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Google-Ads-SQL-Analysis-

Overview

This project analyzes ad campaign performance using SQL queries:

  • CTR (Click-through rate) by campaign
  • ROI by campaign
  • Conversion rate by region & device
  • CPC & CPA by device

Database Schema

  • campaigns (campaign_id, name, impressions, clicks, conversions, cost, device, region, ad_group)

Example Query

SELECTc.campaign_name,
ROUND(SUM(p.clicks) *100.0/ NULLIF(SUM(p.impressions),0), 2) AS ctr_pct
FROM campaigns c
JOIN ad_groups a ONc.campaign_id=a.campaign_idJOIN performance p ONa.ad_group_id=p.ad_group_idGROUP BYc.campaign_nameORDER BY ctr_pct DESC;

About

## Overview This project analyzes ad campaign performance using **SQL queries**: - CTR (Click-through rate) by campaign - ROI by campaign - Conversion rate by region & device - CPC & CPA by device

Topics

data-analysissql

Resources

Readme
Activity

Stars

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0 watching

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Add copy buttons to all 
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(function() {
function addCopyButtons() {
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try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '
GitHub - Ahadxcode/Google-Ads-SQL-Analysis-: ## Overview This project analyzes ad campaign performance using **SQL queries**: - CTR (Click-through rate) by campaign - ROI by campaign - Conversion rate by region & device - CPC & CPA by device · GitHub
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Repository files navigation
Google-Ads-SQL-Analysis-
Overview
This project analyzes ad campaign performance using SQL queries:
  • CTR (Click-through rate) by campaign
  • ROI by campaign
  • Conversion rate by region & device
  • CPC & CPA by device
Database Schema
  • campaigns (campaign_id, name, impressions, clicks, conversions, cost, device, region, ad_group)
Example Query
SELECTc.campaign_name,
ROUND(SUM(p.clicks) *100.0/ NULLIF(SUM(p.impressions),0), 2) AS ctr_pct
FROM campaigns c
JOIN ad_groups a ONc.campaign_id=a.campaign_idJOIN performance p ONa.ad_group_id=p.ad_group_idGROUP BYc.campaign_nameORDER BY ctr_pct DESC;
About
## Overview This project analyzes ad campaign performance using **SQL queries**: - CTR (Click-through rate) by campaign - ROI by campaign - Conversion rate by region & device - CPC & CPA by device
Topics
data-analysissql
Resources
Readme
Activity
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, 'i');
if (__m === '*' || __re.test(location.href)) {
// Force GitHub README to respect dark mode
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var style = document.createElement('style');
style.textContent = '
.markdown-body {
color-scheme: dark light;
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(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - Ahadxcode/Google-Ads-SQL-Analysis-: ## Overview This project analyzes ad campaign performance using **SQL queries**: - CTR (Click-through rate) by campaign - ROI by campaign - Conversion rate by region & device - CPC & CPA by device · GitHub
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Repository files navigation
Google-Ads-SQL-Analysis-
Overview
This project analyzes ad campaign performance using SQL queries:
  • CTR (Click-through rate) by campaign
  • ROI by campaign
  • Conversion rate by region & device
  • CPC & CPA by device
Database Schema
  • campaigns (campaign_id, name, impressions, clicks, conversions, cost, device, region, ad_group)
Example Query
SELECTc.campaign_name,
ROUND(SUM(p.clicks) *100.0/ NULLIF(SUM(p.impressions),0), 2) AS ctr_pct
FROM campaigns c
JOIN ad_groups a ONc.campaign_id=a.campaign_idJOIN performance p ONa.ad_group_id=p.ad_group_idGROUP BYc.campaign_nameORDER BY ctr_pct DESC;
About
## Overview This project analyzes ad campaign performance using **SQL queries**: - CTR (Click-through rate) by campaign - ROI by campaign - Conversion rate by region & device - CPC & CPA by device
Topics
data-analysissql
Resources
Readme
Activity
Stars
0 stars
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0 watching
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0 forks
Report repository
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, 'i');
if (__m === '*' || __re.test(location.href)) {
// Highlight search terms from Google/DuckDuckGo/Bing referrer
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var ref = document.referrer;
var terms = [];
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observer.observe(document.body, { childList: true, subtree: true });
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} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - Ahadxcode/Google-Ads-SQL-Analysis-: ## Overview This project analyzes ad campaign performance using **SQL queries**: - CTR (Click-through rate) by campaign - ROI by campaign - Conversion rate by region & device - CPC & CPA by device · GitHub
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Repository files navigation
Google-Ads-SQL-Analysis-
Overview
This project analyzes ad campaign performance using SQL queries:
  • CTR (Click-through rate) by campaign
  • ROI by campaign
  • Conversion rate by region & device
  • CPC & CPA by device
Database Schema
