The spreadsheet was never the problem. The inputs were.
A model is only as honest as the numbers you feed it — and that’s exactly where a property deal goes wrong.
Almost every serious buyer builds a spreadsheet. It’s the right instinct: force the deal to prove itself in numbers before you fall for the photos. The trouble isn’t the maths — a yield, a cash-on-cash return, a break-even are all one formula each. The trouble is that a spreadsheet believes whatever you type into it.
And what you type is usually the asking price, an optimistic rent, and costs you half-remember. Get those three wrong and a beautiful model hands you a confident, precise, wrong answer — which is worse than no answer, because now you trust it.
Where the numbers come from is the whole game
The output of any property model lives or dies on three inputs: what you’ll really pay, what it will really rent for, and the true round-trip cost of owning it. A spreadsheet can’t source any of those — it waits for you to guess. DealPilot AI fills them from real, dated market data: the actual sale prices and rents for that size of flat in that city, refreshed monthly, with the transfer taxes, agent fees and running costs modelled per country rather than penciled in as “≈ 10%”.
That’s the difference between a model that looks rigorous and one that’s actually anchored to the market you’re buying in.
A worked example: watch two honest cells sink the deal
Take a round-number example — not a real listing, just to show the mechanics. A €200,000 flat you expect to rent for €1,000 a month. Type those into a spreadsheet and it reports €12,000 a year on €200,000: a 6% gross yield. On that line alone you buy.
Now feed it the two things the spreadsheet couldn’t know. First, the real market rent for that size of flat in that city turns out to be €850, not €1,000 — you were optimistic by 15%, which is completely normal. Second, the true cost of owning it — management, insurance, maintenance, the local property tax, void periods — eats roughly a third of the rent. Suddenly the €12,000 is €10,200 of rent, minus about €3,400 of costs, on a purchase that actually cost €214,000 once you add transfer tax and fees. The 6% headline is really about 3.2% net. Same spreadsheet, same formulas — two honest inputs turned a clear buy into a shrug.
That is the whole trap: the maths never lied. The inputs did. And the two inputs that move the answer most — real rent and real all-in cost — are exactly the two a blank spreadsheet leaves you to invent.
One property, four strategies, in seconds
The honest version of a spreadsheet isn’t one tab — it’s four: long-let, short-let, a flip, and the hotel/serviced angle, each with its own costs, risks and financing. Almost nobody builds all four, so most people quietly optimise for the strategy they already wanted. DealPilot AI runs the property through all of them and tells you which one the numbers actually support — and when the answer is “none of them, walk away.”
The takeaway isn’t “spreadsheets are bad.” It’s that a model is a calculator, not a source. Keep the calculator; stop asking it to also be your data, your local tax code, and your discipline about optimistic rent.
- It uses your asking price, not the real sale price the market is paying.
- It trusts an optimistic rent instead of the real one for that size and city.
- Round-trip costs get rounded to a guess, not modelled per country.
- It quietly flatters the strategy you already wanted to buy.
- It never tells you to walk away.
The shortcuts, defined
Why isn’t a spreadsheet enough to analyse a rental property?
A spreadsheet does the maths but sources none of the numbers — it returns whatever price, rent and costs you type in. The answer is only as honest as those inputs, and the two that move it most (real market rent and true all-in cost of ownership) are exactly the ones a blank spreadsheet leaves you to guess. A precise, confident, wrong answer is worse than none, because you trust it.
What inputs does a property investment calculation actually need?
Three real numbers decide the outcome: the price you’ll genuinely pay (usually below asking), the rent that size of flat truly commands in that city, and the full round-trip cost of owning and eventually selling — purchase tax and fees in, operating and income costs while you hold, selling cost out. Get those from the market rather than from memory and the formulas take care of themselves.
What is the difference between asking price and the real sale price?
The asking price is what a seller lists; the sale price is what buyers actually pay after negotiation, and it’s often several percent lower. Modelling a deal on the asking price quietly understates your yield and overstates the price you can resell at. Anchoring to real, dated transaction and listing data — not the headline number — is what makes the rest of the calculation trustworthy.
How much can an optimistic rent assumption distort a yield?
A lot, because yield scales directly with rent. Overestimating rent by 15% overstates gross yield by roughly 15%, and because most operating costs are fixed in euros rather than a percentage of rent, the hit to net yield is proportionally larger. Being wrong about rent by 10–20% is completely normal, which is why a serious model stress-tests the rent instead of taking the first optimistic figure.
Should I stop using a spreadsheet to underwrite property?
No — a spreadsheet is a fine calculator. The point is that a calculator is not a data source. Keep the model, but feed it the real sale price, the real market rent for that flat size and city, and country-specific round-trip costs rather than a “≈ 10%” placeholder. The formula was never the weak link; the invented inputs were.
Keep the spreadsheet if you love it. Just feed it real numbers — or paste the listing and let DealPilot AI build the honest version in 60 seconds.
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