Pause and activate groups of campaigns, to test anything you like.

AB Testing.js

/**
* Brainlabs A/B Testing Tool with Statistical Relevance Calculator
*
* This script will pause and activate campaigns and shopping campaigns every hour.
* The script will calculate the statistical relevance of the results and email
* if a sufficient confidence is achieved.
*
* Version: 2.2
* AdWords script maintained on brainlabsdigital.com
**/
  
function main() {
  
  //~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
  //~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
  //~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
  
  //The A/B testing
  
  // Labels used for the Search/Display campaigns being tested
  // Leave as blank, "", to skip
  var campaignLabelA = "Control";
  var campaignLabelB = "Experiment";
  
  // Labels used for Shopping campaigns being tested
  // Leave as blank, "", to skip
  var shoppingLabelA = "Shopping Control";
  var shoppingLabelB = "Shopping Experiment";
  
  // The confidence levels at which to reject the null hypothesis for the trials
  // Set to a number between 0 and 1
  // We recommend 0.95
  var confidenceThreshold = 0.95;
  
  // Date range over which to take data for statistical relevance calculation
  // Choose from TODAY, YESTERDAY, LAST_7_DAYS, THIS_WEEK_SUN_TODAY, LAST_WEEK, LAST_14_DAYS,
  // LAST_30_DAYS, LAST_BUSINESS_WEEK, LAST_WEEK_SUN_SAT, THIS_MONTH, LAST_MONTH, ALL_TIME
  // To skip leave as "" and add in a start date below.
  var reportDate = "LAST_30_DAYS";
  
  // Rather than use a preset date range, give the start date for your experiment.
  // The script will make a date range starting on that day and ending on today.
  // Format is "yyyy-mm-dd". Leave as "" to skip.
  var startDate = "2015-10-01";
  
  // People who will be alerted when statistical significance is achieved
  // Separate multiple recipients with a comma
  // Leave blank, "", to skip sending emails
  var emailRecipients = "eve@example.com"; // e.g. "alice@example.com, bob@example.com"
  
  //~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
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  //~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
  
  if (reportDate == "") {
    reportDate = [startDate.replace(/-/g,""),Utilities.formatDate(new Date(), "UTC", "yyyyMMdd")];
    Logger.log("Using date range " + startDate + " to " + Utilities.formatDate(new Date(), "UTC", "yyyy-MM-dd"));
  } else {
    Logger.log("Using date range " + reportDate);
  }
  
  var campaignCTR = {
    campaignType: "campaigns",
    metricA: "Impressions",
    metricB: "Clicks",
    rateName: "CTR",
    testName: "campaign CTR",
    labelA: campaignLabelA,
    labelB: campaignLabelB,
    confidenceThreshold: confidenceThreshold,
    reportDate: reportDate,
  };
  
  var campaignConversionRate = {
    campaignType: "campaigns",
    metricA: "Clicks",
    metricB: "Conversions",
    rateName: "conversion rate",
    testName: "campaign conversion rate",
    labelA: campaignLabelA,
    labelB: campaignLabelB,
    confidenceThreshold: confidenceThreshold,
    reportDate: reportDate,
  };
  
  var shoppingCTR = {
    campaignType: "shoppingCampaigns",
    metricA: "Impressions",
    metricB: "Clicks",
    rateName: "CTR",
    testName: "shopping campaign CTR",
    labelA: shoppingLabelA,
    labelB: shoppingLabelB,
    confidenceThreshold: confidenceThreshold,
    reportDate: reportDate,
  };
  
  var shoppingConversionRate = {
    campaignType: "shoppingCampaigns",
    metricA: "Clicks",
    metricB: "Conversions",
    rateName: "conversion rate",
    testName: "shopping campaign conversion rate",
    labelA: shoppingLabelA,
    labelB: shoppingLabelB,
    confidenceThreshold: confidenceThreshold,
    reportDate: reportDate,
  };
  
  var objects = [campaignCTR, campaignConversionRate, shoppingCTR, shoppingConversionRate];
  
  //~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
  //~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
  //~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
  
