I do not want my first serious RV park mistake to happen after closing.
That is the point of underwriting. Not to make the deal look good. To make the weak spots visible before momentum takes over.
This is the first-pass checklist I would use before spending serious time, money, or emotional energy on an RV park.
The Short Answer
Before underwriting returns, I would underwrite reality:
- How many sites exist?
- How many are occupied?
- What type of occupancy is it?
- Are the utilities clean?
- Is the current use legal?
- Can the seller prove income?
- What is the real expense load?
- What capex is coming?
- Who manages the park?
- What happens if occupancy does not improve?
If those questions are fuzzy, the IRR does not matter yet.
Site Count and Site Mix
The first question is not just "How many sites?"
It is:
- How many sites are rentable today?
- How many are long-term?
- How many are nightly or weekly?
- How many are vacant because of demand?
- How many are vacant because of infrastructure?
- Are there expansion sites, and are they actually permitted?
A 90-site park with 70 usable sites is not a 90-site park for underwriting purposes.
Rate Mix and Revenue Quality
After site count, I would separate revenue by customer type.
Nightly, weekly, monthly, seasonal, and long-term residents all behave differently. A blended average rate can hide important risk. A nightly guest may produce more revenue per site, but also requires marketing, cleaning, reviews, booking systems, and hospitality operations. A long-term resident may produce less revenue per site, but can create steadier income and lower turnover.
I would want to know:
- Average rate by site type
- Occupancy by site type
- Length of stay by customer type
- Seasonal revenue swings
- Refunds, discounts, and non-payment
- Ancillary income from laundry, storage, utilities, or vending
The goal is to understand the quality of the income, not just the total income.
Occupancy and Demand
Current occupancy matters because it tells me whether the market is already accepting the product.
I would want to know:
- Current occupancy by site type
- Historical occupancy by month
- Average length of stay
- Waitlist or inquiry volume
- Nearby employers, attractions, or demand drivers
- Competing parks and their pricing
The key question is whether low occupancy is a management problem or a demand problem.
Management problems can be fixed. Demand problems are harder.
Expense Normalization
The seller's expenses are not automatically the buyer's expenses.
This is one of the easiest ways to overpay for a small park. A long-time owner may self-manage, defer repairs, pay below-market insurance, use informal labor, ignore software, or understate maintenance because they have been handling problems personally for years.
After closing, the buyer may need professional bookkeeping, better insurance, software, legal support, property management, marketing, utility repairs, and reserves.
That means I would normalize expenses before underwriting returns.
I would not ask, "What did the seller spend?"
I would ask, "What will this property cost me to operate responsibly?"
Utilities
Utilities can make or break an RV park.
I would want records for:
- Water source and capacity
- Sewer or septic system
- Electrical capacity
- Internet and cable availability
- Trash contracts
- Stormwater or drainage issues
- Any known violations or repair history
If the park has private utilities, the diligence bar is higher. If the park needs major utility upgrades, that belongs in the model before the offer feels attractive.
Capex and Deferred Maintenance
Capex is where a cheap-looking deal can become expensive.
I would want to walk the property with a very practical eye: roads, drainage, electrical pedestals, septic, water lines, bathhouse condition, laundry, signage, trees, lighting, fencing, office, common areas, and any structures on site.
The question is not only what is broken today. The question is what will probably need money in the next 12 to 36 months.
I would separate capex into three buckets:
- Immediate safety or legal items.
- Operational improvements that protect income.
- Optional upgrades that might improve revenue later.
Only the first two belong in the base case.
Zoning and Legal Use
I would not rely on the seller's memory here.
I would want to verify:
- Current zoning
- Permitted RV use
- Number of approved sites
- Rules for long-term residents
- Expansion limits
- Any open code issues
- Any nonconforming-use risk
A park can look profitable and still carry real legal-use risk.
Management Plan
The management plan belongs in underwriting, not after closing.
Before buying, I would want to know who handles guest communication, collections, maintenance, rules enforcement, bookkeeping, reviews, online listings, and emergency issues.
If the park is long-term resident heavy, the management plan may look more like community operations. If it is nightly or weekly heavy, it may look closer to hospitality. If it is mixed, the systems need to handle both.
