Built for MCA brokers and ISO offices
The funded-deal SERP is the only SERP that matters. Audit your brokerage against Rapid, Kapitus, OnDeck, BlueVine, Forward Financing, and the AI surfaces that now sit between a borrower and a quote request.
Built for ISO offices and direct-funder brokerages: the schema, entity, and content gaps that quietly leak funded deals, with disclosure guidance alongside.
The diagnosis
Three failure modes we see on roughly nine out of ten MCA brokerages we audit. Each is structural to the vertical, not random.
The generic playbook
What is actually true for this vertical
How our audit covers it
Generic playbook
Generic SEO tools tell you to "add more keywords on the page" and rank you against the same horizontal Top-10 they show every site they audit.
Reality
The MCA SERP is a tight, well-defended ring of about 12 to 20 brokers (Rapid Finance, Kapitus, OnDeck, Forward Financing, CAN Capital, Credibly, Lendio, BlueVine, Reliant Funding, Fundbox, plus regional players). Generic competitive analysis surfaces noise like Investopedia and Forbes, not the brokers actually winning quote-request volume.
Our coverage
Vertical-aware competitor sets baked into every audit: we benchmark you against the real MCA broker ring (10 named brokers in the adapter), and explain the schema and entity gaps that separate you from the brokers AI engines already cite.
Generic playbook
Classic audits do not check for the regulatory-disclosure surface that B2B finance buyers (and AI engines) read as a trust signal.
Reality
When ChatGPT, Perplexity, or Claude is asked "what is the best merchant cash advance for a $50k restaurant draw," the models lean on Nav, NerdWallet, Fundera, and SBA citations. Brokers without an APR-equivalent disclosure, a state-licensure footer, or LoanOrCredit / FinancialProduct schema give a careful buyer, and an engine, far less to verify.
Our coverage
Vertical-tailored guidance and review prompts for the APR-equivalent disclosure, the state-licensure footer, and "guaranteed approval" language, alongside the checks that run on every audit: the MCA adapter raises the entity-graph finding to HIGH severity and tailors every fix to B2B finance.
Generic playbook
Horizontal tools score "AI visibility" as an afterthought add-on. MCA buyers research entirely through AI before they ever request a quote.
Reality
B2B borrowers (independent restaurant owners, fleet operators, e-commerce merchants drawing working capital) now spend the first 20 minutes of their decision in ChatGPT or Perplexity. If your brokerage is not cited there, you are not in the consideration set. Period.
Our coverage
Equal-weight AI Visibility pillar: passage extractability for the 134-167 word "factor rate vs APR" passages LLMs prefer to lift, schema completeness for LoanOrCredit + FinancialProduct + Organization, citation tracking across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews for the 12 to 25 funded-deal queries that matter most for your brokerage.
The checks, vertical-tailored
Every audit, on every plan, scores Foundational SEO, Technical SEO and AI Visibility. Local SEO is scored when the pages we read show a physical location or a service area, such as a street address, a city and state or a Maps link. The check definitions are constant; the severity, the recommended fix, the competitor set, and the example code shift per vertical via the adapter.
Foundational pillar
Keyword universe, content depth, on-page structure, internal link graph.
Your "Apply for an MCA" page must lead with a single H1 ("Working capital for [industry], funded in 24 to 72 hours") that matches the funded-deal intent, not a generic "Welcome" header.
Each offer-detail page should carry a 134 to 167 word "How factor rates work vs APR" passage co-located under a question-shaped H2 so ChatGPT and Perplexity can lift it verbatim into an answer.
Cite the CFPB small-business-financing inquiry, the SBA primer on alternative financing, and at least one Federal Reserve source on credit access. Outbound authority on regulatory pages signals trust to both Google E-E-A-T and to citation-aware LLMs.
Technical pillar
Crawl, render, schema validation, Core Web Vitals, render-parity diff.
LoanOrCredit + FinancialProduct JSON-LD must validate against schema.org. Include interestRate (as factor rate, with APR-equivalent disclosure), loanType "Merchant Cash Advance", and a fees-and-commissions specification URL.
Your offer table and APR disclosure must render in raw HTML, not via React after hydration. AI crawlers (GPTBot, ClaudeBot, PerplexityBot) do not execute JS and will treat the page as empty if your pricing is client-rendered.
MCA quote-request landing pages are mobile-dominant (borrowers fill out forms from a phone in a back office). LCP below 2.0s and INP below 200ms are required to keep funded-deal conversion above the broker-network average.
Local pillar
On-site local signals: LocalBusiness schema, Maps link, phone and address, service-area pages.
The audit checks that a LocalBusiness-class type is declared in your JSON-LD. If you operate from a physical office in a single state, LocalBusiness with state-licensure references in the address block fits. Multi-state ISO offices should use Organization with a sameAs to each state license verification page.
The audit reads this page for a complete phone, street address, and ZIP code fingerprint. It does not compare your listings on the BBB, Crunchbase, LinkedIn, or your state-of-incorporation registry; check those by hand so they match your site exactly.
AI Visibility pillar
AI crawler readability, schema for AI, passage extractability, entity graph.
AI engines lean on Organization + LoanOrCredit + FinancialProduct + FAQPage. Missing any of the four drops you out of the citation pool for "best MCA company" queries. The fix is ~80 lines of JSON-LD and one deploy.
sameAs from your homepage Organization JSON-LD to your Crunchbase, LinkedIn, BBB, and (if applicable) Trustpilot profiles. AI engines triangulate B2B-finance authority through these graphs. Most brokerages we audit ship only a LinkedIn link.
