Imperfect Foods Appears in 9.1% of AI Answers. Here's Our Five-Step Plan to Improve Its AI Visibility.

Mark HuntleyBy Mark HuntleyFounder and CEO
10 minutes read

Key Takeaways

  • Imperfect Foods was mentioned in 9.07% of benchmark answers and recommended in 5.06%, with most mentions carrying positive wording.
  • The main issue is limited reach, not negative sentiment; the company is rarely placed in top positions even when it is recommended.
  • The first actions are to establish a baseline, verify any claims against primary sources, and review the homepage and help pages that appear in answers.
  • Content opportunities cluster around buyer questions on price, produce boxes, and local grocery delivery, supported by verified facts rather than promotional claims.

Answer Capsule

In November 2026, Imperfect Foods appeared in 43 of 474 AI answers included in the Grocery Delivery Services benchmark (9.07%). It received 24 recommendations (5.06%), with 6 Top 3 placements and 1 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 Imperfect Foods mentions, recommendations and placements compare with its Grocery Delivery Services peers?

Imperfect Foods recorded 43 mentions (9.07%) and 24 recommendations (5.06%) across 474 answers included in the benchmark. Top 3 placements numbered 6; first-place recommendations numbered 1. Framing among its mentions was 24 positive, 19 neutral and 0 negative.

Rank

Company

Mentions

Mention rate

Recommendations

Recommendation rate

Top 3

Top 3 rate

#1

#1 rate

1

Amazon

465

98.10%

400

84.39%

341

71.94%

50

10.55%

1

Walmart

456

96.20%

400

84.39%

353

74.47%

166

35.02%

3

Instacart

474

100.00%

390

82.28%

364

76.79%

175

36.92%

4

Shipt

323

68.14%

241

50.84%

71

14.98%

1

0.21%

5

Thrive Market

215

45.36%

205

43.25%

16

3.38%

4

0.84%

6

Misfits Market

176

37.13%

168

35.44%

20

4.22%

2

0.42%

7

Gopuff

137

28.90%

112

23.63%

18

3.80%

5

1.05%

8

FreshDirect

115

24.26%

101

21.31%

13

2.74%

4

0.84%

9

Kroger Delivery

159

33.54%

56

11.81%

26

5.49%

2

0.42%

10

Imperfect Foods

43

9.07%

24

5.06%

6

1.27%

1

0.21%

Imperfect Foods appears in a small share of the answers measured, yet most of those appearances carry an endorsement. That gap between being mentioned and being recommended is the useful signal: when the company surfaces, the answer tends to speak well of it. The constraint is reach, not tone.

Placement is a separate matter. Being named near the top of an answer is rare, and a first-place position rarer still. Those positions sit inside the recommendation counts rather than adding to them, so the practical reading is that Imperfect Foods is endorsed occasionally and ranked highly almost never.

For the agency, this points to widening where the company is discussed rather than repairing its reputation. Proposed work would focus on the questions and sources where competitors are named and Imperfect Foods is absent.

What changed since last month

Questions This Section Answers

  • How did Imperfect Foods counts and coverage differ across the available monthly snapshots?

Metric

Nov 2026

Mentions

43 / 474 (9.07%)

Recommendations

24 / 474 (5.06%)

Top 3 recommendations

6 / 474 (1.27%)

#1 recommendations

1 / 474 (0.21%)

Only months with verified results are shown. Monthly sample coverage is listed in Methodology.

There are insufficient usable monthly observations for a prior-period comparison.

Only one month of verified results is available, so there is no prior period to compare against. The current figures stand as a baseline rather than a trend, and any movement described later will be measured against this starting point.

Because the monthly samples are drawn separately, a future change in totals would not by itself show why counts or rates moved. The agency would treat each month as its own sample and describe what was recorded before drawing conclusions.

Proposed work begins with locking this baseline into a scorecard so later months can be read against a fixed reference.

AI recommendation trend

Observed recommendation rate (%), Nov 2026

  • Imperfect Foodsno change
    Nov 20265.06%

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 Imperfect Foods?

AI answers contained 0 conflicting claims about Imperfect Foods: 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 Imperfect Foods were recorded in the captured answers, so there is nothing in the fact-check queue at critical or high priority. That is a clean starting position, though it reflects the answers sampled rather than a guarantee that every statement elsewhere is accurate.

A visibility comparison would show where the company is named alongside competitors and where it is missing entirely. Pairing that with a short list of claims worth verifying gives the client a clear order of work rather than a broad mandate.

The agency would build a baseline scorecard and a scoped fact-review register, with each entry assigned an owner and an evidence requirement.

Step 2. Make the website consistent

Questions This Section Answers

  • Which recorded claim differences about Imperfect Foods 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.

No results are available for this part of the analysis, so there are no disputed topics to work through yet. The agency would not treat that absence as a finding about the website; it simply means this check has not produced material to act on.

Where claims do surface later, the first step is to confirm the entity, the date and the source behind each one. Different dates can make two statements look contradictory when they are not, and a company name can match more than one business.

Proposed page briefs would be drafted only after that verification, and only where a current primary source supports the wording. Ambiguous matches would stay out of the correction queue.

