Ionna Appears in 22.6% 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

  • Ionna appears in 71 of 314 benchmark answers, but is recommended in only 26, showing a gap between mention share and endorsement share.
  • Most mentions are positive, yet Ionna is rarely placed in the top three or ranked first, so visibility does not translate into selection.
  • The homepage is the most cited owned page and the only one linked to recommending answers, making it the main page to review first.
  • Buyer questions cluster around reliability and charging speed, which makes those themes the strongest basis for new or revised content briefs.

Answer Capsule

In November 2026, Ionna appeared in 71 of 314 AI answers included in the EV Charging Networks benchmark (22.61%). It received 26 recommendations (8.28%), with 10 Top 3 placements and 2 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 Ionna mentions, recommendations and placements compare with its EV Charging Networks peers?

Ionna recorded 71 mentions (22.61%) and 26 recommendations (8.28%) across 314 answers included in the benchmark. Top 3 placements numbered 10; first-place recommendations numbered 2. Framing among its mentions was 48 positive, 23 neutral and 0 negative.

Rank

Company

Mentions

Mention rate

Recommendations

Recommendation rate

Top 3

Top 3 rate

#1

#1 rate

1

Tesla Wall Connector (Tesla, Inc.)

298

94.90%

131

41.72%

128

40.76%

89

28.34%

2

ChargePoint Home (ChargePoint Holdings)

270

85.99%

130

41.40%

117

37.26%

36

11.46%

3

EVgo

184

58.60%

41

13.06%

25

7.96%

0

0.00%

4

Electrify America

181

57.64%

37

11.78%

24

7.64%

0

0.00%

5

Ionna

71

22.61%

26

8.28%

10

3.18%

2

0.64%

6

Blink Charging

73

23.25%

17

5.41%

2

0.64%

0

0.00%

7

EV Connect

24

7.64%

8

2.55%

0

0.00%

0

0.00%

8

FLO

16

5.10%

5

1.59%

1

0.32%

1

0.32%

9

Shell Recharge

26

8.28%

2

0.64%

0

0.00%

0

0.00%

10

Francis Energy

3

0.96%

1

0.32%

0

0.00%

0

0.00%

Ionna appears in roughly one in five answers and is recommended in a smaller share, so its reach is broader than its endorsement. Most mentions carry positive wording, which suggests the network is described favourably even when it is not put forward as a choice. That gap between being talked about and being chosen is the practical issue.

Placement is thinner still. Only a small number of answers put Ionna at the front of a shortlist, and fewer name it first. Reach, recommendation and position should be read as separate signals: the brand is known to the answers, but rarely the answer. The agency would build a scorecard that tracks these three measures separately so progress in one is not mistaken for progress in another.

What changed since last month

Questions This Section Answers

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

Metric

Jul 2026

Sep 2026

Oct 2026

Nov 2026

Mentions

41 / 515 (7.96%)

51 / 521 (9.79%)

52 / 509 (10.22%)

71 / 314 (22.61%)

Recommendations

6 / 515 (1.17%)

8 / 521 (1.54%)

15 / 509 (2.95%)

26 / 314 (8.28%)

Top 3 recommendations

2 / 515 (0.39%)

3 / 521 (0.58%)

4 / 509 (0.79%)

10 / 314 (3.18%)

#1 recommendations

0 / 515 (0.00%)

1 / 521 (0.19%)

0 / 509 (0.00%)

2 / 314 (0.64%)

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

From October 2026 to November 2026, Ionna's mention count rose from 52 to 71, while its recommendation count rose from 15 to 26. The recommendation rate was 2.95% and 8.28% respectively.

The November sample shows higher mention and recommendation counts than October, and the recommendation rate moved up alongside them. The two months drew on different answer sets, so the movement describes what was recorded rather than a like-for-like change. It does not establish why the counts or rates moved.

The earlier months show a gradual upward drift in mentions and recommendations, with first-place appearances rare throughout. Read as separate samples, the series suggests growing presence rather than a settled trend. The agency would keep the monthly scorecard in place and treat each month as its own reading until enough comparable periods accumulate to describe direction with confidence.

AI recommendation trend

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

0%2.5%5%7.5%10%Jul 2026Sep 2026Oct 2026Nov 20261.17%Jul 2026: 1.17%1.54%Sep 2026: 1.54%2.95%Oct 2026: 2.95%8.28%Nov 2026: 8.28%
  • Ionna8.28%

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 Ionna?

AI answers contained 0 conflicting claims about Ionna: 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 Ionna were recorded in the captured answers, so there is nothing yet that demands urgent correction. That is a clean starting position, not proof that every description of the company is accurate. The absence of disputes means fact-checking can be planned rather than reactive.

The agency would pair the visibility comparison with a scoped list of claims worth verifying, each with an owner and an evidence requirement. This lets the client see where the answers describe the network well and where a claim needs a primary source before anyone acts on it.

Step 2. Make the website consistent

Questions This Section Answers

  • Which recorded claim differences about Ionna 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 work through for Ionna at present. The agency would still prepare conditional page briefs that can be activated if a conflict appears, each tied to a named source and a verification step before any change is proposed.

