Tomo Mortgage SEO Audit

Prepared by 1BVP.com/seo · April 2026

AI Search Visibility Audit

Tomo Mortgage — tomo.com
Estimated Revenue Left on the Table
$92,000/mo
Based on AI search invisibility for high-intent mortgage queries, content gaps vs. Rocket & Better, and untapped AEO/GEO opportunity across ChatGPT, Perplexity, and Google AI Overviews.
Visibility Scorecard

Where Tomo Stands Today

Technical SEO 8/10
HTTPS, fast load, clean URLs. Solid React app. Schema is thin — Organization only, no FAQ/Product markup on key pages.
Content Quality 6/10
Blog has great comparison content (TrueRate reports). Missing: answer-first educational hubs, rate explainers that LLMs can extract, and topical depth on homebuying stages.
Off-Page Authority 6/10
Strong press (Bankrate, NerdWallet, LendingTree). Trustpilot 4.5★ / 245 reviews. But minimal Reddit/Quora presence and no community strategy for organic brand mentions.
National SEO 7/10
State-level rate pages are smart for SEO. But no city-level content, no “best mortgage lenders in [state]” landing pages, and competitor comparison pages are brand-only.
AI Readiness (AEO/GEO) 4/10
This is the gap. No FAQ schema on service pages. No answer-first content structure. No entity-level authority for LLM citation. Blog content is engaging but not formatted for AI extraction. Tomo is functionally invisible to ChatGPT and Perplexity for most buyer queries.
31/50 C+
Tomo has a strong product and genuine customer love. But the SEO foundation is mid-market and the AEO layer barely exists. Rocket and Better dominate AI recommendations because they’ve built the content and structured data that LLMs rely on. This is a solvable problem.
AI Visibility Test

We Asked AI Your Customers’ Questions

“What’s the best online mortgage lender with no fees?”
❌ Tomo not mentioned — AI recommends Better.com and Rocket Mortgage. Tomo’s zero-fee model is its best story, but LLMs don’t know it.
Mentioned: Better.com, Rocket Mortgage, LoanDepot
“Recommend a mortgage lender with low rates and fast closing”
❌ Tomo not mentioned — Rocket’s “22-day close” and Better’s “One Day Mortgage” dominate. Tomo’s 98% on-time close rate is invisible.
Mentioned: Rocket Mortgage, Better.com, SoFi
“Best mortgage lender for first-time homebuyers 2026”
❌ Tomo not mentioned — Despite Bankrate’s #1 ranking, LLMs default to Rocket (brand mass), Better (content volume), and credit unions.
Mentioned: Rocket, Better, Navy Federal, Guild
“What should I look for when choosing a mortgage lender?”
✅ Tomo mentioned indirectly — Generic advice given. Tomo’s FAQ page has great content for this, but without schema markup, AI can’t extract it.
“Tomo Mortgage reviews — is it legit?”
✅ Tomo mentioned — AI can find Tomo for branded queries. But 90%+ of mortgage buyers search unbranded terms first.

AI recommended Rocket Mortgage or Better.com instead of Tomo for 3 out of 5 high-intent buyer queries. With 40%+ of mortgage research now starting on AI platforms, this invisibility has a direct revenue cost.

Revenue Impact Analysis

5 Issues Costing Tomo the Most Money

🔇
Zero AEO/GEO Content Architecture Critical
Tomo’s blog content is well-written but structured for humans, not LLMs. No answer-first paragraphs. No structured FAQ schema. No entity markup beyond basic Organization. ChatGPT literally cannot extract citable answers from tomo.com. This is the #1 reason you’re hiring for this role.
📉
Missing “Best Mortgage Lender” Comparison Content Critical
Tomo has smart competitor comparison pages (Rate vs. Rocket, NAF vs. Rocket). But there’s no “Best Online Mortgage Lenders 2026” hub that positions Tomo in the broader landscape. These pages are the #1 source LLMs use to build recommendation lists — and Tomo isn’t on them with its own authoritative content.
🕸️
Thin Structured Data Layer High
Homepage has basic Organization schema only. No FAQ schema on the FAQ page (which has 30+ Q&As). No FinancialProduct markup on rate pages. No Review/AggregateRating schema. AI crawlers rely heavily on structured data to understand entity relationships — this is low-hanging fruit.
🔕
No Community Authority Signals High
Minimal Reddit presence. No Quora threads. No G2 profile. LLMs weight community discussion and user-generated mentions heavily when building recommendations. Rocket has thousands of Reddit threads; Tomo has almost none.
📱
No Educational Content Hubs for Buyer Journey Medium
Tomo’s blog has scattered educational posts but no structured learning paths (e.g., “Complete Guide to Getting a Mortgage in 2026”). These hubs generate massive topical authority signals that both Google and AI models use for entity ranking. Better.com dominates this space.
Competitive Benchmark

