Finding deals
Property deal analyser: spreadsheet vs app (and when each wins)
The money keyword, answered honestly: spreadsheets are good at this, right up until they aren't.
If you've searched for a property deal analyser, chances are what you actually want is a spreadsheet. Most UK investors run their numbers in Excel or Google Sheets, usually one they built themselves, usually held together by habit and a few formulas nobody has checked since 2021.
This isn't a lecture about why you should stop. Spreadsheets are genuinely good at this, and for plenty of investors they stay the right tool. But they fail in specific, predictable ways, and it's worth knowing exactly where that line sits before you spend money on software that might not fix anything.
What a deal analyser actually has to do
Strip away the branding and every deal analyser, spreadsheet or app, answers the same five questions:
- What's it worth done up? The end value after works, based on what comparable properties actually sold for.
- What will the works cost? The refurb priced realistically, not optimistically.
- What can I borrow, and what does it cost? Your mortgage or bridge, your rates, your fees.
- What will it rent for? Whole-property or by the room, from real local evidence.
- So what should I offer? The number that makes the deal work for your strategy, whether that's buy-to-let, a flip, or buy-refurbish-refinance.
Everything else is presentation.
Where the spreadsheet wins
You understand every number in it. That matters more than people admit. When your maximum offer comes out of a formula you wrote, you know exactly what it assumes. When it comes out of an app, you're trusting someone else's assumptions, and most apps never show you what they are.
It's yours. Your fees, your lender's terms, whether you self-manage: a spreadsheet holds your cost structure, not a national average that's wrong for you.
It's free, it works offline, and no subscription lapses the week you finally find a deal.
If you analyse a few deals a month and you work one postcode area you know intimately, then honestly, a good spreadsheet plus your own local knowledge is hard to beat. Anyone who tells you otherwise is selling something.
Where the spreadsheet fails
It fails at the edges: the places where the numbers come from, and where the results go.
The inputs are manual. Every comparable sale, every local rent, every sold price gets googled, judged and retyped. That's 20 to 40 minutes per deal before the spreadsheet does a thing. Do it at 11pm after work and the quality of what you type drops off a cliff, and the output is only ever as good as what went in.
It analyses one deal at a time. A spreadsheet can tell you whether this property stacks up. It can't tell you that a better one came back on the market this morning two streets away, or that a listing you dismissed in March has since been cut twice. Finding deals and analysing them live in different worlds, and the spreadsheet only lives in one of them.
Nothing follows up. The deal you analysed lives in a tab. The viewing you booked lives in your calendar. The offer you made lives in your sent items. Three weeks later, when the agent goes quiet, nothing nudges you, and the follow-up is where deals actually get done.
Formula rot is real. Stamp duty bands change. Cell references break the moment you insert a row. Most self-built analysers we've seen carry at least one silent error the owner stopped noticing years ago.
Where apps win, and where they overreach
A good app fixes the edges. Market data lands in the fields instead of being retyped, the analysis is tied to a pipeline that chases you about follow-ups, and the maths is kept current by someone whose job that is.
But be careful with the middle. Some tools now promise to work out your offer for you: an automatic valuation, a one-click "maximum price". Treat that with suspicion, because the two numbers that make or break a deal are exactly the ones no app can know:
- Your refurb cost. No algorithm has stood in the kitchen. Agent photos are framed to hide the very things that cost money.
- Your finance. Your rate, your fee structure, your deposit, whether you manage it yourself. Those are facts about you, not about the property.
An analyser that fills them in for you isn't being clever. It's guessing, confidently, about the two things it can't see, and the review pages of the big property-data tools are full of investors who learned that the expensive way.
The honest division of labour: the tool brings the market's numbers (sold prices, local rents, how long things sit, what's been cut), and you bring your numbers (works, lending, costs). Any product that reverses that has its incentives backwards.
The practical answer
- A few deals, one patch you know cold? Keep the spreadsheet. Just check the stamp duty bands are current, and set a calendar reminder to actually chase your offers.
- Analysing weekly, or comparing areas? The retyping is costing you real hours now, and the finding gap is costing you deals you never even saw. That's the point where software earns its fee.
- Either way, never trust a number you can't see the assumptions behind. That goes for your own spreadsheet from 2021 just as much as any app.
We're building BrickSift on exactly that division of labour. The market's numbers arrive in the fields (sold prices, local rents, price cuts, time on market), and the offer stays yours. Join the waitlist to get it first.