Free PPC

Toolkit

The Problem This Solves

Sudden drops are easy to spot. Gradual declines, a 2% CPA increase per week over 6 weeks, go unnoticed until you’ve wasted thousands. This agent catches them early.

var CONFIG = {
  // ═══════════════════════════════════════════════════════════════════════════
  // DETECTION SETTINGS
  // ═══════════════════════════════════════════════════════════════════════════
  RECENT_WINDOW: 7,           // Days for "current" performance
  BASELINE_WINDOW: 30,        // Days for baseline comparison
  MIN_CONVERSIONS: 5,         // Skip campaigns with too few conversions

  // Thresholds (percentage change to trigger alert)
  THRESHOLDS: {
    CPA_INCREASE: 20,         // CPA up 20%+ vs baseline
    CONV_RATE_DROP: 15,       // Conv rate down 15%+ vs baseline
    CTR_DROP: 20,             // CTR down 20%+ vs baseline
    ROAS_DROP: 20,            // ROAS down 20%+ vs baseline
  },

  // ═══════════════════════════════════════════════════════════════════════════
  // NOTIFICATIONS
  // ═══════════════════════════════════════════════════════════════════════════
  EMAIL_RECIPIENTS: [],
  SLACK_WEBHOOK_URL: '',
  SPREADSHEET_URL: 'CREATE_NEW',
};

function main() {
  var recent = getPeriodData(CONFIG.RECENT_WINDOW);
  var baseline = getPeriodData(CONFIG.BASELINE_WINDOW);
  var alerts = [];

  Object.keys(recent).forEach(function(campaign) {
    var r = recent[campaign];
    var b = baseline[campaign];
    if (!b || b.conversions < CONFIG.MIN_CONVERSIONS) return;

    var checks = [];

    // CPA check
    if (r.conversions > 0 && b.conversions > 0) {
      var cpaCurrent = r.cost / r.conversions;
      var cpaBaseline = b.cost / b.conversions;
      var cpaChange = ((cpaCurrent - cpaBaseline) / cpaBaseline) * 100;
      if (cpaChange >= CONFIG.THRESHOLDS.CPA_INCREASE) {
        checks.push({
          metric: 'CPA',
          baseline: '$' + cpaBaseline.toFixed(2),
          current: '$' + cpaCurrent.toFixed(2),
          change: '+' + cpaChange.toFixed(1) + '%',
          severity: cpaChange >= CONFIG.THRESHOLDS.CPA_INCREASE * 2 ? 'high' : 'medium',
        });
      }
    }

    // Conversion rate check
    if (r.clicks > 50 && b.clicks > 50) {
      var crCurrent = r.conversions / r.clicks * 100;
      var crBaseline = b.conversions / b.clicks * 100;
      var crChange = ((crBaseline - crCurrent) / crBaseline) * 100;
      if (crChange >= CONFIG.THRESHOLDS.CONV_RATE_DROP) {
        checks.push({
          metric: 'Conv. Rate',
          baseline: crBaseline.toFixed(2) + '%',
          current: crCurrent.toFixed(2) + '%',
          change: '-' + crChange.toFixed(1) + '%',
          severity: crChange >= CONFIG.THRESHOLDS.CONV_RATE_DROP * 2 ? 'high' : 'medium',
        });
      }
    }

    // CTR check
    if (r.impressions > 100 && b.impressions > 100) {
      var ctrCurrent = r.clicks / r.impressions * 100;
      var ctrBaseline = b.clicks / b.impressions * 100;
      var ctrChange = ((ctrBaseline - ctrCurrent) / ctrBaseline) * 100;
      if (ctrChange >= CONFIG.THRESHOLDS.CTR_DROP) {
        checks.push({
          metric: 'CTR',
          baseline: ctrBaseline.toFixed(2) + '%',
          current: ctrCurrent.toFixed(2) + '%',
          change: '-' + ctrChange.toFixed(1) + '%',
          severity: 'medium',
        });
      }
    }

    if (checks.length > 0) {
      alerts.push({ campaign: campaign, issues: checks });
    }
  });

  if (alerts.length > 0) {
    logResults(alerts);
    sendNotifications(alerts);
  }

  Logger.log('Done. ' + alerts.length + ' campaigns with degradation detected.');
}

function getPeriodData(days) {
  var end = new Date();
  var start = new Date();
  start.setDate(start.getDate() - days);

  var fmt = function(d) {
    return Utilities.formatDate(d, AdsApp.currentAccount().getTimeZone(), 'yyyyMMdd');
  };

  var query = 'SELECT CampaignName, Impressions, Clicks, Cost, Conversions ' +
    'FROM CAMPAIGN_PERFORMANCE_REPORT ' +
    'WHERE CampaignStatus = ENABLED ' +
    'DURING ' + fmt(start) + ',' + fmt(end);

  var rows = AdsApp.report(query).rows();
  var data = {};

  while (rows.hasNext()) {
    var row = rows.next();
    var name = row['CampaignName'];
    if (!data[name]) {
      data[name] = { impressions: 0, clicks: 0, cost: 0, conversions: 0 };
    }
    data[name].impressions += parseInt(row['Impressions']);
    data[name].clicks += parseInt(row['Clicks']);
    data[name].cost += parseFloat(row['Cost']);
    data[name].conversions += parseFloat(row['Conversions']);
  }

  return data;
}

function logResults(alerts) {
  var ss;
  if (CONFIG.SPREADSHEET_URL === 'CREATE_NEW') {
    ss = SpreadsheetApp.create('Performance Trends — ' + new Date().toISOString().split('T')[0]);
  } else {
    ss = SpreadsheetApp.openByUrl(CONFIG.SPREADSHEET_URL);
  }

  var sheet = ss.getActiveSheet();
  if (sheet.getLastRow() === 0) {
    sheet.appendRow(['Date', 'Campaign', 'Metric', 'Baseline', 'Current', 'Change', 'Severity']);
  }

  var today = new Date().toISOString().split('T')[0];
  alerts.forEach(function(a) {
    a.issues.forEach(function(i) {
      sheet.appendRow([today, a.campaign, i.metric, i.baseline, i.current, i.change, i.severity]);
    });
  });
}

function sendNotifications(alerts) {
  var totalIssues = alerts.reduce(function(sum, a) { return sum + a.issues.length; }, 0);
  var subject = 'Performance Alert: ' + totalIssues + ' degradations in ' + alerts.length + ' campaigns';

  var body = alerts.map(function(a) {
    var lines = a.campaign + ':';
    a.issues.forEach(function(i) {
      lines += '\n  [' + i.severity.toUpperCase() + '] ' + i.metric +
        ' ' + i.baseline + ' → ' + i.current + ' (' + i.change + ')';
    });
    return lines;
  }).join('\n\n');

  CONFIG.EMAIL_RECIPIENTS.forEach(function(email) {
    MailApp.sendEmail(email, subject, body);
  });

  if (CONFIG.SLACK_WEBHOOK_URL) {
    UrlFetchApp.fetch(CONFIG.SLACK_WEBHOOK_URL, {
      method: 'post',
      contentType: 'application/json',
      payload: JSON.stringify({ text: '*' + subject + '*\n```\n' + body + '\n```' }),
    });
  }
}

What It Detects

Why 7 vs 30?

A 7-day window is long enough to smooth daily variance but short enough to catch trends within 1-2 weeks. The 30-day baseline represents “normal” performance. If 7-day metrics diverge from the 30-day norm, something changed.