Purple Carrot Appears in 51.7% of AI Answers. Here's Our Five-Step Plan to Improve Its AI Visibility.

Mark HuntleyBy Mark HuntleyFounder and CEO
11 minutes read

Key Takeaways

  • Purple Carrot is mentioned in 51.67% of benchmark answers and recommended in 47.42%, but it rarely reaches top-three or first-place placement.
  • The main issue is positioning, not basic visibility: the brand is present in answers but seldom the leading recommendation.
  • No conflicting claims were recorded in the captured answers, so the first step is to verify facts and build a baseline scorecard.
  • The plan focuses on homepage and recipe-page briefs, plus content around meal subscription and vegetarian buyer questions.

Answer Capsule

In November 2026, Purple Carrot appeared in 340 of 658 AI answers included in the Meal Delivery Services benchmark (51.67%). It received 312 recommendations (47.42%), with 27 Top 3 placements and 7 first-place recommendations. A mention means the company appeared in an answer; a recommendation means the answer affirmatively endorsed it.

Our plan compares the company with its competitors, checks conflicting AI claims against reliable sources, and identifies website pages, third-party sources and buyer questions to address. The historical results show how the figures changed across available months. Different monthly samples limit those comparisons, and conflicting AI claims require verification before corrections are proposed.

Current AI visibility

Questions This Section Answers

  • How do Purple Carrot mentions, recommendations and placements compare with its Meal Delivery Services peers?

Purple Carrot recorded 340 mentions (51.67%) and 312 recommendations (47.42%) across 658 answers included in the benchmark. Top 3 placements numbered 27; first-place recommendations numbered 7. Framing among its mentions was 327 positive, 13 neutral and 0 negative.

Rank

Company

Mentions

Mention rate

Recommendations

Recommendation rate

Top 3

Top 3 rate

#1

#1 rate

1

Factor

582

88.45%

526

79.94%

272

41.34%

85

12.92%

2

HelloFresh

579

87.99%

514

78.12%

411

62.46%

198

30.09%

3

CookUnity

553

84.04%

509

77.36%

299

45.44%

123

18.69%

4

Home Chef

507

77.05%

445

67.63%

268

40.73%

34

5.17%

5

EveryPlate

459

69.76%

402

61.09%

109

16.57%

9

1.37%

6

Green Chef

438

66.57%

381

57.90%

71

10.79%

7

1.06%

7

Purple Carrot

340

51.67%

312

47.42%

27

4.10%

7

1.06%

8

Blue Apron

310

47.11%

252

38.30%

144

21.88%

48

7.29%

9

Marley Spoon

281

42.71%

240

36.47%

148

22.49%

87

13.22%

10

Sunbasket

164

24.92%

126

19.15%

20

3.04%

6

0.91%

Purple Carrot is mentioned and recommended in roughly half of the answers in this benchmark, which puts it mid-table among the listed services. The more telling gap is position: it rarely lands in the top three or at number one, so it is present in the conversation without often being the answer a buyer is pointed toward first.

That pattern matters because reach and position do different jobs. Being named keeps the brand in consideration; being recommended with positive wording moves it closer to a choice. Purple Carrot already earns recommendations at a rate close to its mention rate, so the wording is largely working. The shortfall is in how often it surfaces as a leading pick.

We would treat this as a positioning question rather than a visibility emergency. The proposed work is a scorecard that separates mentions, recommendations and placement so the client can see which lever is actually short, and page briefs aimed at the buyer questions where Purple Carrot is named but not placed first.

What changed since last month

Questions This Section Answers

  • How did Purple Carrot counts and coverage differ across the available monthly snapshots?

Metric

Aug 2026

Sep 2026

Oct 2026

Nov 2026

Mentions

481 / 696 (69.11%)

457 / 691 (66.14%)

417 / 677 (61.60%)

340 / 658 (51.67%)

Recommendations

437 / 696 (62.79%)

416 / 691 (60.20%)

390 / 677 (57.61%)

312 / 658 (47.42%)

Top 3 recommendations

38 / 696 (5.46%)

28 / 691 (4.05%)

32 / 677 (4.73%)

27 / 658 (4.10%)

#1 recommendations

16 / 696 (2.30%)

6 / 691 (0.87%)

6 / 677 (0.89%)

7 / 658 (1.06%)

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.

