Common use cases

Your might be asked to use multiple scales to accommodate the following use cases:

• Previous vendor used multiple scales — If you are replacing a non- Experience Cloud implementation, your company stakeholders might want to keep scales used in that prior implementation. Encourage your company to understand that swapping one technology for another will not drive business improvements. Ask your stakeholders to re-think their approach to customer experience, and move towards a simpler, OCEM-based approach. Also, consider that historical data imports might not be valid statistically if there are other changing factors (such as shortening the time from transaction to to survey) that could influence scores.

• Different survey methodology across business units or markets — Some companies have defined survey methodologies that differ across areas of their business or by market. Seek to understand whether a global view is important. If it is, articulate that it is difficult to compare scores usefully across regions using different scales.

• Social media scores — Social media scores are usually given on a 5 point scale, while Experience Cloud most commonly uses a 10 point scale to align with NPS methodology. If you plan to use social scores, convert them to a unified scale, as described in Social Feedback scores.

• Non-Medallia survey imports — Your company might insist on importing survey results conducted outside of your Medallia implementation, and those surveys might use a different scale.

Areas impacted by multiple scales

If you must implement multiple scales, note the following areas of Experience Cloud that are impacted, and note the solutions where they are available.

In general, reports that combine records from surveys with different scales require K-fields to combine scores into a single scale. Even with this accommodation, reports can be confusing to users because any metric will have been modified from the survey taker’s answer choice. For example, if converting everything to a 5-point scale, a user might wonder how someone who gave an answer of 10, could have an average of a 5. For more information, see K-fields.

Medallia Mobile

The main score field drives the numbers that appear in the left side of Responses reports in Medallia Mobile. Some companies might wan this to be configured to be different than the main score field used for Text Analytics. To solve this need, create a K-field for the main score to be used in Medallia Mobile.

For more information bout creating K-fields, see K-fields. For more information, see Medallia Mobile.

Score Filter dropdown

The Score Filter dropdown in the Control Panel can be confusing with multiple scales. There is no solution to this problem other than training users when to use each scale.

Recent Responses dashboard modules

You can define only 1 score field for the Score Filter property of Recent Responses dashboard modules. Instead of creating a module for each score, choose the most important score. For more information, see Recent Responses.

Satisfaction Distribution report

You can define only 1 value string for the ScoreDistrString property of Satisfaction Distribution reports. Social media are the exception, are hard coded to appear at the bottom of the report. For more information, see Satisfaction reports.

Calculations

You can create calculations to accommodate multiple scales, using JavaScript for each field to be used in a calculation. For example, you could write a top-box calculation to include a 5-point and 10-point scale. For more information, see Calculations.

Text Analytics and Word Clouds

Medallia Text Analytics and Word Cloud modules use a single field. For programs with multiple surveys, you must use a K-field that combines scales from different surveys into a single field. For example, the following code converts fields to a 5-point scale:

/* This k-field is used to consolidate main scores across multiple surveys that use DIFFERENT scales or altsets
If consolidating scores from different scales, use Consolidate Main Score across Surveys - Same Scale
*/

// Helper function to convert scales if using metrics on different scales.
convertScales = function(sourceScaleMin, sourceScaleMax, targetScaleMin, targetScaleMax, sourceMetric)
  {     

  // Null check.
  if (isNull(sourceScaleMin) || isNull(sourceScaleMax) || isNull(targetScaleMin) ||   isNull(targetScaleMax) || isNull(sourceMetric)){
   return null;
   }

  // Set ranges.
  var sourceScaleRange = sourceScaleMax - sourceScaleMin;
  var targetScaleRange = targetScaleMax - targetScaleMin;

  // % Normalize = (Current Value-Current Min Value)/Range of Current Value
  var normalizePct = (sourceMetric - sourceScaleMin) / sourceScaleRange;

  // Desired value = (Desired Range*% Normalize) + Min of Desired Range
  var targetValue = (targetScaleRange * normalizePct) + targetScaleMin;

  // Round targetValue to integer by randomizing % to round up/down using targetValue decimals
  var pctRoundUp = targetValue - Math.floor(targetValue);

  // Generate random number for this survey
  var randomNumber = random(a_surveyid);

  // Compare randomNumber to pctRoundUp - if lower, then round up
  if (randomNumber < pctRoundUp) return Math.floor(targetValue) + 1;

  // else round down
  return Math.floor(targetValue);
  }

// Consolidate main metrics across surveys
(function () {

  // Review/modify: Scale to use for main score - replace with relevant minimum and maximum values.
  var targetScaleMin = 0;
  var targetScaleMax = 10;

  // REVIEW/MODIFY HERE - List all score fields you want to consolidate into the main score and their respective min/max values across survey scales.
  var mainScoreFields = [
    // Example metric with 0-10 scale
    {
      field
    },
   // Example metric with 1-10 scale
   {
      field
   },
   // Example metric with 1-5 scale
    {
      field
    }
  ];

    // Loop through all fields and recalculate to target scale, if needed.
    for (var i = 0; i < mainScoreFields.length; i++) {

      // Null check - skip to next loop
      if (isNull(mainScoreFields[i].field))

     {
        continue;
     }
     // If source and target scales are the same, return raw value.
     if (mainScoreFields[i].sourceScaleMin == targetScaleMin && mainScoreFields[i].sourceScaleMax == targetScaleMax)

    {
      return mainScoreFields[i].field;
    }
    // If source and target scales different, return the converted score.
      return convertScales(mainScoreFields[i].sourceScaleMin, mainScoreFields[i].sourceScaleMax, targetScaleMin, targetScaleMax, mainScoreFields[i].field);

   }

    // If no score at all, return null
    return null;

    }());

For more information about creating K-fields, see K-fields. For more information about configuring Text Analytics, see Implement Text Analytics. For more information about configuring Word Cloud modules, see Word Cloud.