Optum Appears in 7.8% of AI Answers. Here's Our Five-Step Plan to Improve Its AI Visibility.

Mark HuntleyBy Mark HuntleyFounder and CEO
9 minutes read

Key Takeaways

  • Optum appeared in 22 of 281 benchmark answers in November 2026, with 17 recommendations and 14 Top 3 placements.
  • Its presence is limited compared with larger peers, but the answers that mention Optum tend to frame it positively.
  • The analysis found no conflicting claims tied to Optum in the captured answers, so the first priority is measuring where it is absent.
  • The recommended work focuses on verified website pages, relevant third-party sources, and buyer questions about cheaper prescriptions and online pharmacy services.

Answer Capsule

In November 2026, Optum appeared in 22 of 281 AI answers included in the ED Treatment Pills benchmark (7.83%). It received 17 recommendations (6.05%), with 14 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 Optum mentions, recommendations and placements compare with its ED Treatment Pills peers?

Optum recorded 22 mentions (7.83%) and 17 recommendations (6.05%) across 281 answers included in the benchmark. Top 3 placements numbered 14; first-place recommendations numbered 7. Framing among its mentions was 17 positive, 5 neutral and 0 negative.

Rank

Company

Mentions

Mention rate

Recommendations

Recommendation rate

Top 3

Top 3 rate

#1

#1 rate

1

Hims

252

89.68%

189

67.26%

144

51.25%

75

26.69%

2

Ro

237

84.34%

179

63.70%

131

46.62%

20

7.12%

3

GoodRx Care

214

76.16%

168

59.79%

122

43.42%

62

22.06%

4

plushcare

111

39.50%

92

32.74%

40

14.23%

6

2.14%

5

Lemonaid Health

98

34.88%

79

28.11%

28

9.96%

1

0.36%

6

BlueChew

68

24.20%

33

11.74%

16

5.69%

2

0.71%

6

Rex MD

51

18.15%

33

11.74%

17

6.05%

1

0.36%

8

Blink Health

20

7.12%

20

7.12%

12

4.27%

5

1.78%

9

Optum

22

7.83%

17

6.05%

14

4.98%

7

2.49%

10

K Health

17

6.05%

15

5.34%

5

1.78%

1

0.36%

Optum appears in a small share of benchmark answers, yet when it does appear it is often placed near the top and framed positively. That combination suggests the brand is not broadly present in these conversations but is treated favorably where it surfaces. The practical question is whether that narrow presence reflects limited coverage of the topics buyers ask about.

A useful first step is a visibility scorecard that separates mentions, recommendations and placements so the client can see where Optum is absent rather than only where it appears. Because the benchmark includes several larger competitors, the scorecard should also show which question types Optum never enters, since that is where content work could plausibly matter.

What changed since last month

Questions This Section Answers

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

Metric

Oct 2026

Nov 2026

Mentions

13 / 296 (4.39%)

22 / 281 (7.83%)

Recommendations

2 / 296 (0.68%)

17 / 281 (6.05%)

Top 3 recommendations

1 / 296 (0.34%)

14 / 281 (4.98%)

#1 recommendations

0 / 296 (0.00%)

7 / 281 (2.49%)

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

From October 2026 to November 2026, Optum's mention count rose from 13 to 22, while its recommendation count rose from 2 to 17. The recommendation rate was 0.68% and 6.05% respectively.

The recorded results moved upward between the two selected months, with more mentions and more recommendations in the later sample. The samples are separate and differ in size, so the movement describes what was recorded rather than establishing why it happened. Treat the two months as snapshots, not a trend line.

The agency would document the movement as observed and keep the comparability limit beside it. A short history note in the scorecard can flag that the answer samples differ, so the client reads the change as a recorded shift rather than evidence that any action worked.

AI recommendation trend

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

  • Optum+5.37 pp
    Oct 20260.68%
    Nov 20266.05%

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 Optum?

AI answers contained 0 conflicting claims about Optum: 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 Optum were recorded in the captured answers, so there is no immediate fact-check queue tied to the brand. That is a clean starting position, but it also means the measurement work should focus on where Optum is absent and which questions it fails to enter.

The agency would build a baseline scorecard covering mentions, recommendations and placements by question type, plus a scoped fact-review register that stays empty unless a claim is later identified. Each record would carry an owner and a review status so the client can see what was checked and what remains open.

Step 2. Make the website consistent

Questions This Section Answers

  • Which recorded claim differences about Optum 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 disputed topics were supplied for this part of the analysis, so there is nothing to correct on the website at this stage. The agency would not invent a correction; instead it would confirm which Optum pages are current and accurate before any brief is written.

Where a page is proposed for revision, the brief would rest on verified primary-source facts, with entity, date and source resolved first. Apparent conflicts can come from different dates or different product lines, so the review would separate confirmed edits from no-change decisions and record both.

