NMI Appears in 5.8% 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

  • NMI is mentioned in 5.75% of benchmark answers, but it has no Top 3 or first-place placements in the November sample.
  • Mentions increased in November, while recommendations fell, showing that visibility and endorsement are moving in different directions.
  • The main fact issue is a conflicting claim about how many processors NMI supports, which needs primary-source verification before any page changes.
  • Priority work focuses on the homepage, gateway and ecommerce pages, plus buyer questions about embedded payments, recurring billing and pricing.

Answer Capsule

In November 2026, NMI appeared in 23 of 400 AI answers included in the Credit Card Processing Companies benchmark (5.75%). It received 4 recommendations (1.00%), with 0 Top 3 placements and 0 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 NMI mentions, recommendations and placements compare with its Credit Card Processing Companies peers?

NMI recorded 23 mentions (5.75%) and 4 recommendations (1.00%) across 400 answers included in the benchmark. Top 3 placements numbered 0; first-place recommendations numbered 0. Framing among its mentions was 5 positive, 18 neutral and 0 negative.

Rank

Company

Mentions

Mention rate

Recommendations

Recommendation rate

Top 3

Top 3 rate

#1

#1 rate

1

Adyen

345

86.25%

156

39.00%

42

10.50%

20

5.00%

2

Braintree

263

65.75%

96

24.00%

29

7.25%

7

1.75%

3

Authorize.Net

200

50.00%

79

19.75%

11

2.75%

3

0.75%

4

Checkout.com

278

69.50%

41

10.25%

10

2.50%

6

1.50%

5

Stax Payments

33

8.25%

13

3.25%

3

0.75%

0

0.00%

6

Payoneer

33

8.25%

11

2.75%

1

0.25%

0

0.00%

7

Payment Depot

29

7.25%

10

2.50%

3

0.75%

1

0.25%

8

Elavon

32

8.00%

6

1.50%

0

0.00%

0

0.00%

8

Nuvei

13

3.25%

6

1.50%

1

0.25%

1

0.25%

10

NMI

23

5.75%

4

1.00%

0

0.00%

0

0.00%

11

WePay

8

2.00%

3

0.75%

0

0.00%

0

0.00%

12

Dharma Merchant Services

6

1.50%

1

0.25%

0

0.00%

0

0.00%

12

Merchant One

3

0.75%

1

0.25%

0

0.00%

0

0.00%

12

Payline Data

2

0.50%

1

0.25%

0

0.00%

0

0.00%

12

Payroc

4

1.00%

1

0.25%

0

0.00%

0

0.00%

16

BluePay

2

0.50%

0

0.00%

0

0.00%

0

0.00%

16

CDGcommerce

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Clearent

1

0.25%

0

0.00%

0

0.00%

0

0.00%

16

EMS Electronic Merchant Systems

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Flagship Merchant Services

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Gravity Payments

1

0.25%

0

0.00%

0

0.00%

0

0.00%

16

Heartland Payment Systems

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Host Merchant Services

4

1.00%

0

0.00%

0

0.00%

0

0.00%

16

Lightspeed

8

2.00%

0

0.00%

0

0.00%

0

0.00%

16

Melio Payments

1

0.25%

0

0.00%

0

0.00%

0

0.00%

16

Olo

1

0.25%

0

0.00%

0

0.00%

0

0.00%

16

PaySimple

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Payanywhere

1

0.25%

0

0.00%

0

0.00%

0

0.00%

16

Paytrace

3

0.75%

0

0.00%

0

0.00%

0

0.00%

16

Pineapple Payments

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Priority

19

4.75%

0

0.00%

0

0.00%

0

0.00%

16

ProPay

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Revel Systems

1

0.25%

0

0.00%

0

0.00%

0

0.00%

16

Sekure Merchant Solutions

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Shift4 Payments

7

1.75%

0

0.00%

0

0.00%

0

0.00%

16

SpotOn

1

0.25%

0

0.00%

0

0.00%

0

0.00%

16

USAePay

3

0.75%

0

0.00%

0

0.00%

0

0.00%

NMI appears in a modest share of answers, and the gap between being mentioned and being recommended is the central issue. Mentions are frequent enough to show the name circulates in payment-gateway discussions, but affirmative endorsements are rare. Positive framing is present, yet framing alone does not amount to a recommendation.

