

Picture this: it is the last week of the month, your ad platforms are open in one tab, your CRM in another, invoices in a third. You know you should be tracking CAC, but instead you are copying costs into a spreadsheet at 11 p.m., hoping you didn’t miss a line item.A CAC calculator turns that chaos into a single source of truth. By pulling marketing, sales, and overhead costs together and dividing by new customers, you see instantly whether every new buyer is profitable or just expensive vanity. For founders, agencies, and performance marketers, CAC becomes the heartbeat of budget decisions, pricing, and which channels to scale or kill.Delegating the CAC calculator to an AI computer agent levels this up again. Instead of you chasing numbers, the agent logs into your ad dashboards, CRM, and billing tools, copies fresh data into Google Sheets or Excel, applies your formulas, and even snapshots trends. You keep the strategic control; the agent quietly handles the clicks, copy-paste, and sanity checks in the background.
You can calculate Customer Acquisition Cost with nothing more than a laptop and a spreadsheet. The question is: do you want to do it once, or do you want it to run every week without you touching a key?Below are the top ways to build and then scale your CAC calculator, from totally manual to fully automated with an AI agent.## 1. Manual CAC Calculation in Google SheetsThis is where most founders, marketers, and small agencies start.**Step-by-step:**1. List your time period: Decide if you are calculating CAC monthly, quarterly, or for a specific campaign.2. Create a costs tab: In Google Sheets, add a table with columns like: Cost type, Channel, Amount, Date, Notes.3. Add marketing costs: Fill in ad spend (Meta, Google, LinkedIn, etc.), content costs, tools, freelancers, agencies.4. Add sales costs: Include salaries, commissions, bonuses, sales tools, and travel related to acquiring customers.5. Add overhead allocation: If relevant, assign a percentage of shared costs (e.g., 20% of your CMO’s salary).6. Count new customers: In another tab, list customers acquired in that period, or simply put the total number in a cell.7. Apply the formula: In a summary cell: `CAC = (Total marketing costs + Total sales costs + Allocated overhead) / New customers`8. Visualize: Build a quick chart showing CAC trend over time by month or by channel.**Pros:**- Fully transparent and easy to audit.- Perfect for early-stage teams and simple funnels.**Cons:**- Manual data entry is time-consuming and error-prone.- Easy to forget a cost or mix time periods.## 2. Manual CAC in Excel With Deeper AnalysisExcel shines when finance, RevOps, or growth teams want more control.**Step-by-step:**1. Import raw data: Pull CSV exports from ad platforms and CRM, then use Excel tables for each source.2. Normalize columns: Align date formats, campaign names, and customer identifiers.3. Build a mapping sheet: Map campaigns and sales activities to channels (e.g., Paid Search, Paid Social, Partnerships).4. Use SUMIFS and pivot tables: Aggregate costs and customers by period and channel.5. Create scenarios: Add separate sheets for best-, base-, and worst-case CAC with different cost assumptions.**Pros:**- Strong for multi-scenario modeling and board-ready reports.- Pivot tables make deep channel analysis easy.**Cons:**- Still heavily manual to refresh each month.- People-dependent: if your Excel wizard leaves, the model often breaks.## 3. Semi-Automated CAC Using Spreadsheet ConnectorsBefore agents, many teams connect Google Sheets or Excel directly to tools.**How it works:**- Use connectors or add-ons to sync spend from ad platforms and new-customer counts from the CRM.- Schedule refreshes daily or weekly.- Keep your existing CAC formulas pointing to these live data ranges.**Pros:**- Less copy-paste, fresher data.- Still lives inside the spreadsheets your team already understands.**Cons:**- Connectors can be brittle when schemas change.- You still have to clean anomalies, reconcile dates, and check if numbers look off.## 4. Fully Automated CAC With an AI Computer AgentNow imagine the same CAC workflow, but instead of you doing the clicking, an AI agent behaves like a meticulous operations assistant.An AI computer agent powered by Simular can:- Open your browser and sign in to ad accounts, analytics tools, and your CRM.- Export or scrape spend and customer data for the specific period you care about.- Paste those numbers into the right Google Sheets or Excel templates.- Apply your CAC formulas, update charts, and save versions for the week or month.- Log its every action so you can see exactly what changed.**Pros:**- Frees hours every month for founders, marketers, and finance teams.- Production-grade reliability across thousands of steps.- Transparent execution: every edit is inspectable.**Cons:**- Requires a one-time setup and clear instructions.- Best results when you already have a clean base spreadsheet model.## 5. Hybrid: You Design the Logic, the Agent Runs the RoutineThe most effective pattern for agencies and scaling teams is hybrid:- You or your analyst designs the CAC logic, channel mapping, and dashboards once in Google Sheets or Excel.- The AI agent is then trained to do everything that feels like drudgery: logging into tools, collecting data, refreshing the model, and notifying you when CAC crosses a threshold.You keep the story and decisions; the agent owns the grunt work.## 6. When Should You Automate CAC?You are ready to hand CAC to an AI agent when:- You recalculate CAC at least monthly and touch multiple tools to do it.- You keep losing time or making mistakes copying data between tabs.- Your team needs CAC by segment, channel, or geography, and doing it manually would kill your week.If that sounds familiar, your next CAC improvement probably will not come from a clever new formula. It will come from no longer being the person who runs the calculator.
Start with one period, like last month. In Google Sheets or Excel, sum all sales and marketing costs tied to new customers: ad spend, sales salaries, tools, and agency fees. Then count how many new customers you acquired in that same period. Divide total costs by new customers to get CAC. Add a second column for the next month and repeat to track trends over time.
Create a table with each acquisition channel as a row: Paid Search, Paid Social, Email, Partnerships, etc. For each, sum its marketing and sales costs and the number of new customers it drove. Use one column for total cost, one for new customers, and a CAC column with cost divided by customers. Add another column for revenue per customer so you can compare CAC to LTV and see which channels truly pay off.
For fast-moving startups and agencies, monthly is the minimum; weekly is ideal for paid-heavy acquisition. At a set cadence, refresh your spreadsheet with the latest ad spend, sales costs, and new customer counts. Review overall CAC, then drill into CAC by channel and campaign. Look for trends rather than single datapoints, and decide which tactics to scale, pause, or rework based on those shifts.
Use your CAC calculator as a lab. Filter by channel to find outliers with high CAC and low retention. Trim spend there and reinvest into channels with better CAC-to-LTV ratios. Improve funnel conversion by tightening ad targeting, refining offers, and fixing leaky steps (like slow follow-up). Recalculate CAC after each change so you see how actions affect cost per new customer in real time.
First, design a clean CAC template in Google Sheets or Excel. Then configure your AI agent with step-by-step instructions: log in to ad platforms and CRM, filter by date range, export or copy metrics, and paste them into the correct ranges. Have it run a test month and compare its output to your manual results. Once aligned, schedule it to update CAC regularly and send you a summary, while you keep final review control.