How to Estimate Rental Performance in Phuket Before You Buy: Step-by-Step Method

Buying a Phuket condo for rental income is not a guessing game—it is a modelling exercise. Before you transfer funds, you should be able to explain, in plain numbers, how you derived ADR, occupancy, gross revenue, and net income after fees, CAM, management, OTA commissions, and taxes. If you cannot do that, you are not investing; you are hoping.

This guide walks through a conservative, repeatable method used by serious investors: find five comparable listings, infer occupancy from calendar behaviour, apply realistic annual occupancy (70–80% for many well-managed units, lower for weak operations), then subtract management (15–20%), OTA commissions (15–20% on platform bookings), CAM fees (often around $1,000–2,500/year depending on project), and withholding tax assumptions (commonly modelled around 15% of gross rental revenue in simplified investor spreadsheets—verify with your accountant for your structure).

Step 1 — Pull five comparable units (not “nearby island” comps)

If you cannot find five close comps, your market may be too thin to price confidently—or your unit may be unique in ways that cut both ways (premium uniqueness versus liquidity risk).

Comparables must match:

• Building or street (same supply dynamics)
• Bedroom count and layout
• View tier (sea view vs road view is not cosmetic pricing)
• Furniture quality and pool/gym access

If you compare a Surin premium sea-view unit to a Rawai entry unit, your model is fiction. Bang Tao from around $265K and Rawai from around $96K can both yield well—but not on the same comp set.

Comp quality	What breaks the model
Strong	Same building, similar floor, similar view
OK	Adjacent building with equivalent walk time
Weak	“Same area” but different guest segment

Step 2 — Read calendars like an analyst (occupancy is visible)

On many OTAs, blocked dates can indicate booked nights, owner stays, or maintenance—so you must triangulate. You are looking for patterns:

• Long blocks of unavailability in peak season suggest strong demand or owner blocking (check reviews for clues)
• Wide open calendars in peak season suggest weak pricing, bad reviews, or listing issues

Rule of thumb: assume you are not smarter than the market. If comps struggle to fill, your unit will not magically outperform without a concrete reason (renovation, better management, superior view).

Step 3 — Derive realistic ADR (nightly rate)

Use comparable pricing across shoulder and peak months. Many beginners take January’s rate and multiply by 365—that is how yield fantasies are born.

Season bucket	What to capture
Peak	Highest sustainable nightly rate with good reviews
Shoulder	Discounted but still profitable
Low	Promotional rates that still cover cleaning and wear

Step 4 — Apply conservative occupancy

For professional management, 75% can be a reasonable starting point for modelling when you have evidence of strong demand. For self-managed units with inconsistent guest communication, 60% may be more honest.

Many investors use 70–80% as a planning band for well-managed units in tourism-heavy areas—Kamala often supports 8–10% gross conversations in optimised stock, while Patong can reach 8–12% gross when operations match the nightlife guest profile. 7–9% gross remains a common anchor for Phuket condos when the model is honest.

Management quality	Conservative annual occupancy
Strong operator + good reviews	70–80%
Average	60–70%
Weak / self-managed	50–60% (unless proven)

Step 5 — Gross revenue formula

Gross revenue ≈ ADR × booked nights

Booked nights = 365 × occupancy (for a full-year short-stay strategy without owner blocks).

If you owner-block 8 weeks, you must remove those nights explicitly.

Step 6 — Subtract the fee stack (this is where gross yield dies)

Management (15–20% of revenue)

Many programmes charge 15–20% of gross rental revenue for short-stay management. Long-term leasing may be cheaper but has different lease-up costs.

OTA commissions (15–20% when booked via platform)

If you rely heavily on bookings through OTAs, assume 15–20% of those bookings goes to the platform. Direct bookings improve net, but you must earn them first.

CAM fees ($1,000–2,500/year typical range)

CAM varies by project luxury tier. $1,200/year is a useful placeholder for quick modelling, but verify in the developer’s schedule. Premium projects can exceed $2,000/year.

Withholding tax (often modelled at ~15% of gross rental revenue)

Investors often use 15% as a rough planning placeholder for withholding tax on gross rental revenue in simplified spreadsheets. This is not tax advice—your structure (company vs personal) changes outcomes. Use a Thai accountant before you buy.

Deduction	Typical planning range
Management	15–20% of gross revenue
OTA commissions	15–20% of OTA bookings
CAM	$1,000–2,500/year
Withholding tax (placeholder)	~15% of gross rental revenue (verify)

Step 7 — Net yield and cash-on-cash clarity

Net yield ≈ net income / purchase price

Net income is gross revenue minus all operating costs and taxes, including periodic maintenance, insurance, and furnishings refresh.

