mentions. Both counts rose slightly and the recommendation rate edged up between the two months; the separate samples do not explain the movement.

Sunbasket

Questions This Section Answers

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

Sunbasket ranks 10 by recommendation count. Mentions: 164 (24.92%); recommendations: 126 (19.15%). Top 3 placements: 20 (3.04%); first-place placements: 6 (0.91%).

Wording about the company: 139 positive, 25 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 76.8%. The net framing score was 0.85 (defined in Methodology).

38 mentions had no recorded recommendation. Of recorded recommendations, 15.87% were Top 3 and 4.76% were first-place.

From October 2026 to November 2026, Sunbasket's mention count fell from 255 to 164, while its recommendation count fell from 228 to 126. The recommendation rate was 33.68% and 19.15% respectively.

Sunbasket has the smallest reach in this comparison, and its recommendation-to-mention ratio is the lowest recorded, meaning a larger share of its appearances lacked an endorsement. Its placements are correspondingly sparse.

Framing was mostly positive with a neutral minority. Counts and the recommendation rate fell sharply between the two months; that recorded comparison is reported without attributing it to sample size or any other cause.

Earlier ranking snapshot context

Questions This Section Answers

• How do the available Meal Delivery Services 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 snapshots come from separate answer samples, so counts and rates should be read together rather than as a continuous series. A lower count can accompany a higher rate, and rank changes reflect the recorded ordering in each month.

These comparisons show how results differed across months; they do not establish why, and a single prior month cannot support claims of first-ever results or stable standing.

What the November Rankings Show

The November results answer several distinct questions. Reach asks how often a company appeared; recommendation asks whether an answer affirmatively endorsed it; placement asks where an endorsement sat in the ordering; framing asks how the wording was classified. Each measure uses its own base, and placements nest inside recommendations.

Reading them together shows that volume, endorsement and ordering do not move in lockstep: some companies appear often but are rarely shortlisted, while others with modest reach are frequently placed highly. Framing adds context about wording, not proof of quality or cause.

Methodology

Questions This Section Answers

• How were the November 2026 Meal Delivery Services 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 from several AI services, and the exact collection dates are unverified. Each company is counted at most once per qualifying answer, and one answer can cover several companies, so company totals should not be summed.

Recommendation requires both affirmative endorsement and positive wording. Rates use the full answer total, and placements are subsets of recommendations. Net framing describes wording only, not customer satisfaction, and the monthly samples differ, so comparisons show change without explaining it.