Across the selected monthly samples, Purple Carrot's mentions and recommendations both moved lower from October to November, and the recommendation rate moved with them. Top-three placements held at a similar level, while first-place placements stayed very low throughout the period.

The samples differ between months, so these are separate observations rather than a like-for-like trend line. A different answer total does not establish why counts or rates moved, and we would not read a cause into the movement. What the record does show is a company that is consistently present but seldom leading.

For planning, we would use the monthly record as a baseline to compare against future samples, not as evidence that anything the company did worked or failed. The proposed scorecard would track the same measures month to month so any future movement can be read against a stable starting point.

AI recommendation trend

Observed recommendation rate (%), Aug 2026 to Nov 2026

0%20%40%60%80%Aug 2026Sep 2026Oct 2026Nov 202662.79%Aug 2026: 62.79%60.20%Sep 2026: 60.20%57.61%Oct 2026: 57.61%47.42%Nov 2026: 47.42%
  • Purple Carrot47.42%

Separate selected monthly samples. Missing points are unavailable, not zero. Provider/prompt equivalence is unverified; rate movement does not demonstrate causation.

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Step 1. Measure

Questions This Section Answers

  • What should the agency measure and verify first for Purple Carrot?

AI answers contained 0 conflicting claims about Purple Carrot: 0 critical, 0 high, 0 medium, 0 low. Of these, 0 were rated critical or high priority; the critical claims are included in that total. These ratings help prioritize fact-checking. They do not establish that a company or publisher made an error.

No conflicting claims about Purple Carrot were recorded in the captured answers, so there is no fact-check queue to work through at the outset. That is a clean starting position, but it is also a thin one: absence of conflict is not confirmation that the answers describe the company accurately.

The useful first step is a visibility comparison that sets Purple Carrot's reach and placement against the other listed services, paired with a short list of claims worth verifying from primary sources. Together these tell the client where attention is best spent rather than spreading effort evenly.

We would build that comparison as a scorecard and keep the claim list scoped, with each item assigned an owner and an evidence requirement before any correction is considered.

Step 2. Make the website consistent

Questions This Section Answers

  • Which recorded claim differences about Purple Carrot should be verified before proposed page edits?

No results are available for this part of the analysis.

Both columns quote AI answers, not verified company facts. Resolve the entity, date and source before deciding whether a correction is warranted; different dates can explain an apparent conflict.

This part of the analysis returned no results, so there are no disputed topics to resolve and no page briefs to justify on consistency grounds. We would not manufacture a correction queue where the evidence is silent.

What we can propose is readiness. If conflicting claims appear in a later sample, the first move is to confirm the entity, the date and the source behind each claim, because different dates can explain an apparent conflict without anyone being wrong. Only after that check would a page brief or correction be warranted.

For now, the consistency work is a holding position: a documented process and an owner, ready to act when the evidence arrives.

Step 3. Align the external narrative

Questions This Section Answers

  • Which cited third-party pages are relevant to fact review for Purple Carrot?

Cited page selected for review

Citation appearances in all captured answers

Answers mentioning the company

Conflicting claims linked to this page

https://peanutbutterrunner.com/purple-carrot-review/

2

2

0

https://target.com/p/purple-carrot-vegan-frozen-plant-based-be-39-f-udon-noodle-bowl-10-75oz/-/A-84728629?store=

2

2

0

https://blueapron.com/recipes/standard-meal-kit/balsamic-cherry-glazed-chicken-with-mashed-potatoes-sauteed-carrots?cycle_date=2026-10-12&item_id=019fd2ce-b060-7091-b881-5acaed73b2fe&product_id=019fd2ce-b060-7596-98aa-f2e25817b566&product_servings=2

1

1

0

https://deliveryrank.com/reviews/purple-carrot

1

1

0

https://everydayhealth.com/diet-nutrition/purple-carrot-review/

1

1

0

https://goodhousekeeping.com/food-products/a69062560/purple-carrot-review/

1

1

0

These pages were selected because they relate to the company in the captured answers. Their current contents still need checking before any correction request. A page linked to a conflicting claim is not necessarily its cause, and the same answer may contribute to more than one row.