  • campaigns (campaign_id, name, impressions, clicks, conversions, cost, device, region, ad_group)
Example Query
SELECTc.campaign_name,
ROUND(SUM(p.clicks) *100.0/ NULLIF(SUM(p.impressions),0), 2) AS ctr_pct
FROM campaigns c
JOIN ad_groups a ONc.campaign_id=a.campaign_idJOIN performance p ONa.ad_group_id=p.ad_group_idGROUP BYc.campaign_nameORDER BY ctr_pct DESC;
About
## Overview This project analyzes ad campaign performance using **SQL queries**: - CTR (Click-through rate) by campaign - ROI by campaign - Conversion rate by region & device - CPC & CPA by device
Topics
data-analysissql
Resources
Readme
Activity
Stars
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0 forks
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, 'i');
if (__m === '*' || __re.test(location.href)) {
// Strip utm_, fbclid, gclid, etc. from all links on page
(function() {
var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',
'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',
'ref', 'ref_src', 'source', 'medium', 'campaign'];
function cleanUrl(url) {
try {
var u = new URL(url, window.location.origin);
var changed = false;
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if (u.searchParams.has(p)) {
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});
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});
observer.observe(document.body, { childList: true, subtree: true });
})();
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} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '
GitHub - Ahadxcode/Google-Ads-SQL-Analysis-: ## Overview This project analyzes ad campaign performance using **SQL queries**: - CTR (Click-through rate) by campaign - ROI by campaign - Conversion rate by region & device - CPC & CPA by device · GitHub
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conversion-rate.png
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queries.sql
Repository files navigation
Google-Ads-SQL-Analysis-
Overview
This project analyzes ad campaign performance using SQL queries:
  • CTR (Click-through rate) by campaign
  • ROI by campaign
  • Conversion rate by region & device
  • CPC & CPA by device
Database Schema
  • campaigns (campaign_id, name, impressions, clicks, conversions, cost, device, region, ad_group)
Example Query
SELECTc.campaign_name,
ROUND(SUM(p.clicks) *100.0/ NULLIF(SUM(p.impressions),0), 2) AS ctr_pct
FROM campaigns c
JOIN ad_groups a ONc.campaign_id=a.campaign_idJOIN performance p ONa.ad_group_id=p.ad_group_idGROUP BYc.campaign_nameORDER BY ctr_pct DESC;
About
## Overview This project analyzes ad campaign performance using **SQL queries**: - CTR (Click-through rate) by campaign - ROI by campaign - Conversion rate by region & device - CPC & CPA by device
Topics
data-analysissql
Resources
Readme
Activity
Stars
0 stars
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0 watching
Forks
0 forks
Report repository
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, 'i');
if (__m === '*' || __re.test(location.href)) {
// Auto-enable theater mode on YouTube
(function() {
function tryTheater() {
var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]');
if (btn && !btn.classList.contains('activated')) {
btn.click();
}
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// Try immediately
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})();
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - Ahadxcode/Google-Ads-SQL-Analysis-: ## Overview This project analyzes ad campaign performance using **SQL queries**: - CTR (Click-through rate) by campaign - ROI by campaign - Conversion rate by region & device - CPC & CPA by device · GitHub
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README.md
conversion-rate.png
conversion-rate.png
queries.sql
queries.sql
Repository files navigation
Google-Ads-SQL-Analysis-
Overview
This project analyzes ad campaign performance using SQL queries:
  • CTR (Click-through rate) by campaign
  • ROI by campaign
  • Conversion rate by region & device
  • CPC & CPA by device
Database Schema
  • campaigns (campaign_id, name, impressions, clicks, conversions, cost, device, region, ad_group)
Example Query
SELECTc.campaign_name,
ROUND(SUM(p.clicks) *100.0/ NULLIF(SUM(p.impressions),0), 2) AS ctr_pct
FROM campaigns c
JOIN ad_groups a ONc.campaign_id=a.campaign_idJOIN performance p ONa.ad_group_id=p.ad_group_idGROUP BYc.campaign_nameORDER BY ctr_pct DESC;
About
## Overview This project analyzes ad campaign performance using **SQL queries**: - CTR (Click-through rate) by campaign - ROI by campaign - Conversion rate by region & device - CPC & CPA by device
Topics
data-analysissql
Resources
Readme
Activity
Stars
0 stars
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0 watching
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0 forks
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, 'i');
if (__m === '*' || __re.test(location.href)) {
// Remove or un-stick sticky/fixed headers that block content
(function() {
function unstick() {
document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) {
if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {
el.style.position = 'static';
el.style.top = 'auto';
el.style.zIndex = 'auto';
}
});
}
unstick();
var observer = new MutationObserver(unstick);
observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });
})();