Placement is the sharper constraint. NMI holds no shortlist or first-place positions in this sample, so its reach is broad but shallow. For a gateway competing against larger processors, that pattern suggests the brand is known but not chosen. The agency would build a scorecard separating mentions, recommendations and placement so the client can see which measure to move first.

What changed since last month

Questions This Section Answers

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

Metric

Sep 2026

Oct 2026

Nov 2026

Mentions

15 / 417 (3.60%)

14 / 389 (3.60%)

23 / 400 (5.75%)

Recommendations

6 / 417 (1.44%)

8 / 389 (2.06%)

4 / 400 (1.00%)

Top 3 recommendations

2 / 417 (0.48%)

2 / 389 (0.51%)

0 / 400 (0.00%)

#1 recommendations

1 / 417 (0.24%)

1 / 389 (0.26%)

0 / 400 (0.00%)

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

From October 2026 to November 2026, NMI's mention count rose from 14 to 23, while its recommendation count fell from 8 to 4. The recommendation rate was 2.06% and 1.00% respectively.

The monthly record shows mentions rising while recommendations fell, and shortlist and first-place positions dropped to zero. These are separate selected samples, so the movement should be read as an observed change rather than a trend with a known cause. The answer sets differ between months, which limits direct comparison.

The practical reading is that visibility and endorsement moved in opposite directions. That makes the recommendation gap the more urgent question, not the mention count. The agency would track both measures side by side in the next scorecard and avoid treating a single month as a verdict.

AI recommendation trend

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

0%0.75%1.5%2.25%3%Sep 2026Oct 2026Nov 20261.44%Sep 2026: 1.44%2.06%Oct 2026: 2.06%1.00%Nov 2026: 1.00%
  • NMI1.00%

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 NMI?

AI answers contained 1 conflicting claim about NMI: 0 critical, 0 high, 0 medium, 1 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.

A visibility comparison would place NMI against the processors that dominate recommendations, showing where the gap is widest and which questions produce endorsements for rivals. That gives the client a priority order rather than a general impression.

A fact-check list would then capture the one low-severity conflicting claim recorded about NMI. The conflict concerns how many processors the platform supports, with two different figures appearing in answers. Neither figure is verified. The agency would log the claim, assign an owner and require primary-source confirmation before any correction is considered.

Step 2. Make the website consistent

Questions This Section Answers

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

Review topic

Severity

Recorded AI claim A

Recorded AI claim B

number of supported processors

low

over 150 processors

200+ processors

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.

The disputed point is a count of supported processors, and the two recorded figures differ. Before any page change, the agency would confirm the current figure from NMI's own documentation, note the date it applies and identify the source. Different publication dates can explain an apparent conflict without either answer being wrong.

If verification supports one figure, a conditional page brief would align the relevant company page and any related product descriptions. If the evidence is inconclusive, the item stays open rather than becoming a correction. The brief would also flag where the figure appears so the client can keep it consistent across pages.

Step 3. Align the external narrative

Questions This Section Answers

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

Cited page selected for review

Citation appearances in all captured answers

Answers mentioning the company

Conflicting claims linked to this page

https://nmigateway.com/nmi-payment-gateway/

2

1

1

https://finance-studio.com/blog/what-is-nmi-payment-gateway-features-security-and-benefits/

1

0

1

https://nmigateway.com/nmi-merchant-services/

1

0

1

https://nmigateway.com/nmi/

1

0

1

https://paymentcloudinc.com/blog/nmi/

1

0

1

https://thrivecart.com/blog/best-payment-gateways/

42

3

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 include NMI's own gateway and merchant-services pages alongside third-party blogs. Citation frequency varies widely, and one comparison blog appears far more often than the company pages. A citation does not establish that a page influenced an answer, and a page linked to a conflicting claim is not necessarily its cause.