The cited pages selected for review are a mix of independent reviews, a retailer listing and a recipe page from another service. None of them is linked to a conflicting claim in the captured answers, and citation alone does not show that a page influenced what an answer said.

That shapes the external work. Rather than assuming publisher error or asking for changes, we would review each page's current contents against verified company facts and decide, page by page, whether any request is justified. Some may need nothing.

Where a request is justified, it should be specific and evidence-backed, and the client should expect that publishers control their own pages. The proposed output is a shortlist with a recorded decision for each entry: confirmed edit, no change, request sent, or response received.

Step 4. Optimize priority company pages

Questions This Section Answers

  • Which observed Purple Carrot website pages should receive review briefs?

Company website page

Citation appearances in all captured answers

Benchmark answers citing the page

Recommending answers citing the page

https://purplecarrot.com/

5

5

5

https://purplecarrot.com/privacy

1

0

0

https://purplecarrot.com/recipe/herby-lentils-with-balsamic-roasted-vegetables-romesco

1

1

1

The company's website was cited 7 times across 3 distinct page addresses; the table shows 3 pages selected for review. Zeros in the answer columns mean no matching answers were recorded. A cited page is not automatically a page that accompanied a recommendation.

Purple Carrot's own site was cited across a small number of page addresses, with the homepage accounting for most of those appearances and a recipe page accounting for the rest. The privacy page was cited but did not appear in benchmark answers, which is a reminder that a citation is not the same as a page that accompanied a recommendation.

The opportunity is to make the pages that do get cited carry the facts and framing that support a leading recommendation. We would prepare page briefs built on approved company facts and the questions buyers actually ask, starting with the homepage and the recipe page already in the record.

Before proposing any new page, we would check existing coverage so the work adds something rather than duplicating what is already there.

Step 5. Publish around buyer questions

Questions This Section Answers

  • Which observed buyer questions support content briefs for Purple Carrot?

Question observed in the research

Benchmark answers to this question

Company mentions

Company recommendations

What are the best food subscriptions?

4

4

4

What's the best meal subscription box?

5

4

4

What is the highest rated meal delivery service?

4

4

3

What are some good food subscriptions?

3

3

3

What are the best meals delivered to your home?

5

3

3

What is the best food delivery service for vegetarians?

3

3

3

What is the best home delivery meal service?

3

3

3

What is the best home meal delivery service?

4

3

3

These are recorded answer observations, not search volume, verified demand, or proof of missing website content.

The recorded questions are broad category questions: best food subscriptions, best meal subscription box, highest rated service, and best options for vegetarians and home delivery. Purple Carrot is mentioned in most of these answers and recommended in nearly all of the ones where it appears, but the questions themselves are generic rather than brand-specific.

That suggests content aimed at helping a buyer choose within the category, with vegetarian suitability as a natural angle given the company's positioning. These are recorded answer observations, not search volume or proof that the website is missing anything.

We would turn the questions into content briefs, check existing coverage first, and prioritize the vegetarian and subscription-comparison angles where the brand has a credible story to tell.

Our 90-day action plan

Questions This Section Answers

  • How should the agency sequence the proposed Purple Carrot work and judge completion?

Period

Deliverable

Completion criterion

Days 1–30

Baseline scorecard, scoped fact-review register and page/source shortlist

Each record has an owner, evidence requirement and review status

Days 31–60

Approved page briefs and justified publisher requests

Separate confirmed edits, no-change decisions, requests and responses

Days 61–90

Buyer-content briefs and a fresh scorecard

Record work completed separately from measured answer outcomes and comparability limits

The first month is groundwork: a baseline scorecard, a scoped fact-review register and a page and source shortlist, each record carrying an owner, an evidence requirement and a review status. Nothing gets corrected in this phase.

The second month turns that groundwork into approved page briefs and any publisher requests that survive verification, with confirmed edits, no-change decisions, requests and responses recorded separately so the client can see what was actually done.

The third month adds buyer-question content briefs and a fresh scorecard. We would report completed work separately from measured answer outcomes, and we would not present the plan as a guarantee of improved visibility.

