Two Quotes for a Website or App: How to Tell Which Is Fair

By Mackenzie Bowes · mackenzie@mackenziebowes.com · @_mackenziebowes on X

When two quotes for the same software are far apart, they may be pricing different jobs. Five checks put them on the same footing before you pay, plus a prompt to hand your AI with both quotes.

Two quotes for the same website or app can describe two different jobs. One can include hosting, a year of fixes and the code, while the other includes none of that and looks cheaper. Before you can tell which is fair, put them on the same footing. Five checks do that.

Why I wrote this

I read 601,111 opening messages that people sent to ChatGPT, from a public research dataset [1], looking for the moment someone decides to pay for something. 615 of the messages were that kind of decision. When a person named what would decide it, price came first, in 48% of them. Among the people deciding whether to hire someone, the same request kept coming back: here are two quotes, which one, and what should I offer? [2]

Below are three of those situations, paraphrased with the details changed:

• A shop owner has two quotes to build a business site. One is more than twice the other, and the dearer firm keeps calling for a decision.
• A founder asks what it should cost to have a developer build a website for a small business, before asking anyone.
• An operator weighs a vendor's fee against what they can spend, and wants to know what to counter with.

Few said what worried them: only 6% of the 615 did. The worry shows up later, after the money is gone.

The five checks

1. Is it the same scope? Ask each firm for a written list of what you get: pages, features, the systems it connects to, who writes the words, how many rounds of changes. Then ask both to price the same list. Whatever gap is left is the real one.

2. Is it broken into lines? One number hides how it was built. Ask for line items with hours and a rate, or a price per piece. Also ask which kind of quote it is. A fixed price puts the risk of overruns on the builder. Time and materials puts it on you, so it needs a ceiling.

3. What isn't included? The usual gaps are hosting, the domain, email, paid plugins or app store fees, content, photos, a support period after launch, and changes after sign-off. Ask each firm to list what it won't do, because a cheaper quote can move these costs back onto you once the work has started and you can no longer walk away easily.

4. Who will own the code? In the US, custom software made by a contractor is a "work made for hire" only in narrow cases, and only with a signed written agreement that says so [3]. Otherwise the person who wrote it is its author. If you want to own it, the contract has to give it to you in writing. Outside the US, check your own country's rules. This isn't legal advice.

5. How do you pay? Tie payments to things you can see working, such as a first version you can click through, then the launch, then the end of the support period, so that each payment buys something you have checked. Be careful with a quote that wants most of the money before you've seen anything run.

A prompt for your AI

People already paste quotes into an AI and ask which is better. Ask it to do the checks instead:

Here are two quotes for the same project. For each one, list: the deliverables, the line items with hours and rates, fixed price or time and materials, what is excluded, who owns the code, and the payment schedule. Mark anything a quote doesn't say as "not stated". Then show the costs only for the work both quotes cover, and list the questions I should send each firm before I choose.

"Not stated" is the useful part. Usually the gaps are what you need to ask about, not the prices.

What I expect, and how I'll check

I've sealed a prediction for this page. In the 14 days to 2026-10-31, it will get more visits from AI agents and more ChatGPT referrals than the median post on this site, and at least one email will mention it. I count agents and referrals at the edge with my own counter, which keeps totals and no IP addresses. I'll post the result here either way.

Method and limits

The dataset is real conversations people chose to share with researchers in return for free access, not a sample of business owners. A keyword filter picked 10,845 candidates. A model labelled each one, after it found 6 of 7 spend decisions with no false alarms in 70 messages I had labelled by hand [2]. 615 is a floor: the filter misses phrasings it doesn't know. One person checked the labels: me.

If you're holding two quotes for a website or app right now, I'd like to see where they differ. Send them along with what you're trying to build.