  //date info
  var days = [31,28,31,30,31,30,31,31,30,31,30,31];
  
  var date = new Date();
  var timeZone = AdWordsApp.currentAccount().getTimeZone();
  var month = parseInt(Utilities.formatDate(date, timeZone, "MM"), 10) - 1;
  var dayOfMonth = parseInt(Utilities.formatDate(date, timeZone, "dd"), 10);
  var hour = parseInt(Utilities.formatDate(date, timeZone, "HH"), 10);
  var year = parseInt(Utilities.formatDate(date, timeZone, "YYYY"), 10);
  
  if(leapYear(year)) days[1] = 29;
  
  var totalDays = 0;
  
  for(var i = 0; i < month; i++){
    totalDays += days[i];
  }
  
  totalDays += dayOfMonth;
  
  Logger.log("Day of year: " + totalDays);
  
  Logger.log("hour: " + hour);
  
  //~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
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  //~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
  
  var campaignTypeArray = [];
  
  for(var i = 0; i < objects.length; i++){
    if(objects[i]['labelA'] !== '' && objects[i]['labelB'] !== ''){
      if(campaignTypeArray.indexOf(objects[i]['campaignType']) === -1){
        enable_pause(objects[i], totalDays, hour);
        campaignTypeArray.push(objects[i]['campaignType']);
      }
    }
  }
  
  //~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
  //~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
  //~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
  
  for (var i = 0; i < objects.length; i++) {
    if (objects[i]['confidenceThreshold'] >= 0 && objects[i]['confidenceThreshold'] <= 1) {
      if (objects[i]['labelA'] !== '' && objects[i]['labelB'] !== '') {
        objects[i]['results'] = allStats(objects[i]);
        objects[i]['confidenceLevelData'] = calculation(objects[i]['results']);
        objects[i]['confidenceLevel'] = objects[i]['confidenceLevelData']['confidence'];
        Logger.log("Experiment: " + objects[i]['testName'] + " Result: " + objects[i]['confidenceLevel']);
      }
    }
  }
  
  //~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
  //~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
  //~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
  
  var accountName = AdWordsApp.currentAccount().getName();
  var emailSubject = "AdWords - " + accountName + " - A/B test results";
  var emailBody = "The A/B tests in the AdWords account " + accountName + " have statistically significant results:\n\n\n";
  
  var trigger = 0;
  
  for (var i = 0; i < objects.length; i++) {
    if (objects[i].hasOwnProperty('confidenceLevel')) {
      if (objects[i]['confidenceLevel'] >= objects[i]['confidenceThreshold']) {
  
        trigger = 1;
  
        // Create properties for the campaign group with the better rate
        winnerStats(objects[i]);
  
        emailBody += "The test for " + objects[i]['testName'] + " shows statistically significant results. ";
        emailBody += "The null hypothesis - that the control and experiment have the same rate - can be rejected ";
        emailBody += "with " + percent(objects[i]['confidenceLevel'], 2) + " certainty. ";
  
        emailBody += "The winner is campaigns labelled with \"" + objects[i]['winner']['label'] + "\" which have ";
        emailBody += "a " + objects[i]['rateName'] + " of " + objects[i]['winner']['rate'] + ". ";
        emailBody += "The loser is campaigns labelled with \"" + objects[i]['loser']['label'] + "\" which have ";
        emailBody += "a " + objects[i]['rateName'] + " of " + objects[i]['loser']['rate'] + ".\n\n";
  
      }
    }
  }
  
  if(trigger === 1 && emailRecipients !== ''){
    MailApp.sendEmail(emailRecipients, emailSubject, emailBody);
  }
  
}
  
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
// Reporting functions
  
/**
* Returns stats for campaign experiment type
*
* @param object campaignExperiment the object housing the details
* @return object the results
*/
function allStats(object){
  
  var results = {};
  
  results['control'] = getStats(object, object['labelA']);
  results['experiment'] = getStats(object, object['labelB']);
  
  return results;
  
}
  
/**
* Returns stats for campaign experiment type
*
* @param object campaignExperiment the object housing the details
* @param object the results
* @return object the results
*/
function getStats(object, label){
  
  var campaignType = object['campaignType'];
  var date = object['reportDate'];
  var metricA = object['metricA'];
  var metricB = object['metricB'];
  
  var results = {
    metricA: 0,
    metricB: 0
  };
  
  var iterator = eval(objectIterator(campaignType, label));
  while(iterator.hasNext()){
    var object = iterator.next();
    if (typeof date == "object") {
      var stats = object.getStatsFor(date[0],date[1]);
    } else {
      var stats = object.getStatsFor(date);
    }
    results['metricA'] += eval("stats.get"+metricA+"();");
    results['metricB'] += eval("stats.get"+metricB+"();");
  }
  
  return results;
  