Methodology

Questions This Section Answers

  • How are Purple Carrot answer metrics and citation populations defined?

This report covers 2026-11. The exact dates when the original AI answers were collected have not been verified. The visibility rates use 658 answers that met the benchmark's inclusion rules. A company is recommended only when the answer both endorses it and uses positive wording. Top 3 and first-place counts are part of those recommendations, not extra recommendations.

An answer can mention or recommend several companies, so company counts cannot be added to find the number of distinct answers. The net sentiment score is positive minus negative mentions, divided by all company mentions; it describes answer wording, not customer satisfaction.

The wider citation analysis covers 800 captured answers and 5688 appearances of cited URLs. Citation appearances across all captured answers differ from the number of benchmark answers citing a page and the number that also recommend a company. The current contents of cited pages and disputed company claims still need independent verification.

Monthly sample coverage:

Reporting month

Answers included

AI services covered

Services

Aug 2026

696

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

Sep 2026

691

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

Oct 2026

677

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

Nov 2026

658

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

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

The visibility rates rest on the answers that met the benchmark's inclusion rules, and the exact collection dates for the original answers have not been verified. A company counts as recommended only when an answer endorses it with positive wording; top-three and first-place counts sit inside those recommendations rather than adding to them.

Because one answer can mention several companies, company counts cannot be summed to find a number of distinct answers. The wider citation analysis covers more answers than the benchmark and should not be read as the same measure.

Monthly samples differ, so comparisons show how recorded results changed, not why. Cited pages and any disputed claims still need independent verification.

Our first three priorities

First, establish the baseline scorecard and a scoped fact-review register. The absence of conflicting claims is good news, but it should be confirmed against primary sources before the client treats it as settled, and the register gives that check a home with owners and evidence requirements.

Second, prepare page briefs for the homepage and the recipe page that already appear in citations, using approved facts and buyer questions. This is where a presence in answers can be turned into a stronger case for a leading recommendation, without assuming the current pages are deficient.

Third, build buyer-question content around category choice and vegetarian suitability, checking existing coverage first. Publisher review runs alongside these, with each cited page assessed on its current contents and requests made only where the evidence supports them.

/ Learn More

Understanding AI search visibility.

AI search experiences create answers by pulling information from many places online and summarizing it into a single response.

What Is AI Citation Intelligence?
AI citation intelligence is the process of measuring where AI platforms source their information and how frequently a brand is mentioned or referenced in AI-generated responses. Because LLMs synthesize across multiple sources, the sites and brands that appear repeatedly tend to influence how a topic or company is framed. This practice focuses on identifying which sources shape AI outputs and tracking brand visibility across different AI systems.
What Is Citation Architecture?
Citation architecture describes the set of sources that consistently inform how AI systems talk about a brand, product, or topic. LLMs draw from websites, articles, forums, and public discussion, and the sources they rely on most often become the backbone of their answers. Building strong citation architecture means ensuring that accurate, credible, high authority sources are the ones most likely to shape the way AI tools summarize and recommend a brand.
What Is Generative Engine Optimization?
Generative engine optimization (GEO) is the practice of improving the chances that AI systems use and cite your brand or content when generating answers. While traditional SEO is centered on ranking pages in search results, GEO focuses on how LLMs retrieve, interpret, and combine information when responding to a question. The objective is to strengthen the content and sources AI systems rely on, so your brand is treated as a trusted reference in AI responses.
What Is AI Share of Voice?
AI share of voice tracks how often a brand appears in AI-generated answers compared with competitors in the same category. It reflects visibility across AI platforms such as ChatGPT, Gemini, Claude, and Perplexity. Monitoring AI share of voice helps organizations see whether AI systems consistently include and recommend their brand for key queries or whether competitor brands are showing up more often.

About The Author

Mark Huntley

Mark Huntley

Founder and CEO

Mark Huntley, J.D. is founder of CiteWorks Studio, a strategic advisory focused on visibility, authority, and recommendation presence in AI-shaped search environments. His work centers on embedding-level GEO, vector optimization, and cosine gap engineering — helping brands align their digital presence with the retrieval systems that increasingly shape discovery, interpretation, and choice.

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