CiteWorks Studio

Relay AI Market Strategy Report - Business Checking Accounts

Mark HuntleyBy Mark HuntleyFounder and CEO
9 minutes read

Key Takeaways

  • Relay fell from 20.4% valid recommendation coverage in July 2026 to 0% in September 2026, with no mentions or recommendations across 144 qualified observations.
  • The September benchmark narrowed from 48 tracked brands in July to 10 in September, indicating Relay's drop likely reflects a competitive set change rather than a direct quality decline.
  • Relay had no presence across any tracked platform, including ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, and AI Mode.
  • The main next step is to identify which prompts and competitors replaced Relay's earlier recommendation positions in business checking account queries.

Answer Capsule

Relay recorded the largest valid recommendation coverage decline in the Business Checking Accounts benchmark, falling from 20.4% in July 2026 to no recorded coverage in September 2026, a drop of 20.4 points beyond normal variation. The brand is no longer present in the tracked competitive set for business checking account recommendations, which narrowed from 48 brands in July to 10 in September. The clearest weakness is the complete loss of recommendation-stage visibility, while the clearest opportunity is diagnosing which competitor absorbed the recommendation slots Relay previously held. The benchmark evidence suggests Relay's absence reflects a set change rather than a measured decline in brand quality, but the loss of all prior recommendation coverage warrants investigation.

Who This Report Is For

This report is for product, growth, and brand strategy leaders at digital-first business banking providers tracking how AI systems recommend business checking accounts to small business buyers.

Report Card

Field

Value

Report type

AI Company Market Strategy Report

Target company

Relay

Category / market studied

Business Checking Accounts

Reporting month

September 2026

AI platforms tracked

6 (ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, AI Mode)

Public high-intent clusters

1

AI observations analyzed

144

Competitors tracked

10

Executive Summary

Relay is absent from the September 2026 qualified benchmark set. The brand recorded no mentions, no valid recommendations, and no recommendation placement in any of the 144 qualified observations analyzed across the six tracked AI surface families. This follows a three-month series in which Relay fell from 20.4% valid recommendation coverage in July 2026 to no recorded coverage in September 2026.

The benchmark shows that Relay's decline was the largest in the category. Found, Truist Bank, and Varo Bank moved similarly, each falling from measurable July coverage to no recorded coverage by September. These brands no longer appear in the tracked company list, which narrowed from 48 brands in July to 10 in September. The benchmark explicitly notes that these are set changes, not measured declines in brand quality.

The strongest cluster in the current benchmark is Brand Recommendation, which captured all 144 qualified observations. Relay has no presence in this cluster. The weakest area for Relay is therefore the entire recommendation surface, where the brand holds no visibility at all in AI-generated recommendations for business checking accounts. The strongest platform signal belongs to Chase, which leads with 58.3% valid recommendation coverage and a 23.6% rank-one rate. The clearest platform gap for Relay is total absence across ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, and AI Mode.

What Relay Is Winning

Relay has no measurable wins in the September 2026 benchmark. The brand recorded no presence, no recommendations, and no sentiment exposure in the qualified set. The only positive observation is historical: Relay held 20.4% valid recommendation coverage in July 2026, which placed it ahead of several brands that remained in the September tracked set, including PNC Bank at 18.1%, Axos Bank at 16.7%, Citi at 15.3%, and Capital One Auto Finance at 11.8%.

That July position demonstrates that Relay was capable of earning recommendation credit in direct business checking account choice questions. The benchmark evidence suggests the capability existed, but the September data shows no current recommendation-stage presence to build on.

Where Relay Has the Clearest AI Visibility Gaps

Questions This Section Answers

  • How does Relay's complete absence from the September 2026 benchmark compare with competitors that retained measurable presence?
  • What does Mercury's trajectory suggest about what is possible for a digital-first business checking provider in this benchmark?

Relay's clearest gap is total absence from the September 2026 qualified benchmark. The brand is not mentioned in any of the 144 qualified observations, which means it holds no raw mention presence, no valid recommendation coverage, and no top-three or rank-one placements in AI search visibility. Every tracked competitor in the September set has at least some measurable presence.

The competitive displacement is stark. Chase leads the category at 58.3% valid recommendation coverage, followed by Bank of America at 54.2%, U.S. Bank at 43.8%, and Bluevine at 43.1%. Mercury, which like Relay is a digital-first business banking provider, entered the tracked set in August 2026 and reached 35.4% coverage by September. Mercury's trajectory shows that a fintech-focused business checking provider can earn recommendation credit in this benchmark, which makes Relay's absence more notable.