Where a future conflict involves dates or entity names, the first task is to resolve which company and which period the claim refers to. Apparent disagreements often dissolve once that is settled. No correction would be requested until a current primary source confirms the position.

Step 3. Align the external narrative

Questions This Section Answers

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

Cited page selected for review

Citation appearances in all captured answers

Answers mentioning the company

Conflicting claims linked to this page

https://cnet.com/home/electric-vehicles/ionna-ev-fast-charging-2026-growth-ceo-interview/

4

4

0

https://ievchina.com/insights/ev-fast-charging-network-tier-list-2026-tesla-supercharger-nacs-ea-ionna/

2

2

0

https://e-charge.show/us-fast-charging-network-surpasses-80000-ports-in-q3-2026-as-tesla-leads-and-ionna-climbs-to-second-place/

1

1

0

https://finance.yahoo.com/energy/articles/ionna-ranked-1-jd-power-130000067.html

1

1

0

https://gmauthority.com/blog/2026/08/ionna-dominates-j-d-power-2026-u-s-ev-experience-public-charging-study/

1

1

0

https://thechargeport.com/ev-charging-networks

24

16

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 cluster around a few themes: a chief executive interview, a network ranking piece, a study result and a general charging-network directory. None of them is linked to a recorded conflicting claim, so the task is review rather than repair. A citation shows a page was referenced, not that it shaped the answer.

The agency would check the current contents of each page before proposing anything, then decide separately whether a request to a publisher is justified, unnecessary or simply unanswered. Requests would rest on verified evidence and would be logged with their responses so the client can see what was asked and what came back.

Step 4. Optimize priority company pages

Questions This Section Answers

  • Which observed Ionna 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://ionna.com/

19

16

11

https://ionna.com/news/ionna-ranked-1-in-jd-power-study-as-network-more-than-doubles-size-during-2026/

2

0

0

https://ionna.com/ev-charging-stations/ga/forest-park/5043-frontage-rd-30297/

1

0

0

https://ionna.com/faqs/

1

0

0

https://ionna.com/news/ionna-begins-operations-in-north-america/

1

0

0

https://ionna.com/partner-brand/toyota/

1

0

0

https://ionna.com/support/

1

0

0

The company's website was cited 26 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 homepage accounts for most citations of the owned site, and it is the only page that appears alongside recommending answers. The news, station, FAQ, partner and support pages were cited far less and not in recommending answers. That makes the homepage the natural first focus for page work.

The agency would draft a brief for the homepage built on approved facts and the questions buyers actually ask, then check whether the existing page already covers them before proposing additions. Secondary pages would get lighter briefs, prioritised by whether they answer a question the answers keep raising.

Step 5. Publish around buyer questions

Questions This Section Answers

  • Which observed buyer questions support content briefs for Ionna?

Question observed in the research

Benchmark answers to this question

Company mentions

Company recommendations

What are the best EV charging stations?

3

2

2

What are the best charging stations for electric vehicles?

2

2

2

What are the most reliable EV charging stations?

2

2

2

What is the most reliable EV charging station?

4

2

2

Which DC fast charger is best?

3

2

2

What is the fastest charging EV station?

2

2

1

Which charging stations charge the fastest?

3

2

1

electric vehicle charging companies

2

2

1

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

The recorded questions centre on reliability, speed and which networks are best, and Ionna is mentioned in most of them. Recommendations follow in nearly all cases, though the fastest-charging questions produced slightly fewer. These are answer observations, not search demand, so they indicate where the conversation sits rather than how many people are asking.

The agency would turn these into buyer-question content briefs, checking existing coverage first so new pages are not created where a current page already answers the question. Reliability and charging speed stand out as the themes worth addressing with approved, verifiable detail.

Our 90-day action plan

Questions This Section Answers

  • How should the agency sequence the proposed Ionna 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. This groundwork matters because later requests and briefs depend on knowing what has been verified and what has not.

The second month produces approved page briefs and any 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 would be reported apart from measured answer outcomes, since delivering a brief does not guarantee a change in visibility.

Methodology

Questions This Section Answers

  • How are Ionna 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 314 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 5034 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

Jul 2026

515

6

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

Sep 2026

521

6

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

Oct 2026

509

6

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

Nov 2026

314

6

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

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 answers were collected on dates that have not been verified, and the monthly samples differ in size and composition. Comparisons across months show how recorded results moved, not why. A company counts as recommended only when an answer endorses it with positive wording, and placement counts sit inside recommendations rather than adding to them.

Answers can mention several companies, so counts cannot be summed to find distinct answers. Sentiment describes answer wording, not customer experience. Cited pages and any disputed claims still need independent checking before action.

Our first three priorities

The first priority is to keep the monthly scorecard running and read each month as its own sample, so the gap between mentions and recommendations stays visible without being over-interpreted. The second is to brief the homepage around approved facts and the reliability and speed questions the answers keep raising, checking current coverage before proposing changes.

The third is to review the selected external pages for accuracy and decide, page by page, whether a publisher request is warranted. None of these steps guarantees a visibility gain; they give the client verified ground to work from and a clear record of what was done.

/ 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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