Estimate a cost per click campaign with ranges, not a single promise. Combine likely search demand, expected click share, CPC range and conversion assumptions, then compare the result with the business's acceptable cost per customer.
Define the scope precisely
List the location, language, schedule, network, product or service and the intentions you plan to target. A national campaign around broad research terms cannot use the same cost assumption as a local campaign around urgent purchase searches.
Build keyword themes rather than one giant list. Separate brand, high-intent category, comparison and exploratory demand so their costs and conversion expectations remain visible.
Collect planning inputs
Use Keyword Planner and any historical account data to create a CPC and volume range. Treat estimates as directional; live auctions, relevance, competition and budget settings will change delivery. Add assumptions for click-through rate, landing-page conversion, qualification and close rate.
Document the source and date for every input. A forecast becomes difficult to improve when nobody remembers which figures were observed and which were guessed.
Build three scenarios
For each scenario calculate:
Clicks = planned spend ÷ average CPC
Leads = clicks × landing-page conversion rate
Customers = leads × qualification rate × close rate
Cost per customer = planned spend ÷ customers
Use conservative, expected and optimistic assumptions. If the model only works in the optimistic case, the launch is not commercially ready.
Add operational costs and limits
Media is not the entire cost. Include creative, landing-page work, tracking, management and sales handling where relevant. Set an average daily budget, monthly ceiling and a stop condition for tracking failure or irrelevant traffic. Google's budget overview explains how average daily budgets relate to daily and monthly spending limits.
Turn the forecast into a test plan
Name what the first period must teach: actual CPC, search-term quality, page conversion and lead quality. Decide which assumptions will be replaced first with observed data. Forecasting is valuable because it makes the learning explicit, not because it predicts the invoice perfectly.
For the next step, use our Google Ads budget forecasting method. Digital Marketing in Practice develops these planning and measurement skills through practical campaign work.