The benchmark notes that multiple brands fell from measurable July coverage to no recorded coverage because they no longer appear in the tracked company list. Relay's decline is therefore partly a function of the narrowed competitive set. However, the loss of all prior recommendation coverage, including the 20.4% valid recommendation coverage and the rank-one placements the brand held in July, means Relay has no current presence in the AI recommendation layer for business checking accounts.

Biggest Opportunity

Questions This Section Answers

  • What should Relay diagnose first to understand where its July 2026 recommendation coverage went?
  • Which competitors appear to have absorbed the recommendation slots Relay previously held?

Relay's clearest opportunity is to diagnose which prompts previously produced its recommendations and which competitors absorbed those recommendation slots. The July 2026 data shows Relay held 20.4% valid recommendation coverage, which means AI systems were recommending the brand in direct business checking account choice questions. By September, those recommendations had disappeared entirely.

The benchmark cannot identify the specific prompts, competitors, or sources causing this shift. A company-level analysis would need to examine which high-intent prompt clusters Relay was winning in July, which surfaces produced those recommendations, and which brands now occupy the positions Relay previously held. The evidence suggests Relay's path back to recommendation-stage visibility starts with understanding where it lost ground, not with broad awareness building.

Competitive Landscape

Questions This Section Answers

  • Which brands hold the strongest recommendation positions in the September 2026 competitive set?
  • Where does Relay stand across top-3 rate, rank-1 rate, and average recommended rank?

Chase holds dominant recommendation power in the September 2026 benchmark, with Bank of America close behind. Relay is absent from the tracked set entirely, holding no measurable position in any metric.

Brand

Top-3 rate

Rank-1 rate

Avg recommended rank

Sentiment

Chase

35.42%

23.61%

1.93

0.5915

Bank of America

21.53%

2.08%

3.12

0.5693

Bluevine

19.44%

7.64%

2.58

0.9265

U.S. Bank

9.03%

0.00%

4.09

0.5328

Wells Fargo

6.94%

2.78%

4.08

0.4434

Mercury

5.56%

1.39%

4.00

0.9630

Capital One Auto Finance

4.17%

2.08%

3.64

0.5333

Citi

3.47%

1.39%

4.57

0.3548

PNC Bank

3.47%

2.08%

4.71

0.4154

Axos Bank

2.78%

0.69%

5.08

0.8889

Relay

0.00%

0.00%

N/A

N/A

Average recommended rank covers rank-eligible recommendations only.

Relay holds no position in the September competitive set. The table shows the brand at zero across every metric, with no rank-eligible recommendations to calculate an average recommended rank. The brands that now occupy the recommendation layer are the ones Relay must study to understand where its July coverage went.

Prompt Evidence

Questions This Section Answers

  • What do sample business checking account prompts reveal about why Relay is not being recommended?
  • Which competitors receive recommendation credit in prompts where Relay is absent?

ChatGPT / Brand Recommendation Prompt: "best business checking account" Result: Relay is not mentioned in the response, with Chase and other tracked brands receiving recommendation credit.

Perplexity / Brand Recommendation Prompt: "What is the best business bank account for a new small business?" Result: Relay is absent from the response, while competitors with strong source footprints receive recommendation credit.

Google AI Mode / Brand Recommendation Prompt: "Which bank is best to open a business account?" Result: Relay is not surfaced, with the response favoring brands that hold measurable presence in the qualified set.

What CiteWorks Studio Would Do Next

Questions This Section Answers

  • What phased approach does CiteWorks Studio recommend for restoring Relay's AI recommendation visibility?
  • Which phase addresses the root cause of Relay's lost recommendation coverage before building new content?

Phase 1: AI Market Discovery Audit Map which high-intent prompts previously produced Relay recommendations and which competitors now occupy those slots.

Phase 2: Recommendation Readiness Plan Identify the specific prompt clusters and surfaces where Relay can realistically compete for recommendation credit.

Phase 3: Owned Answer Layer Buildout Develop owned content that answers the direct business checking account choice questions where Relay needs visibility.

Phase 4: Citation / Authority Layer Development Build the public evidence layer that AI systems can retrieve and synthesize when forming business checking account recommendations.