The agency would review the current contents of the selected pages before making any request. Where a page is a company-owned property, the client can act directly. Where it is a publisher, the agency would prepare an evidence-backed request and record the response separately from any confirmed edit.

Step 4. Optimize priority company pages

Questions This Section Answers

  • Which observed NMI 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://nmi.com/

3

2

0

https://nmi.com/products/payment-gateway/

3

0

0

https://nmi.com/solutions/ecommerce-payments/

2

1

0

https://nmi.com/blog/the-ultimate-white-label-payment-gateway-introduction-for-merchant-acquirers/

1

0

0

https://nmi.com/blog/what-are-embedded-payments/

1

1

1

https://nmi.com/developers/sdks-apis/

1

0

0

https://nmi.com/eu/resources/payments-101/faq/

1

0

0

https://nmi.com/products/nmi-payments/

1

0

0

The company's website was cited 20 times across 15 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.

The company website was cited across a range of pages, but the selected pages show little connection to recommending answers. Most recorded citations sit on the homepage and gateway product page, while blog and developer pages appear only occasionally. A cited page is not automatically a page that accompanied a recommendation.

Page briefs would use approved facts and the questions buyers actually ask, then map them to the existing pages rather than assuming new pages are needed. The agency would check current coverage first, then propose updates to the gateway and ecommerce pages where the citation record is strongest.

Step 5. Publish around buyer questions

Questions This Section Answers

  • Which observed buyer questions support content briefs for NMI?

Question observed in the research

Benchmark answers to this question

Company mentions

Company recommendations

embedded payments companies

1

1

1

payment gateway for online gaming

2

1

1

payment gateways in usa

2

1

1

recurring payment gateway

1

1

1

What platforms support Checkout Champ?

3

3

0

How much does NMI payment gateway cost?

2

2

0

How much does USAePay cost?

2

1

0

How much does a high-risk merchant account cost?

1

1

0

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

The recorded questions cluster around gateway selection, embedded payments, recurring billing and cost. NMI is mentioned in several of these answers, and in a few it is also recommended, which suggests the brand can surface when the question fits its strengths. Cost questions produced mentions without recommendations.

Content briefs would address these buyer questions directly, using verified pricing and capability facts. Before proposing anything new, the agency would check whether existing pages already answer them. Where coverage exists, the brief would focus on clarity and evidence rather than adding another page.

Our 90-day action plan

Questions This Section Answers

  • How should the agency sequence the proposed NMI 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 record needs an owner, an evidence requirement and a review status so nothing sits unresolved.

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 delivers buyer-content briefs and a fresh scorecard. Completed work is reported apart from measured answer outcomes, and no visibility gain is claimed from the work itself.

Methodology

Questions This Section Answers

  • How are NMI 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 400 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 4711 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

Sep 2026

417

6

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

Oct 2026

389

6

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

Nov 2026

400

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.

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

The report covers a single month, and the exact dates when the original answers were collected are unverified. Rates rest on answers that met the benchmark's inclusion rules. A company counts as recommended only when an answer endorses it with positive wording, and shortlist and first-place positions sit inside those recommendations rather than adding to them.

Answers can mention several companies, so counts cannot be summed into distinct answers. The citation analysis covers a wider set of captured answers than the benchmark, and cited pages still need independent checking. Monthly samples differ, so comparisons show what changed, not why.

Our first three priorities

The first priority is resolving the processor-count conflict through primary-source verification, since it is the only recorded claim and it touches a core product fact. Until that is settled, no correction should be issued.

The second is a focused review of the company gateway and ecommerce pages, using approved facts and the buyer questions already observed. The third is a set of buyer-content briefs on gateway selection, embedded payments and cost, checked against existing coverage first. Together these give the client a defensible base for later visibility work without promising outcomes the evidence cannot support.

/ 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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