Step 3. Align the external narrative

Questions This Section Answers

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

Cited page selected for review

Citation appearances in all captured answers

Answers mentioning the company

Conflicting claims linked to this page

https://optumrx.com/en/

12

11

0

https://doctorondemand.com/online-prescriptions/

18

11

0

https://pharmacy.amazon.com/

18

11

0

https://express-scripts.com/rx

11

11

0

https://clearwayhealth.com/post/these-online-pharmacies-can-make-getting-your-prescription-so-much-easier

19

10

0

https://goodrx.com/healthcare-access/telehealth/get-prescription-online

16

9

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 span pharmacy, telehealth and comparison sources, and none carries a conflicting claim about Optum. Citation does not show that a source influenced an answer, so the review would check current page contents before any request is made. Several of these pages are third-party sites the client does not control.

The agency would prioritize the pages most closely tied to Optum's own services and prepare evidence-backed requests only where a factual gap is confirmed. Requests would be framed as clarifications, with responses logged separately from confirmed edits so the client can see what was asked and what changed.

Step 4. Optimize priority company pages

Questions This Section Answers

  • Which observed Optum 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://perks.optum.com/blog/how-to-get-finasteride

4

0

0

https://perks.optum.com/blog/how-much-is-wegovy-without-insurance

2

0

0

https://optum.com/en/pharmacy-services.html

1

1

1

https://perks.optum.com/blog/cialis-over-the-counter

1

1

0

https://perks.optum.com/blog/how-to-get-cialis

1

0

0

https://perks.optum.com/blog/how-to-get-viagra

1

0

0

https://perks.optum.com/blog/valtrex-without-seeing-a-doctor

1

0

0

https://perks.optum.com/drug/zepbound

1

0

0

The company's website was cited 13 times across 9 distinct page addresses; the table shows 8 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.

Optum's own pages were cited across a small set of addresses, and most of those citations did not accompany a recommendation. That gap is worth examining: a page can be referenced without the answer endorsing the company, so citation counts alone do not show persuasive value.

The agency would prepare page briefs for the listed addresses using approved facts and the questions buyers actually ask. Each brief would note whether the page currently answers the question, and existing coverage would be checked before proposing new content. Briefs are proposed work, not measured outcomes.

Step 5. Publish around buyer questions

Questions This Section Answers

  • Which observed buyer questions support content briefs for Optum?

Question observed in the research

Benchmark answers to this question

Company mentions

Company recommendations

What is the app that gives you cheaper prescriptions?

1

1

1

What is the best online pharmacy to use?

1

1

1

What is the best online prescription service?

3

1

1

What is the website to get prescriptions cheaper?

1

1

1

Which mail order pharmacy is the best?

1

1

1

buy prescription drugs online

1

1

1

buy prescription pills online

1

1

1

online prescription

1

1

1

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

The recorded questions cluster around cheaper prescriptions, best online pharmacy and best online prescription service, and Optum was mentioned and recommended in each of the observed answers. The sample per question is thin, so these are observations to brief against rather than proof of demand or of missing content.

The agency would draft buyer-question content around cost, service comparison and mail-order choice, checking existing Optum pages first. Where coverage already exists, the brief would propose tightening rather than adding a page, keeping the work tied to the questions actually recorded.

Our 90-day action plan

Questions This Section Answers

  • How should the agency sequence the proposed Optum 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 would deliver a baseline scorecard, a scoped fact-review register and a page and source shortlist, each with an owner and review status. The second month would produce approved page briefs and justified publisher requests, with confirmed edits, no-change decisions and responses recorded separately.

The final month would deliver buyer-content briefs and a fresh scorecard. Completed work would be reported apart from measured answer outcomes, and the comparability limits between monthly samples would stay visible so no one reads the plan as a promise of visibility gains.

Methodology

Questions This Section Answers

  • How are Optum 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 281 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 5650 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

Oct 2026

296

6

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

Nov 2026

281

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.

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

The benchmark covers one reporting month and a defined set of answers that met inclusion rules. The exact collection dates for the original answers are unverified, and the monthly samples differ, so comparisons show recorded change rather than cause. A company counts as recommended only when an answer endorses it with positive wording.

Answers can mention several companies, so company counts do not sum to distinct answers. Citation appearances across all captured answers are a wider measure than benchmark answers citing a page, and cited page contents still need independent checking.

Our first three priorities

First, confirm which Optum pages and third-party sources are current before any brief or request is drafted, since citation alone does not show influence or accuracy. Second, build page briefs for the listed Optum addresses around the recorded buyer questions, checking existing coverage first. Third, prepare buyer-question content on cost and service comparison, with approved facts and a clear review owner.

These priorities are proposed work. They would be tracked through the scorecard and review register, with completed deliverables reported separately from any later change in measured visibility.

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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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