Buy Sell Land
Vacant-land acquisition across the Southeast. County-level entity architecture, structured geographic relevance and AI-citation testing.
- Location-scale content systems
- Commercial seller intent
- AI recommendation testing
AI VISIBILITY ENGINEERING
Your customers are asking AI who to hire.
Find out who it recommends instead.
RankOps measures how ChatGPT, Gemini, Perplexity, Google AI and other answer engines understand your business, then fixes the evidence, entity, content and authority gaps costing you buyer visibility.
Buyer promptstested, not guessed
Competitorsnamed by AI
Gap ledgertracked until closed
Retestingproof over promises
SEO+AEO+GEO+ENTITY ENGINEERING+AI CITATION TRACKING
THE NEW SEARCH PROBLEM
Ranking is no longer the whole battlefield.
Customers increasingly ask AI systems direct buying questions. They do not always click ten blue links first. The answer engine compares entities, sources, proof and relevance, then produces a recommendation.
“Who should I hire?”
“What is the best company for this?”
“Where should I buy this?”
“Who actually specializes in my problem?”
Somebody gets recommended. Somebody does not. RankOps measures that gap.
THE INSTRUMENT
We track what AI actually says.
Not a vanity score. Not a keyword-position screenshot. RankOps tracks buyer prompts, entity mentions, competitors, citation sources, wins, losses and unresolved visibility gaps over time.
THE FLAGSHIP
The RankOps AI Visibility System
A continuous commercial visibility loop built around one question: why is AI recommending someone else when the buyer is ready to act?
- 01
Measure
Build a buyer-prompt map and test branded, non-branded, local, comparison, recommendation and transactional questions.
- 02
Diagnose
Identify citation gaps, entity ambiguity, missing evidence, weak commercial pages, source deficiencies and authority deficits.
- 03
Engineer
Build the missing structure: entity relationships, answer-ready content, schema, proof, internal linking, landing pages and source-targeted authority work.
- 04
Validate
Retest the exact buying situations. A recommendation is only a win when the system can see it.
- 05
Compound
Keep a rolling gap ledger. Preserve unresolved gaps, flag new wins separately, and attack the highest-value next opportunity.
THE MONCRIEFF METHOD
Evidence first. Machines second. Claims last.
RankOps does not begin by spraying content. We begin by defining the entity, the buying situation, the evidence available and the sources machines are already using.
Audit→Entity→Answers→Citations→Tracking
PROOF, NOT POSTURING
Built in real businesses.
Different industries expose different failure modes. RankOps uses owned projects and client work to test what actually improves machine understanding and commercial discoverability.
Kaminos
A large Shopify catalog with technical products, collections, manufacturers and specifications that cannot tolerate reckless bulk edits.
- Catalog reconciliation
- Collection and PDP optimization
- Evidence-led QA and controlled rollout
RankOps Lab
Owned entities and brands are continuously tested to understand attribution, citation sources, related-entity confusion and prompt-level visibility.
- Share-of-voice tracking
- Entity resolution experiments
- New citation win detection
SHOPIFY SPECIALIZATION
Improve visibility without gambling with the catalog.
Large Shopify stores can have thousands of products and fragile relationships between collections, vendors, specifications, metadata and theme behavior. The optimization process needs controls.
Discuss a Shopify Safety SprintShopify SEO Safety
01
Reconcile products, collections, templates and evidence.
02
Research official manufacturer and product sources.
03
Preview proposed changes before write access is needed.
04
QA deterministic rules before implementation.
05
Roll out controlled batches with snapshots and rollback protection.
HOW WE ENGAGE
One diagnostic. One system. Continuous improvement.
The entry point should create clarity by itself, then credit naturally into implementation.
DIAGNOSTIC
AI Visibility Opportunity Map
$1,250
Commercial prompt testing, competitor mapping, source analysis, severity-ranked gap ledger and exact implementation roadmap.
- Buyer-intent prompt set
- Branded + non-branded tests
- Competitors AI names instead
- Citation/source map
- Critical gap priorities
100% credited toward the System Build.
Map My VisibilityFLAGSHIP
AI Visibility System Build
From $4,997
Implementation of the highest-value entity, content, evidence, structured-data and commercial visibility improvements identified in the map.
- Entity architecture
- Commercial answer surfaces
- Schema and internal relationships
- Evidence and authority plan
- Tracker baseline + retest
RECURRING
AI Visibility Growth
$1,500–$2,500/mo
Continuous prompt testing, gap closure, content/entity improvements, authority work and verified wins.
- Rolling gap ledger
- New-winner alerts
- Competitor movement
- Monthly implementation
- Commercial retesting
THE ECONOMIC LOGIC
You do not need thousands of clients.
RankOps is designed as a high-trust, high-leverage specialist company. A small number of serious accounts can create a viable base while the tracker and methodology compound.
4 clients× $2,000/mo$8,000 MRR
+ 1 system build× $4,997≈ $13K month
8 clients× $2,000/mo$16,000 MRR
START WITH THE BUYING QUESTIONS
Stop guessing whether AI knows who you are.
Give us your email and website. RankOps will use the conversation to determine the commercial prompts worth testing and whether the Opportunity Map is a fit.