Step 3. Align the external narrative

Questions This Section Answers

  • Which cited third-party pages are relevant to fact review for Imperfect Foods?

Cited page selected for review

Citation appearances in all captured answers

Answers mentioning the company

Conflicting claims linked to this page

https://foodspark.io/grocery-delivery-apps-in-usa/

6

1

0

https://wholefoodsmarket.com/amazon

1

1

0

https://cnet.com/home/kitchen-and-household/best-grocery-delivery-service/

242

20

0

https://thekitchn.com/online-grocery-shopping-22945794

100

7

0

https://nbcnews.com/select/shopping/best-grocery-delivery-services-ncna1297967

36

7

0

https://healthline.com/nutrition/best-grocery-delivery

73

6

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 vary widely in how often they appear and how often they mention the company. A page can be cited many times without naming Imperfect Foods at all, which makes it a candidate for review rather than a proven gap.

Citation does not establish that a source shaped an answer, and a page linked to a disputed claim is not necessarily its cause. The agency would check each page's current contents before proposing any change.

Proposed work is a prioritized source review, followed by evidence-backed requests to publishers where a genuine omission or error is confirmed. Requests would be framed as information, not demands.

Step 4. Optimize priority company pages

Questions This Section Answers

  • Which observed Imperfect Foods 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://help.imperfectfoods.com/en_us/do-you-accept-snap-benefits-or-ebt-as-payment-Sy77pyZuj

3

0

0

https://imperfectfoods.com/

3

3

1

https://help.imperfectfoods.com/en_us/what-payment-methods-do-you-accept-BJjX6y_o

2

0

0

https://imperfectfoods.com/misfits-market

2

0

0

https://blog.imperfectfoods.com/giving-back-through-our-reduced-cost-box/

1

0

0

https://help.imperfectfoods.com/en_us/are-there-any-order-fees-B10Q6JW_o

1

0

0

https://imperfectfoods.com/terms-and-conditions

1

0

0

The company's website was cited 13 times across 7 distinct page addresses; the table shows 7 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.

The company's own pages were cited across a handful of addresses, with the homepage carrying most of the recommending answers. Help-centre pages on payment methods and order fees drew citations but no recorded recommendations, which suggests they answer practical questions rather than influence a choice.

A cited page is not automatically one that accompanied a recommendation, so these patterns guide review rather than prove effect. The agency would check what each page currently says before proposing edits.

Proposed page briefs would use approved facts and the questions buyers actually ask, applied to the listed pages in priority order.

Step 5. Publish around buyer questions

Questions This Section Answers

  • Which observed buyer questions support content briefs for Imperfect Foods?

Question observed in the research

Benchmark answers to this question

Company mentions

Company recommendations

Which online grocery store is the best?

5

2

1

Is there a fruit delivery service?

1

1

1

What is the best grocery delivery in NYC?

3

1

1

What is the best vegetable delivery service?

1

1

1

What is the cheapest grocery store that delivers?

2

1

1

What is the cheapest way to have groceries delivered?

1

1

1

Where can I order healthy snacks online?

1

1

1

Where is the cheapest place to get groceries delivered?

4

1

1

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

The recorded questions cluster around cost, health and local availability: cheapest delivery, vegetable and fruit boxes, healthy snacks, and service in a specific city. Imperfect Foods was mentioned in answers to most of these, and recommended in nearly all of those mentions.

These are answer observations, not search volume or proof that the website lacks coverage. The agency would check existing pages first, then draft briefs only where a genuine gap remains.

Proposed buyer-question content would address cost comparisons and produce-box questions directly, using verified facts rather than promotional claims.

Our 90-day action plan

Questions This Section Answers

  • How should the agency sequence the proposed Imperfect Foods 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 establishes the baseline scorecard, a scoped fact-review register and a shortlist of pages and sources, each with an owner and a review status. Nothing is corrected in this phase; the aim is a clean, evidenced starting position.

The second month produces approved page briefs and justified publisher requests, with confirmed edits, no-change decisions, requests and responses recorded separately. The third month adds buyer-content briefs and a fresh scorecard.

Delivered work would be reported apart from measured answer outcomes. Completing a brief or sending a request does not establish that visibility changed, and later comparisons would carry their own limits.

Methodology

Questions This Section Answers

  • How are Imperfect Foods 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 474 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 4817 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

Nov 2026

474

6

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

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

The visibility figures rest on answers that met the benchmark's inclusion rules, and the 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 positions sit inside those recommendations rather than adding to them.

Answers can name several companies, so company counts cannot be summed to find distinct answers. Sentiment describes answer wording, not customer satisfaction. Cited pages and any disputed claims still need independent checking, and the monthly samples differ, so comparisons show what was recorded, not why.

Our first three priorities

The first priority is to fix the baseline and confirm that the company's own pages say what the briefs will assume. The homepage carries most of the recommending citations, so it deserves the earliest review, alongside the help pages on payment and fees that draw citations without endorsements.

The second is a focused source review of the pages that discuss grocery delivery without naming Imperfect Foods, checking current contents before any request goes out. The third is buyer-question content on cost and produce boxes, drafted only after existing coverage is checked.

Each step produces verified material for the client to approve, and none of it promises a visibility gain on its own.

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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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