Use Global analytics to review platform adoption and high-level performance trends, then decide where deeper investigation is needed.
The dashboard provides a set of overview blocks for HR leaders, platform administrators, and other stakeholders. You can filter the data, compare trends over time, and identify topics that are driving demand.
For an introduction to Global analytics and how it differs from Knowledge analytics, HR Case management analytics, and Agent analytics, see Global analytics.
Before you begin
- Make sure you have access to Analytics.
Explore the dashboard
Global analytics provides a set of preset overview blocks.
Use the filter bar at the top of the page to filter data by:
- Period
- Role
- Channel
- Geography, where available
- Custom user properties configured for analytics.
Charts update automatically when you change a filter.
Choose a time period
Select a preset time period or specify a custom date range.
Some trend data is averaged over a monthly window. This helps reduce the effect of unusually busy or quiet days and makes longer-term changes easier to identify.
Engaged users
Shows the number of employees who interacted with the platform at least once during the selected period.
An interaction can include:
- Logging in
- Browsing a page
- Asking the AI Assistant a question.
Interactions are counted across any supported channel.
Use Engaged users to understand how many employees are actively interacting with Applaud during a period.
Engaged users doesn't tell you whether those interactions were effective or whether an employee's request was successfully resolved. Compare it with adoption, deflection rate, and user satisfaction for a broader view.
Adoption rate
Shows the percentage of employees with an active account during the selected period who used the platform at least once.
A higher adoption rate means more of your workforce is engaging with self-service rather than going directly to HR.
Use Adoption rate to understand how widely employees are using Applaud among the people who could use it.
A change in adoption rate doesn't by itself explain why employees are or aren't using the platform. Use filters and other analytics areas to investigate differences by role, channel, or other available segments.
Deflection rate
Shows the percentage of employee queries that the AI Assistant resolved on its own without HR intervention.
Only routine, self-service matters are counted. Sensitive topics, such as harassment or disciplinary queries, are always escalated to HR, regardless of whether the knowledge base could answer them.
Use Deflection rate as a high-level self-service outcome indicator.
A low deflection rate doesn't necessarily mean that the AI Assistant is performing poorly. Some topics are intentionally designed to require HR involvement.
For a more detailed view of AI effectiveness, use Agent analytics.
User satisfaction
Shows the percentage of employees who rated their experience positively based on thumbs-up and thumbs-down feedback.
Only sessions where an employee explicitly rated their experience are counted. Sessions with no rating are excluded.
Use User satisfaction to understand employee feedback among sessions that received an explicit rating.
Because this metric is based on submitted feedback, it doesn't represent the satisfaction of every employee who used the platform.
Adoption, self-service deflection & satisfaction trends
Shows adoption, self-service deflection, and satisfaction trends in one view.
The trends are averaged over a monthly window so that a single unusually busy or quiet day doesn't distort the overall picture.
Use this chart to compare how adoption, self-service outcomes, and employee satisfaction change over time.
Look for sustained changes rather than interpreting a single daily movement as a significant trend.
Engaged users by channel
Shows the engaged employee count broken down by the channel employees used to access Applaud.
Channels can include Web, Microsoft Teams, Slack, Mobile, and other supported channels.
Use this chart to understand where employees are accessing Applaud and how channel usage changes over time.
Inquiry volume by knowledge area
Maps employee questions to a knowledge area, such as Time Off, Pay & Benefits, or Onboarding.
The table shows:
- Inquiries - the number of inquiries for the knowledge area.
- Inquiry trend - how inquiry volume changes over time.
- Deflection % - how effectively the AI Assistant is deflecting those inquiries from HR.
The inquiries include questions handled by the AI Assistant as well as questions where HR needs to step in.
Use this view to identify which knowledge areas receive the most employee questions and where the knowledge base may need strengthening.
A high inquiry volume doesn't necessarily indicate a knowledge gap. It may simply indicate that the topic raises many employee questions. Compare inquiry volume with deflection and other knowledge metrics before deciding what action to take.
Use filters to investigate trends
Start with the organization-wide view, then apply filters to investigate specific areas.
For example, you can:
- Filter by role to compare adoption across different groups.
- Filter by channel to compare how employees access Applaud.
- Filter by a custom property, such as Department, to investigate differences between segments.
- Change the period to compare performance over time.
Best practices
- Review Global analytics regularly to understand overall adoption and self-service performance.
- Consider engaged users, adoption, deflection, and satisfaction together rather than relying on a single metric.
- Use Engaged users by channel to understand where employees are accessing Applaud.
- Use Inquiry volume by knowledge area to identify areas of high demand and potential knowledge gaps.
- Consider the monthly averaging window when interpreting trends.
- Use Global analytics to identify where deeper investigation is needed, then open Knowledge analytics, HR Case management analytics, or Agent analytics for more detailed analysis.