This is where an owner can fool herself. A park can look passive in a spreadsheet and become very active in real life.
I would rather be honest about that before closing.
Income and Expense Proof
For income, I would want more than a spreadsheet.
Useful records include:
- Bank statements
- Booking platform reports
- Rent roll
- Utility reimbursements
- Laundry, storage, or other ancillary income
- Tax returns where available
- Point-of-sale records if there is a store
For expenses, I would focus on what changes after ownership:
- Insurance
- Property tax reset
- Management
- Repairs and maintenance
- Utilities
- Software
- Bookkeeping
- Legal and accounting
- Capex reserves
The seller's expenses are not automatically my expenses.
Exit and Refinance Risk
Even if I plan to hold long term, I would still underwrite the exit.
If there is seller financing with a balloon, the refinance risk is obvious. But even without a balloon, I want to know what the asset would look like to another buyer or lender after my improvements.
Questions I would ask:
- Can the property support conventional refinance debt?
- Would a lender trust the records after 12 to 24 months?
- Is the market liquid enough for resale?
- What buyer would want this asset later?
- Does the value depend on my personal effort, or on durable business income?
The exit is not a separate event. It is the test of whether the business I am buying can become cleaner, more financeable, and more valuable.
Financing and Exit Risk
I would underwrite the deal with the financing structure included from the beginning.
Questions I care about:
- Is seller financing available?
- What cash is needed at close?
- Is there a balloon?
- Can the property support refinance debt?
- What happens if rates are higher at refinance?
- What if occupancy improves more slowly than expected?
- What if the cost segregation estimate is lower than hoped?
The exit cannot be a footnote. It is part of the acquisition.
My First-Pass Decision
After the checklist, I want one of three answers:
- Pass quickly.
- Keep watching, but do not spend major diligence dollars yet.
- Move deeper into diligence with a clear list of unknowns.
That is the point of a checklist. It keeps the deal from becoming a story before it becomes a business.
The best acquisitions are not the ones where every answer is perfect. They are the ones where the important risks are visible early enough to price, structure, or walk away from them.
First-Pass Underwriting Flow
The first pass should answer these in order:
- Is the current use legal and documented?
- Are the sites real, rentable, and supported by utilities?
- Can the seller prove income and occupancy?
- Do expenses change materially after closing?
- Does the financing structure leave enough room for reserves and capex?
- Is the upside operational, or does it require a construction miracle?
RV Park Underwriting Checklist Table
| Underwriting area | Documents or proof I want | Pass, watch, or fail signal |
|---|---|---|
| Site count | Site map, rent roll, utility map | Fail if advertised sites are not actually usable |
| Occupancy | Rent roll, booking reports, historical occupancy | Watch if low occupancy has no clear reason |
| Utilities | Water, sewer, power, internet, violations, repair history | Fail if major systems are unknown or undocumented |
| Legal use | Zoning confirmation, permits, code status | Fail if current use is not clearly allowed |
| Income | Bank statements, tax returns, platform reports | Watch if income only exists in a seller spreadsheet |
| Expenses | Insurance, taxes, utilities, management, capex | Watch if post-close expenses are materially higher |
| Financing | Seller note, bank terms, balloon, reserves | Fail if debt service leaves no margin for mistakes |
Graph: Where RV Park Underwriting Risk Usually Hides
Frequently Asked Questions
What should be included in RV park underwriting?
RV park underwriting should include site count, occupancy, rate mix, utility ownership, zoning, rent roll, historical income, operating expenses, capex, management plan, financing, and exit risk.
What is the biggest underwriting risk in RV parks?
The biggest risks are usually undocumented financials, utility systems that are more expensive than expected, legal-use uncertainty, and assuming occupancy can rise without proving demand.
Should nightly and long-term sites be modeled separately?
Yes. Nightly, weekly, monthly, and long-term sites have different revenue, turnover, management, seasonality, and expense patterns. I would model them separately before trusting the blended numbers.
Operator Decision Framework
The practical question is not whether AI can touch this work. The question is whether the work has enough structure for AI to improve it without creating more cleanup. I look for four signals before I trust a workflow with more automation: the input is reliable, the desired output is easy to recognize, the failure mode is manageable, and the next action is already defined.
