If you build sites or tools for small business clients, you've probably been asked "how much should I spend on Google Ads?" more than once. Most of the time the honest answer is "it depends," which is true but useless. So for one of my client-facing tools I built an actual calculator that turns that vague question into a real number range — and the logic behind it is simple enough that it's worth breaking down for anyone building similar tools.
The three-step model
The core idea is to work backward from the outcome the client actually wants, instead of forward from an arbitrary spend figure.
Step 1 — clicks needed. Divide the target number of monthly customers/leads by an assumed landing page conversion rate. If someone wants 20 leads a month and their page converts at 3%, they need roughly 667 clicks.
Step 2 — sector CPC. Multiply that click count by an industry-average cost-per-click range. This is the part people usually get wrong: CPC isn't a single number, it's an auction outcome, and it varies wildly by vertical. Legal, healthcare, and finance clients bid far more per click than e-commerce, because a single converted lead is worth much more downstream. E-commerce has volume but thinner margins, so CPC stays cheap by comparison.
Step 3 — cost per acquisition. Divide CPC by the conversion rate to get an estimated cost per customer. This is usually the number that actually changes a client's mind, more than the raw budget figure does.
Why a range, not a single number
CPC is an auction price, not a fixed rate — two businesses in the identical vertical can pay very different amounts depending on quality score, audience match, and how competitive their specific keywords are. Any tool that spits out one precise number is overpromising. Giving a realistic low-high band is more honest and, in practice, holds up better once the campaign is actually live.
Implementation notes
Nothing here needs to be complicated. A lookup table of sector → CPC range, a couple of form inputs (industry, target leads, landing page quality as a proxy for conversion rate), and the three formulas above are enough to produce a genuinely useful output. The part that takes the most care is calibrating the CPC ranges themselves — pulling realistic sector averages rather than guessing, and being upfront in the UI that this is a planning estimate, not a quote.
The three mistakes I see most often when businesses (or tools) get this wrong: setting a budget too low to let the algorithm exit its learning phase, comparing a highly competitive keyword against a low-competition sector's CPC, and assuming an optimistic conversion rate on a landing page that hasn't actually been optimized yet.
I put a free version of this live on my own site if you want to see the finished output rather than just the math: Google Ads Budget Calculator (Turkish-market focused, but the model itself is portable to any currency or region).
I run a small web design and digital marketing shop out of Istanbul (Laravel/PHP, technical SEO, Google Ads management) — more at resuloztas.com.
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