Cash-on-cash differs if you use a mortgage—debt service must be layered separately.

Worked example: $200,000 purchase (illustrative)

This is a simplified, investor-style sanity check—not a promise.

Line item	Value
Purchase price	$200,000
Modelled ADR	$130
Modelled occupancy	75%
Booked nights	274
Gross revenue	$35,620
Management (18%)	−$6,412
OTA commissions (assume 70% of bookings via OTA at 18%)	−$4,490
CAM (planning)	−$1,200
Withholding tax placeholder (15% of gross)	−$5,343
Net (before major repairs & insurance)	~$18,175

Net yield ≈ 9.1% in this purely illustrative spreadsheet. Change occupancy to 60% and net revenue collapses—showing why sensitivity analysis matters.

Sensitivity table: occupancy vs net (same ADR, simplified)

Occupancy	Gross revenue (ADR $130)	Net (same simplified deductions)
60%	$28,470	Lower
75%	$35,620	Mid
80%	$37,960	Higher

What investors get wrong (most common mistakes)

• Using peak ADR as the year average
• Ignoring OTA commissions because “we will go direct” (you will not on day one)
• Underestimating CAM in luxury buildings
• Confusing gross yield with net cash flow
• Assuming Kamala 8–10% or Patong 8–12% without verifying comps in the same building

The “sanity check” questions

Ask:

1. What would have to be true for this model to work?
2. What evidence supports that ADR and occupancy?
3. What happens in low season if ADR drops 35%?

If you cannot answer with data, do not buy.

Insurance, repairs, and furnishing reserves (often forgotten)

Even strong gross revenue can disappear when you ignore “non-monthly” costs. A practical annual plan includes:

• Insurance appropriate for rental use (not owner-occupier assumptions)
• AC service and periodic replacements (humidity is relentless)
• Furniture refresh every few years (mattresses, sofas, linens)
• Minor repairs after guest damage (even good guests break things)

Reserve idea	Planning approach
Maintenance	1–3% of property value / year (rule of thumb)
Furnishing refresh	Set aside a % of gross revenue annually

This is why 7–9% gross yields are not 7–9% spendable—net cash flow is lower after real life.

Mortgages and FX: stress-test the debt layer

If you finance, model interest rate changes and currency moves explicitly. A property priced in THB with income in USD can feel stable until repayment assumptions shift. Debt service does not care about your peak-season ADR.

Long-term vs short-stay: different comp sets

If you might switch strategies, build two models:

• Short-stay: higher gross, higher fees, higher workload
• Long-term: lower gross yield (often 5–7% gross), lower OTA friction, fewer turnovers

The “right” strategy depends on building rules, personal use plans, and management quality.

Fee stack scenarios: why range matters

Scenario	Management	OTA share	Net outcome
OTA-heavy start	18%	75% of bookings	Lower net until optimising
Balanced	18%	50%	Mid
Direct-heavy mature	15%	30%	Higher net, but earned over time

How MORE Group thinks about this

We prefer conservative underwriting that survives stress tests. If you want a shortlist aligned to real comps and real fee stacks, we will challenge optimistic assumptions—because Phuket already rewards disciplined buyers.

Frequently Asked Questions

What occupancy should I use for Phuket short-stay modelling? +

Start with evidence from comps. Many well-managed units are modelled around 70–80% annually; weaker operations should use 50–60% until proven otherwise.

Are CAM fees really around $1,200 per year? +

It can be a reasonable placeholder for quick modelling, but luxury projects can exceed $2,000/year. Always verify the developer schedule for your exact unit.

Is 15% withholding tax accurate for everyone? +

No. It is a common planning placeholder, but tax outcomes depend on structure and rules. Always confirm with a Thai accountant before purchase.

How do I estimate OTA commissions if I do not know channel mix yet? +

Assume a high OTA share early (60–80% of bookings) with 15–20% commission rates, then improve net as direct repeat grows.

Can I trust developer yield projections? +

Treat them as marketing until verified. Cross-check against independent comps and apply haircuts to ADR and occupancy.

Related Guides

• Phuket rental yield guide — Gross vs net yields, fees, and benchmarks.
• What affects occupancy rates in Phuket — Operational levers behind occupancy.
• Capital growth vs cash flow in Phuket — Choose the right strategy for your goals.