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How the journey effort score is calculated

Journey management creates the effort score is built from , each capturing a different kind of friction a customer can experience. Each contributor is weighted individually by how much it typically impacted an experience in relation to how much the journey itself shaped the outcome.

Step 1: Calculating the contributor score

The weighted score of each of the contributors is calculated from Journey Management events. They are then aggregated, normalized, and combined into a single score per customer. The individual scores are then averaged to derive an journey effort score, which indicates the effort your organization’s customers experience overall.

Some contributors have a cap on the limit to ensure that a small number of skewed data do not distort results.

ContributorWeight

Elapsed time – Extreme values are capped to prevent skewed results.

Elapsed time carries the lightest weight because duration alone matters less to perceived effort than waiting, being bounced around, or not getting resolved, and duration naturally varies by topic.

15%
Wait/idle time – Extreme values are capped to prevent skewed results.25%
Switches and transfers25%

Wasted effort (incomplete journeys)

Carries the heaviest weight because it captures the outcomes customers find most frustrating. 

35%

Step 2: Normalizing the score

The four contributors indicate a different sentiment and are counted differently. For example, elapsed time is measured in milliseconds, while switches and incomplete journeys are counts. To combine them accurately, each contributor is normalized to a common 0–1 range.

  1. Each contributor score is normalized to a common 0–1 range using the minimum and maximum values seen across your organization’s journeys over a rolling 30-day window. This window is ideal to capture normal variation and not be influenced by unusual spikes.
  2. Each normalized value of each of the contributor is multiplied by its weight.
  3. The four weighted values are added to produce a customer’s effort score.

Your customer effort score can be compared against your typical range to understand the effort of that journey. As the score is a result of the normalization done on your organization’s 30-day window period, the score is solely comparable with your normal organization’s normal value. 

Step 3: Grouping the score within effort segments

The effort score is now segmented to understand how the journey ranks within your organization’s own effort patterns. This allows managers to focus on unusually high or low effort journey. A effort score’s segment depends on where it ranks against the rest of the 30-day window. The window period standardizes the segment sizes. However, the effort ranges can vary between organizations.

  1. Before segments are assigned, the most extreme scores in the 30-day window are capped at the 2.5th and 97.5th percentile to ensure that a few outliers do not distort the general pattern.
  2. The distribution is then divided into four cuts: the 20th, 50th (median), 80th, and 95th percentiles. Because the cut points come from percentiles, segments land close to this 20/30/30/20 split regardless of whether your scores run high or low overall.
    Note:  The 95th percentile also flags the most extreme experiences within Very High for internal monitoring — those conversations are still counted and shown as part of Very High.
  3. Segment cut points are recalculated on the same rolling 30-day window used to normalize the score, so segment boundaries shift as your journey patterns shift. This reflects your most recent 30 days and not a one-time calculation.
SegmentWhere it fallsApproximate share

Very Low

Below the 20th percentile

~20%

Low

20th to 50th percentile

~30%

High

50th to 80th percentile

~30%

Very High

80th percentile and above

~20%