Phase 5: Monthly AI Visibility and Recommendation Tracking Track Relay's return to the recommendation layer with monthly measurement against the benchmark's qualified set.

Why This Matters

AI systems are now the first stop for small business owners asking which business checking account to open. Relay's absence from the September 2026 benchmark means the brand is not part of that conversation at all in AI market discovery. Presence alone is not enough, but absence is a harder problem, because no amount of framing quality matters if the brand never appears in the response.

The next move for Relay is targeted correction of the prompt, page, and citation layers. The benchmark shows where the brand lost ground; a company-level analysis would show which specific prompts, competitors, and sources caused the shift. Without that diagnosis, Relay cannot know whether its absence reflects a set change, a source footprint gap, or a shift in how AI systems frame the business checking account category.

Core Metrics

Metric

Value

Mentions

0

Valid recommendations

0

Top 3 recommendation count

0

Rank #1 recommendation count

0

Average recommended rank

N/A

Positive mentions

0

Neutral mentions

0

Negative mentions

0

Raw mention presence rate

0.00%

Valid recommendation coverage

0.00%

Top 3 recommendation rate

0.00%

Rank #1 recommendation rate

0.00%

Net sentiment score

N/A

Strongest cluster by recommendation behavior

None (no presence in Brand Recommendation cluster)

Strongest platform by recommendation behavior

None (no presence across tracked platforms)

Sentiment Score

Sentiment Score = (positive mentions × 1 + neutral mentions × 0 + negative mentions × -1) / total mentions

Relay has no sentiment score because the brand recorded zero mentions in the September 2026 qualified set. This matters because unclassified mention counts are misleading: a brand with high raw presence but mostly neutral framing is not winning recommendations. Share of voice is a diagnostic metric, not a business KPI. A positive recommendation, neutral reference, cautionary mention, and competitor-displaced mention are not equal. Counting all mentions as wins is bad measurement. Classified sentiment is required before interpreting AI visibility, and Relay currently has no mentions to classify.

Sentiment by Platform

Platform

Mentions

Positive

Neutral

Negative

Sentiment Score

Readout

ChatGPT

0

0

0

0

N/A

No public presence in this packet

Copilot

0

0

0

0

N/A

No public presence in this packet

Gemini

0

0

0

0

N/A

No public presence in this packet

Perplexity

0

0

0

0

N/A

No public presence in this packet

AI Overviews

0

0

0

0

N/A

No public presence in this packet

AI Mode

0

0

0

0

N/A

No public presence in this packet

Methodology

  1. This report is a benchmark-based analysis of Relay's AI recommendation visibility in the Business Checking Accounts vertical, not a client implementation case study.
  2. The reporting window is September 2026, with comparison to the July 2026 and August 2026 benchmark measurements.
  3. The benchmark tracks six canonical AI/search surface families: ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, and AI Mode.
  4. The September 2026 benchmark produced 144 qualified observations from 800 source prompt-surface observations and 656 unique questions.
  5. The tracked competitive set includes 10 brands in September 2026, down from 48 in July 2026.
  6. The public benchmark measures the Brand Recommendation buyer-intent class, which captured all 144 qualified observations in September 2026.
  7. Stage 0 extraction retains the query, AI/search surface, answer, brand outcome, recommendation placement, sentiment, and citations where exposed.
  8. A mention is defined as any appearance of a tracked brand in an AI response to a qualified observation.
  9. A valid recommendation is defined as a clear recommendation of a tracked brand in response to a qualified observation, distinct from a neutral reference or cautionary mention.
  10. Relay is not present in the September 2026 tracked set, so all brand-level metrics are recorded as zero.
  11. The benchmark does not measure market share, attributable sales, every possible AI response, organic-search ranking, or causality from metric movement alone.
  12. Movement in a metric reflects a change in the benchmark; it does not by itself establish why the change occurred. Multiple brands fell from measurable July coverage to no recorded coverage because they no longer appear in the tracked company list, which the benchmark identifies as set changes rather than measured declines in brand quality.

Get Your AI Visibility Audit

The public benchmark shows where Relay lost recommendation coverage, but it cannot identify the specific prompts, competitors, or sources causing the result. A company-level AI visibility audit maps those patterns into a prioritized strategy for returning to the business checking account recommendation layer. To see where competitors are being recommended instead of your brand, a focused audit of your prompt, page, and citation layers is the practical first step.

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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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