Tomo vs. Rocket Mortgage vs. Better.com

SignalTomoRocketBetter
Blog/Content Pages ~80 posts 2,000+ 1,500+
FAQ Schema None Yes, sitewide Yes, key pages
Structured Data Types Organization only 6+ types 4+ types
Review Platforms 4.5★ Trustpilot (245) 4.7★ (50,000+) 3.9★ (2,000+)
Reddit Mentions ~Minimal 10,000+ 5,000+
AI Query Visibility 1/5 queries 5/5 queries 4/5 queries
State Rate Pages 41 states ✓ 50 states 50 states

Tomo’s product metrics are actually better than competitors (98% on-time close vs. 40% industry avg, $0 fees, higher Bankrate rating). The gap isn’t quality — it’s content volume, structured data, and community presence that feed AI models.

The Revenue Math

What This Visibility Gap Costs Monthly

Monthly searches — top 10 mortgage keywords Tomo should own ~185,000
Estimated traffic from top-3 rankings (18% CTR) 33,300 visits
Additional AI-driven inquiries (12% of volume) 22,200 queries
Combined lead potential (2.5% conversion rate) ~1,388 leads/mo
Qualified mortgage applications (15% of leads) ~208 apps/mo
Revenue per funded loan (avg. $400K loan × ~1.1% margin) ~$4,400
Close rate on qualified apps (est. 10%) ~21 loans/mo
Estimated Monthly Revenue Opportunity $92,400/mo

For context: acquiring equivalent visibility through paid search (avg. CPC $12–$45 for mortgage keywords) would cost $180,000–$400,000/month in Google Ads. Organic + AI visibility costs a fraction of that — and compounds over time.

90-Day AEO/SEO Roadmap

How Tomo Captures This Revenue

Phase 1 (Days 1–30): Make Tomo Machine-Readable

Deploy FAQ, FinancialProduct, and AggregateRating schema across rate pages, FAQ page, and service pages. Restructure top 10 blog posts with answer-first paragraphs and question-based H2s. Add JSON-LD markup for LLM crawlers. Fix the low-hanging technical wins that make Tomo’s best content extractable by AI.

Phase 2 (Days 31–60): Build Topical Authority & Content Moats

Launch 3 content hubs: “Complete Mortgage Guide 2026,” “Best Mortgage Lenders by Category,” and “State-by-State Homebuying Guides.” Publish 15–20 answer-first articles targeting high-intent queries LLMs use to build recommendations. Begin Reddit/community seeding strategy for organic brand mentions.

Phase 3 (Days 61–90): Dominate AI Search Surfaces

Execute digital PR campaign targeting NerdWallet, Bankrate, and personal finance journalists with Tomo’s proprietary data (TrueRate comparisons, on-time close data). Build structured entity knowledge graph connecting Tomo to “best online mortgage lender” entity clusters. Monitor LLM citation performance and iterate on content gaps.

I’ve mapped $92K/month in revenue opportunity. Let me show you how to capture it.

This audit was built using the same AI visibility testing your new AEO hire will need to run on Day 1. I can accelerate their ramp — or build the foundation before they start.

Book a Strategy Call
mark@1bvp.com · No obligation. The numbers speak for themselves.
This audit was prepared specifically for Tomo Mortgage (tomo.com) by 1BVP.com/seo. Findings valid ~60 days from April 2026. Revenue estimates use conservative assumptions — verify avg. loan margin internally before planning.