If any of those signals are missing, the answer is not to avoid AI forever. The answer is to slow down and design the operating layer first. That usually means writing the checklist, naming the source of truth, choosing the review owner, and deciding what the system should do when the input is incomplete.
| Operating question | Good signal | Risk signal |
|---|---|---|
| Input quality | The source is current, specific, and easy to cite. | The AI has to guess which source is accurate. |
| Output standard | A reviewer can approve or reject the result quickly. | Everyone has a different opinion of what good means. |
| Failure mode | A mistake is caught before a customer or counterparty sees it. | A mistake creates legal, financial, or relationship damage. |
| Next action | The output moves into a known queue, CRM, calendar, or draft surface. | The output sits in a chat thread and gets forgotten. |
How I Would Implement This in a Real Business
I would start by choosing the smallest workflow that still matters. For a service business, that might be missed-call recovery, lead follow-up, estimate reminders, review requests, or weekly reporting. For a real estate operator, it might be deal intake, rent-roll review, seller follow-up, or lender package prep. For a founder-led consulting business, it might be proposal drafting, client onboarding, content repurposing, or inbox triage.
The first version should be deliberately narrow. The AI receives a defined input, produces one defined output, and writes the result somewhere visible. A human reviews the output for a few cycles, records what needed correction, and then turns those corrections into better instructions. That is how the system gets stronger without requiring constant babysitting.
Common Failure Modes to Watch
The most common failure is letting the AI create more surface area than the business can govern. More drafts, more alerts, more summaries, and more dashboards do not automatically mean better operations. The goal is fewer missed decisions and cleaner follow-through, not more things to look at.
The second failure is treating the AI output as proof. A summary is not proof. A draft is not proof. A completed checklist is not proof unless it points back to the source material that made the answer reliable. Strong AI systems make the proof easier to inspect.
Related Source Pages
This topic connects to the broader AI operating system I use across content, acquisition, and implementation work. These related pages are useful next steps:
- How to integrate AI into a small business
- AI integration roadmap
- AI automation mistakes
- AI vs hiring
- AI implementation consulting
Frequently Asked Questions
What is the main takeaway from The RV Park Underwriting Checklist I Would Use First?
The main takeaway is that AI only creates leverage when the workflow has clear inputs, clear standards, and a clear owner. The tool is not the operating system. The operating system is the set of rules that decides what the AI can do, what it must check, where the output goes, and when a person needs to make the final call.
How should a small business start applying this idea?
Start with one repeated workflow that already happens every week. Document the trigger, the source of truth, the expected output, the review rule, and the place where the final result is logged. Once that workflow is stable, use AI to reduce the repetitive work around it. Do not start by connecting every tool in the business at once.
What should stay with a human operator?
The human operator should own judgment, taste, relationship context, strategy, standards, and final accountability. AI can prepare drafts, summaries, research, intake notes, and follow-up queues, but the business still needs a person who understands the goal and can tell whether the output is good enough to use.
What makes this content useful for AI search and answer engines?
Answer engines need direct definitions, decision rules, examples, and complete context. A post is more likely to be useful when it answers the question early, explains the criteria, shows a practical framework, and includes related source pages that clarify how the concept works in a real business.
When is this approach not enough?
This approach is not enough when the business has no defined process, no source of truth, or no owner for review. In that case, the first project is operational design, not automation. The workflow needs to be clarified before AI can make it faster.
Final Takeaway
The baseline is simple: AI should remove manual work wherever the system has proof, feedback loops, and operating standards. Humans should own judgment, standards, relationships, and final accountability. When those roles are clear, the business gets leverage without turning every workflow into a new cleanup project.
Additional Operating Notes for The RV Park Underwriting Checklist I Would Use First
One reason this matters is that small businesses rarely fail at AI because they chose the wrong model. They fail because the workflow around the model is vague. The owner expects the system to know context that was never documented, the team expects a draft to be final, and no one knows where corrections should be stored. A better implementation makes those rules explicit.
That means the workflow should define the source, the output, the reviewer, the escalation path, and the evidence trail. If the system cannot show where the answer came from, the answer should be treated as a draft. If the system cannot explain what action happens next, the workflow is not finished. This is the difference between useful AI and more digital clutter.