ESNTL Wellness

ESNTL Admin Console: A Comprehensive Data Guide for Users

Make the most of our extensive data metrics and analyses to understand and optimize your organization’s wellbeing strategy.

Last updated: Feb 8, 2024

General

Mood with "Not enough data" description

You may notice data visualizations that say “Not enough data” or have gaps between data points. This is because data points are hidden when they don’t make up a large enough aggregate of users to ensure data anonymization. Organizations with more users are less likely to see this. To ensure this data anonymization the following rules are used:

  • Data points representing <5 users are excluded from most visualizations and calculations.

  • Elevated heart rate horizontal bar chart values of 1-3 are represented as “≤ 3”.

  • Weekly active devices data points representing <5 unique devices are excluded.

  • Dates where there were <5 active unique mobile devices are excluded from Wellness resource usage data.

  • Critical Interventions is the only chart that doesn’t have a minimum count requirement.

  • Dashboard Refresh: Each time you view the Wellbeing dashboard or Usage metrics page, it shows the latest health and app usage data collected.
  • When Data Updates: Data is collected after any user:
    • Sets up the app for the first time.
    • Completes a check-in.
    • Opens the app.
  • Time to Sync: Updated information will appear on the dashboard within an hour of these user activities.
  • Health Data from Inactive Users: If a user hasn’t opened the app in a while, their health data will show up after they next use the app, with updates backfilled to fill in the gap.

Date and Job Role filters

The Admin Console provides administrators with valuable insights through the Wellbeing Dashboard and Usage Metrics page. To make the most of these insights, admin users can filter data by date and job role. To utilize job role filtering, ensure that job roles are assigned to app users in the User Management page.

Understanding Job Role Filter and Time

When a job role is assigned to a user, their data will be categorized under that job role for the duration of the assignment.

For instance, if a user is assigned the “Manager” job role in February and later changed to “Director” in March, their data will be included in the “Manager” category when filtering for February data on the Wellbeing Dashboard or Usage Metrics page. When the date range is switched to March, their data will be included in the “Director” category. This ensures accurate data representation for job roles, allowing for seamless transitions in responsibilities across your organization.

Balancing Job Role Filtering and Data Privacy

Filtering data by job roles with only a few users may result in hidden data due to not meeting user count thresholds for data privacy. To prevent this, organizations have the following options:

  1. Create larger job role groups: Ensure that job roles represent sizable groups of users. Although the ideal number of users depends on app usage frequency, we recommend groups of 20 or more users if attempting to see data for only that group on the Wellbeing Dashboard or Usage Metrics page.

  2. Apply multiple filters: Use job roles to exclude or include multiple groups of users. For example, if an organization wants to view data for all users except managers or administrators, they can assign more granular job roles and deselect the groups they wish to mangers and administrators when filtering on the Wellbeing Dashboard or Usage Metrics page. Selecting multiple job roles increases the likelihood of meeting minimum user count thresholds for data privacy.

By implementing job role filtering, organizations can gain a deeper understanding of their data and make more informed decisions to improve overall wellbeing and productivity.

Wellbeing Dashboard

Understanding the metrics on your wellbeing dashboard.

Baseline: Average of data points for the 5 years preceding the date range selected where the data points represent 5 or more users.

Average: Average of the data points for the date range selected where data points represent 5 or more users.

Data pointDescriptionSource
MoodAverage of all mood ratings

·       Start of day checkin

·       End of day checkin

Sleep TimeAverage of all recorded sleep time amountsPassively collected from Watch
Exercise MinsAverage of all recorded exercise minutesPassively collected from Watch
Nutrition SatisfactionAverage of all recorded nutrition satisfaction responsesEnd of day checkin
Sleep Quality ScoreAverage of all recorded sleep quality responsesStart of day checkin
Hydration AmountAverage of all recorded hydration score responsesEnd of day checkin
Work/Life Balance

Average of all recorded work/life balance responses

Note: Work/Life balance is asked in the app once per week. When a user responds to the question, that value is applied to current date and preceding 6 days

End of day checkin
Exercise SatisfactionAverage of all recorded exercise satisfaction responses.End of day checkin
Social Connection

Average of all social connection responses.