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - Ahadxcode/Google-Ads-SQL-Analysis-: ## Overview This project analyzes ad campaign performance using **SQL queries**: - CTR (Click-through rate) by campaign - ROI by campaign - Conversion rate by region & device - CPC & CPA by device · GitHub
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README.md
conversion-rate.png
conversion-rate.png
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queries.sql
Repository files navigation
Google-Ads-SQL-Analysis-
Overview
This project analyzes ad campaign performance using SQL queries:
  • CTR (Click-through rate) by campaign
  • ROI by campaign
  • Conversion rate by region & device
  • CPC & CPA by device
Database Schema
  • campaigns (campaign_id, name, impressions, clicks, conversions, cost, device, region, ad_group)
Example Query
SELECTc.campaign_name,
ROUND(SUM(p.clicks) *100.0/ NULLIF(SUM(p.impressions),0), 2) AS ctr_pct
FROM campaigns c
JOIN ad_groups a ONc.campaign_id=a.campaign_idJOIN performance p ONa.ad_group_id=p.ad_group_idGROUP BYc.campaign_nameORDER BY ctr_pct DESC;
About
## Overview This project analyzes ad campaign performance using **SQL queries**: - CTR (Click-through rate) by campaign - ROI by campaign - Conversion rate by region & device - CPC & CPA by device
Topics
data-analysissql
Resources
Readme
Activity
Stars
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0 watching
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0 forks
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, 'i');
if (__m === '*' || __re.test(location.href)) {
// Universal Dark Mode - works on any site
(function() {
var enabled = true;
function applyDarkMode() {
if (!enabled) return;
// Create style element if it doesn't exist
var style = document.getElementById('universal-dark-mode-style');
if (!style) {
style = document.createElement('style');
style.id = 'universal-dark-mode-style';
document.head.appendChild(style);
}
// Dark mode CSS - inverts colors but preserves images/video
style.textContent = '
/* Invert everything except media */
html {
filter: invert(1) hue-rotate(180deg) !important;
background: #1a1a2e !important;
}
/* Restore images, videos, iframes, canvas */
img, video, iframe, canvas, svg, picture, [style*="background-image"] {
filter: invert(1) hue-rotate(180deg) !important;
}
/* Preserve specific elements that should not be inverted */
.no-dark-mode, .no-dark-mode *,
[data-theme="light"], [data-theme="light"],
.ace_editor, .ace_editor *,
.CodeMirror, .CodeMirror *,
.monaco-editor, .monaco-editor *,
.markdown-body pre, .markdown-body pre *,
.highlight, .highlight *,
pre code, pre code * {
filter: none !important;
}
/* Fix common UI elements */
.modal, .popup, .dropdown-menu, .tooltip, .popover {
filter: invert(1) hue-rotate(180deg) !important;
background: #2d2d44 !important;
border-color: #444 !important;
}
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::-webkit-scrollbar { background: #1a1a2e !important; }
::-webkit-scrollbar-thumb { background: #444 !important; }
::-webkit-scrollbar-thumb:hover { background: #555 !important; }
/* Selection */
::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
';
}
function removeDarkMode() {
var style = document.getElementById('universal-dark-mode-style');
if (style) style.remove();
}
// Toggle with Alt+Shift+D
document.addEventListener('keydown', function(e) {
if (e.altKey && e.shiftKey && e.key === 'D') {
e.preventDefault();
enabled = !enabled;
if (enabled) {
applyDarkMode();
console.log('[Universal Dark Mode] Enabled');
} else {
removeDarkMode();
console.log('[Universal Dark Mode] Disabled');
}
}
});
// Apply on load
applyDarkMode();
// Re-apply on dynamic content
var observer = new MutationObserver(function(mutations) {
if (enabled && !document.getElementById('universal-dark-mode-style')) {
applyDarkMode();
}
});
observer.observe(document.head, { childList: true });
console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');
})();
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();
GitHub - Ahadxcode/Google-Ads-SQL-Analysis-: ## Overview This project analyzes ad campaign performance using **SQL queries**: - CTR (Click-through rate) by campaign - ROI by campaign - Conversion rate by region & device - CPC & CPA by device · GitHub
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conversion-rate.png
conversion-rate.png
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queries.sql
Repository files navigation
Google-Ads-SQL-Analysis-
Overview
This project analyzes ad campaign performance using SQL queries:
  • CTR (Click-through rate) by campaign
  • ROI by campaign
  • Conversion rate by region & device
  • CPC & CPA by device
Database Schema
  • campaigns (campaign_id, name, impressions, clicks, conversions, cost, device, region, ad_group)
Example Query
SELECTc.campaign_name,
ROUND(SUM(p.clicks) *100.0/ NULLIF(SUM(p.impressions),0), 2) AS ctr_pct
FROM campaigns c
JOIN ad_groups a ONc.campaign_id=a.campaign_idJOIN performance p ONa.ad_group_id=p.ad_group_idGROUP BYc.campaign_nameORDER BY ctr_pct DESC;
About
## Overview This project analyzes ad campaign performance using **SQL queries**: - CTR (Click-through rate) by campaign - ROI by campaign - Conversion rate by region & device - CPC & CPA by device
Topics
data-analysissql
Resources
Readme
Activity
Stars
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