new-term-radar
Daily radar for new AI terms: names of new models, products and repos, caught on X, Hugging Face, GitHub and sitemaps before keyword tools list them.
翻译准备中
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在项目文件夹中运行 /nomorevibe verify,即可验证所有权并自行管理介绍。
一分钟完成验证Google Ads ROI Calculator
翻译准备中
取自仓库 README
正在加载完整 README。 以下为已保存的摘录。
A production-ready web tool for account managers to estimate Google Ads revenue potential for clients based on industry, service mix, cost per lead, and close rate.
Open http://localhost:3000.
The calculator answers: If this client spends $X/month on Google Ads, and their close rate is Y%, and their average job value is $Z, then they can expect approximately $N/month in new revenue potential.
For multiple services, the budget is split by allocation percentages and each service is calculated separately, then summed.查看完整 README ↗A production-ready web tool for account managers to estimate Google Ads revenue potential for clients based on industry, service mix, cost per lead, and close rate.
npm install
npm run dev
Open http://localhost:3000.
The calculator answers: If this client spends $X/month on Google Ads, and their close rate is Y%, and their average job value is $Z, then they can expect approximately $N/month in new revenue potential.
leads/month = monthly ad spend / cost per lead
jobs/month = leads × close rate
revenue/month = jobs × average job value
For multiple services, the budget is split by allocation percentages and each service is calculated separately, then summed.
src/
app/
page.tsx # Main page (all state management)
layout.tsx # Root layout
globals.css # Global styles
components/
ClientInputs.tsx # Client name, industry, website text
ServiceSelection.tsx # Service checkboxes, CPL, job value per service
BudgetSalesInputs.tsx # Ad spend, close rate, rounding mode
Results.tsx # Results cards and per-service table
ExportSummary.tsx # Client-facing and internal summary export
lib/
types.ts # TypeScript type definitions
benchmarks.ts # Benchmark data access functions
calculations.ts # Core calculation engine + formatters
service-extraction.ts # Text-based service detection
data/
benchmarks.json # Seed benchmark dataset (EDIT THIS)
All seed data is placeholder. Before using with real clients, replace the values in src/data/benchmarks.json.
Each benchmark entry:
{
"industryId": "plumbing",
"industryName": "Plumbing",
"serviceName": "Drain Cleaning",
"cplLow": 20,
"cplMid": 40,
"cplHigh": 70,
"avgJobValue": 350,
"recommendedMinAdSpend": 800,
"recommendedTargetAdSpend": 1500,
"notes": "Source and rationale here",
"source": "Name of data source",
"confidence": "high"
}
confidence: "high", "medium", or "low" — displayed in the UInotes / source: shown to the AM as contextcplLow/Mid/High to null if unknown (the UI will prompt for manual entry)To add a new industry, add entries with a new industryId — the app picks them up automatically.
npm run build
npm start