}
  
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
// Management functions
  
/**
* Determine which campaign group has a better rate once statistical significance has been established
*
* @param object campaignExperiment the object housing the details
*/
function winnerStats(campaignExperiment){
  
  var controlRate = campaignExperiment['results']['control']['metricB']/campaignExperiment['results']['control']['metricA'];
  var experimentRate = campaignExperiment['results']['experiment']['metricB']/campaignExperiment['results']['experiment']['metricA'];
  
  var controlRatePercent = percent(controlRate, 2);
  var experimentRatePercent = percent(experimentRate, 2);
  
  if(controlRate >= experimentRate){
    campaignExperiment['winner'] = {label: campaignExperiment['labelA'], rate: controlRatePercent};
    campaignExperiment['loser'] = {label: campaignExperiment['labelB'], rate: experimentRatePercent};
  }
  else{
    campaignExperiment['loser'] = {label: campaignExperiment['labelA'], rate: controlRatePercent};
    campaignExperiment['winner'] = {label: campaignExperiment['labelB'], rate: experimentRatePercent};
  }
  
}
  
/**
* Returns true if leap year, false otherwise
*
* @param int year the object housing the details
* @param boole is current year a leap year
*/
function leapYear(year){
  return ((year % 4 == 0) && (year % 100 != 0)) || (year % 400 == 0);
}
  
/**
* Will pause or enable campaigns based on labels
*
* @param object campaignExperiment the object housing the details
* @param int totalDays the number of days since Jan 1st
* @param int hour the hour of the day
*/
  
function enable_pause(campaignExperiment, totalDays, hour){
  
  var campaignType = campaignExperiment['campaignType'];
  var labelA = campaignExperiment['labelA'];
  var labelB = campaignExperiment['labelB'];
  
  if(totalDays % 2 === 0){
    if(hour % 2 === 0){
      EnableCampaigns(campaignType, labelA)
      PauseCampaigns(campaignType, labelB)
    }
    else{
      EnableCampaigns(campaignType, labelB)
      PauseCampaigns(campaignType, labelA)
    }
  }
  else{
    if(hour % 2 === 0){
      EnableCampaigns(campaignType, labelB)
      PauseCampaigns(campaignType, labelA)
    }
    else{
      EnableCampaigns(campaignType, labelA)
      PauseCampaigns(campaignType, labelB)
    }
  }
}
  
/**
* Produces string which can be passed to eval() to create an iterator object.
* Allows dynamic creation of iterators for different types of object.
*
* @param String campaignType the type of iterator to produce e.g "campaigns" or "shoppingCampaigns"
* @param String label for filtering
* @return String Correctly parsed AdWords iterator object
*/
function objectIterator(campaignType, label){
  
  var iterator = "AdWordsApp." + campaignType + "()";
  iterator += ".withCondition('LabelNames CONTAINS_ANY " + '["' + label + '"]' + "')";
  iterator += ".get();";
  
  return iterator;
  
}
  
/**
* Pause all campaigns of specific type which have a specific label
*
* @param String campaignType the type of campaign to change
* @param String label for filtering
*/
function PauseCampaigns(campaignType, label){
  var iterator = eval(objectIterator(campaignType, label));
  if (!iterator.hasNext()) {
    Logger.log("Warning: no " + campaignType + " found with the label '" + label + "'. No campaigns paused.");
  }
  while(iterator.hasNext()){
    var object = iterator.next();
    object.pause();
  }
}
  
/**
* Enable all campaigns of specific type which have a specific label
*
* @param String campaignType the type of campaign to change
* @param String label for filtering
*/
function EnableCampaigns(campaignType, label){
  var iterator = eval(objectIterator(campaignType, label));
  if (!iterator.hasNext()) {
    Logger.log("Warning: no " + campaignType + " found with the label '" + label + "'. No campaigns enabled.");
  }
  while(iterator.hasNext()){
    var object = iterator.next();
    object.enable();
  }
}
  
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
// Statistical analysis functions
  