Note: Social Connection is asked in the app once per week. When a user responds to the question, that value is applied to current date and preceding 6 days

End of day checkin
Resting Heart RateAverage of all recorded resting heart ratesPassively collected from Watch
Elevated Heart Rate EventsAverage number instances per user where resting heart rate was 70% above restingEnd of day checkin
Data pointDescriptionSource
Elevated Heart Rate ActivityTotal number of instances where users selected the activity when reflecting on elevated heart rate events in EOD check-inEnd of day checkin
Elevated Heart Rate Work ActivityTotal number of instances where users selected the work activity when reflecting on elevated heart rate events in EOD check-inEnd of day checkin

How it works

  1. Correlations are calculated for all combinations of Pulse metrics.
  2. Correlations are ordered by absolute value.
  3. The two strongest correlations are displayed on Wellbeing Dashboard


Strength chip: Displays the strength of the correlation as measured by Pearson correlation coefficient, r.

Strength

Correlation (r)

Description

Strong

r >= 0.7

r <= -0.7

A strong linear relationship exists between these two metrics.

Moderate

0.7 > r >= 0.4

-0.7 < r <= -0.4

A moderately strong linear relationship exists between these two metrics.

Weak

-0.4 < r < 0

0 < r < 0.4

A weak linear relationship exists between these two metrics.

None

r = 0

No linear relationship exists between these two metrics.

Polarity chip: Displays the polarity of the correlation as measured by Pearson correlation coefficient, r.

Relationship

Correlation (r)

Description

Positive Correlation

r > 0

Positive correlation is a statistical relationship between two variables in which they tend to increase or decrease together.

Negative Correlation

r < 0

Negative correlation is a statistical relationship between two variables in which one variable tends to increase while the other variable tends to decrease.

No Correlation

r = 0

No linear relationship exists between these two metrics.

 

Usage Metrics

Average: Average of the data points for the date range selected where data points represent 5 or more users.

Total: Sum of the values for the data points in the date range selected where data points represent 5 or more users.

Trend: The percentage difference between the total or average for the currently selected date range and the previous period.

Data pointDescriptionStatistic
Weekly active devices

Mobile: Number of phones with at least one session in the week starting on the given data point.

Watches: Number of watches that gathered biometric data in the week starting on the given data point.

Total: Combined total of weekly active mobile and watch devices for the week starting on the given data point.

Average
Weekly sessions

Total number of sessions across both phone and watch devices for the week beginning on date displayed.

Average
Critical InterventionsNumber of clicks of emergency resourcesTotal
Daily active usersNumber of users that had at least one sessionAverage
Wearers to bed

Number of users that had sleep time data

Watch users (modal window): Number of users that had resting heart rate data

Average
Daily sessions / userSessions per user per dayAverage
Median session lengthFor each date, the median session length is calculated for each job role and the average of those medians is displayed.Average
SOD check-insNumber of start of day check-ins within the date range selectedTotal
EOD check-insNumber of start of day check-ins within the date range selectedTotal

Total: Sum of the values for the data points in the date range selected where data points represent 5 or more users.

Trend: ((Total for selected Date Range – Total for Preceding Period) / Total for Preceding period) *

 

 

Data pointDescription
Total usersNumber of unique users who visited the Resources section
Total views of Wellness pageNumber of views of the Wellness page
Total views of Wellness categoriesNumber of views of the Wellness category pages
Total actions on ResourcesTaps/Clicks on call to action buttons of Wellness resources
Wellness categories bar chart

Users: Number of unique users who viewed Wellness category

or (toggle)

Views: Number of views of Wellness category

Resources bar chart

Users: Number of unique users who viewed Wellness resource

or (toggle)

Actions: Number of taps on CTAs of Wellness resource

Additional questions?