A render-parity diff catches the case where your pricing table renders in raw HTML for browsers but lives behind a React Query call for AI crawlers. We measure raw HTML token count vs rendered token count and flag any page where AI sees less than 70 percent of what humans see.
Sample findings
Three illustrative findings in the format a MCA and merchant cash advance audit produces. Each carries a severity, a confidence flag, and a link to the methodology page that justifies the score.
AI Visibility pillar
AI engines need LoanOrCredit and FinancialProduct JSON-LD to surface MCA offers in "what is the best merchant cash advance" answers. Your /offers/* pages publish Organization JSON-LD but no LoanOrCredit block. Citation rate on Perplexity for "best MCA for restaurants" is currently 0 percent vs Rapid Finance at 18 percent.
Methodology →Foundational pillar
The factor-rate pricing page you audited declares no meta description, so Google writes the snippet from the first text it finds, here a cookie banner. A specific description naming the advance range, the funding speed, and who qualifies earns the click on "merchant cash advance for [industry]" queries. The fix is one template field.
Methodology →Local pillar
The contact page shows a phone number but no street address or ZIP code, so the on-page name, address, and phone fingerprint is incomplete. Publish the full office address in plain HTML and in Organization or LocalBusiness JSON-LD, then make your external profiles match it.
Methodology →Glossary preview
Glossary
The SEO practice for merchant cash advance brokerages, which differs from generic finance SEO in three material ways: B2B (not consumer) buyer intent, regulatory-disclosure surface that doubles as a trust signal, and a tight competitor ring of about 15 named brokers (Rapid, Kapitus, Forward, OnDeck, Credibly, et al) that dominates every funded-deal query.
Read the entry →
Glossary
MCAs are priced as a factor rate (commonly about 1.1 to 1.5) applied to the advance. The estimated APR puts that cost on a yearly basis, and on a short remittance term it often runs into triple digits. California and New York already require an estimated APR in commercial-financing disclosures, and publishing it plainly is also the kind of transparency AI engines can quote.
Read the entry →
Glossary
schema.org's FinancialProduct family, including LoanOrCredit, describes a financing offer: amount range, estimated APR, and a feesAndCommissionsSpecification URL pointing at your cost disclosure, with your Organization as provider. Because most MCAs are structured as purchases of future receivables, choose the type your counsel agrees matches the contract.
Read the entry →
Glossary
A site-footer disclosure listing each state where the brokerage or funder is registered or licensed, with the agency, registration type, and number, linked to the state lookup. Utah, Virginia, Texas, and other states now require registration for sales-based financing. Verifiable registrations are one of the strongest trust signals a finance site can show; never imply a license you do not hold.
Read the entry →
Glossary
On generic "best merchant cash advance" questions, ChatGPT, Claude, and Perplexity lean on comparison and education sites such as Nav, NerdWallet and Fundera, and SBA.gov. Funder and broker sites earn citations on narrower questions, with extractable answers, transparent costs, LoanOrCredit or FinancialProduct markup, and a complete entity graph. The mix varies by engine, so the AI visibility check samples it on questions about your business.
Read the entry →
Compliance + trust note
MCA is not consumer credit, but several states (New York, California, Utah, Virginia and others) now require commercial-financing disclosures or provider registration, and APR-equivalent pricing and licensure transparency are what a careful buyer looks for. Three points are worth reviewing on every pricing page: an APR-equivalent disclosure next to factor rates, a state-licensure or registration footer, and no "guaranteed approval" language. We are not a substitute for an underwriting-compliance review by your in-house counsel.
Today the compliance points on this page are vertical-tailored guidance and review prompts for you and your compliance reviewer. The audit does not run them as automated checks, and nothing in the report is a compliance verdict.
Five questions we hear most from MCA brokerages
Semrush and Ahrefs benchmark you against the horizontal Top-10 for any keyword you query. They surface Investopedia and Forbes as competitors. Our MCA-tailored audit benchmarks you against the real broker ring (Rapid, Kapitus, OnDeck, Forward, CAN, Credibly, Lendio, BlueVine, Reliant, Fundbox), and tailors every finding and fix to B2B finance. APR-equivalent disclosure and state-licensure points come as guidance and review prompts today, not automated checks.
Yes, and the share is growing fast. Borrowers (restaurant owners, fleet operators, e-commerce merchants) now spend the first 20 minutes of their funding research in ChatGPT or Perplexity before requesting a quote. If your brokerage is not cited on "best merchant cash advance for [industry]" queries, you are not in the consideration set. The free AI visibility check samples those answers; paid plans track them weekly. The audit's AI Visibility pillar grades whether your pages are ready to be cited.
Not automatically, yet. Today the disclosure points (APR-equivalent disclosure, state-licensure footer, "guaranteed approval" language, fees and commissions) are guidance and review prompts on this page, not checks the audit runs. They are never a substitute for an underwriting-compliance review by your in-house counsel.
The free audit usually takes 2 to 3 minutes and reads 1 page, the one you enter. Paid plans add weekly AI answer tracking on six AI answer engines, from 25 tracked prompts on Starter to 150 on Agency, more pages per audit, history, and PDF reports, white-labeled on Pro and Agency.
Most brokerages have not. The methodology page on schema-completeness-for-ai includes a paste-ready JSON-LD block with the LoanOrCredit + FinancialProduct fields that AI engines look for, plus citation links to the schema.org specs. The fix is typically one deploy.
Free. No login. Top three findings per pillar visible inline. The full report (typically 45 to 70 findings, vertical-tailored, with evidence and fix per finding) is emailed when you drop an address. MCA brokerages get the audit pre-set to your vertical.