/**
* Return a confidence level for rejecting the null hypothesis that the two sets of
* results are not statistically distinguishable. Takes an object of the form:
*
* var results = {
* control: {metricA: xxx, metricB: xxx},
* experiment: {metricA: xxx, metricB: xxx}
* }
*
* @param Object results the data to analyse
* @return Object outcome the confidence for rejecting null hypothesis
*/
function calculation(results){
  
  var e1a = results['control']['metricA'];
  var e1b = results['control']['metricB'];
  
  var e2a = results['experiment']['metricA'];
  var e2b = results['experiment']['metricB'];
  
  var e1r = e1b/e1a;
  var e2r = e2b/e2a;
  
  var p1_p2 = Math.abs(e1r-e2r);
  var p = (e1b+e2b)/(e1a+e2a);
  
  var se_p = Math.sqrt(p*(1-p)*((1/e1a)+(1/e2a)));
  
  var z = p1_p2/se_p;
  
  // The confidence for rejecting the null hypothesis
  var rejectNullConfidence = normDist(z);
  // The range of values at the null hypothesis rejection confience level
  var top = topInverse(rejectNullConfidence);
  var bottom = bottomInverse(rejectNullConfidence);
  
  var outcome = {confidence: rejectNullConfidence, top: top, bottom: bottom};
  
  return outcome;
  
  /**
  * Find the top and bottom limit of the range. Within parent function
  * scope to take advantage of closure. Referencing variables: p1_p2, se_p
  *
  * @param float cdf the number to parse as a percentage
  * @return string the range bound
  */
  function topInverse(cdf){
    return percent(p1_p2 + baseInverse(cdf) * se_p, 2);
  }
  function bottomInverse(cdf){
    return percent(p1_p2 - baseInverse(cdf) * se_p, 2);
  }
  
}
  
/**
* Parse number as percentage with dec digits after the decimal point
*
* @param float x the number to parse as a percentage
* @param int dec the number of digits after the decimal place
* @return string the parameter number parsed as a percentage string
*/
function percent(x, dec){
  return Math.round(x*100*Math.pow(10,dec))/Math.pow(10,dec) + "%";
}
  
/**
* The inverse of the CDF
*
* @param float cdf the CDF for the normal distribution
* @return float the CDF inverse
*/
// Inverse confidence level
function baseInverse(cdf){
  return normal_cdf_inverse(1-((1-cdf)/2));
}
  
// Source: http://picomath.org/javascript/normal_cdf_inverse.js.html
function rational_approximation(t) {
  // Abramowitz and Stegun formula 26.2.23.
  // The absolute value of the error should be less than 4.5 e-4.
  var c = [2.515517, 0.802853, 0.010328];
  var d = [1.432788, 0.189269, 0.001308];
  var numerator = (c[2]*t + c[1])*t + c[0];
  var denominator = ((d[2]*t + d[1])*t + d[0])*t + 1.0;
  return t - numerator / denominator;
}
  
// Source: http://picomath.org/javascript/normal_cdf_inverse.js.html
function normal_cdf_inverse(p) {
  // See article above for explanation of this section.
  if (p < 0.5) {
    // F^-1(p) = - G^-1(p)
    return -rational_approximation( Math.sqrt(-2.0*Math.log(p)) );
  } else {
    // F^-1(p) = G^-1(1-p)
    return rational_approximation( Math.sqrt(-2.0*Math.log(1.0-p)) );
  }
}
  
// Source: http://picomath.org/javascript/erf.js.html
function erf(x) {
  // constants
  var a1 = 0.254829592;
  var a2 = -0.284496736;
  var a3 = 1.421413741;
  var a4 = -1.453152027;
  var a5 = 1.061405429;
  var p = 0.3275911;
  
  // Save the sign of x
  var sign = 1;
  if (x < 0) {
    sign = -1;
  }
  x = Math.abs(x);
  
  // A&S formula 7.1.26
  var t = 1.0/(1.0 + p*x);
  var y = 1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*Math.exp(-x*x);
  
  return sign*y;
}
  
/**
* Find the CDF from the normal distribution
*
* @param float z the z-score of the distribution
* @return float the CDF
*/
function normDistCDF(z) {
  var cdf = (0.5 * (1.0 + erf(Math.abs(z)/Math.sqrt(2))));
  return cdf;
}
  
/**
* Parse CDF as a confidence level
*
* @param float cdf the CDF for the normal distribution
* @return float the confidence level
*/
function normDist(z){
  return 1-2*(1-normDistCDF(z));
}