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Teamwork Analytics
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- Target Specific Team Owners by Country with Information
- Reminder about Team Guests
- New Public Teams without Guests
- Single Owner Reminder with Channel ID
- Public Teams Reminder with Channel ID
- Target Specific Team Members by AD attributes
- Teams Activity Reminder with Channel ID
- New Public Teams without Guests
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- Summary
- Activity by Country and Modality
- Active User Counts
- Active User Percentages
- Active User Percentages All Bands
- Month on Month
- Device Usage
- Device Usage Details
- Avg Use Per User Per Day by Country
- Relative User Activity
- Users and Attributes
- Custom AD Attributes
- Data Freshness Detail
- Daily Active Users
- Weekly Active Users
- Monthly Active Users Percentage
- Relative Daily Active Users
- Relative Weekly Active Users
- Relative Monthly Active Users
- Activity Counts Daily
- Activity Counts Weekly
- Activity Counts Monthly
- Per User Activity Daily
- Per User Activity Weekly
- Per User Activity Monthly
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- Team Stats
- Teams Distribution
- User Collab Activity
- Collab Activity (Averages)
- Collab Activity (Totals)
- User Mention Activity
- Team Files
- Per Team Profile
- Guest Distribution
- Guest Details
- Users and Attributes
- Threads Country Interaction
- Replying Country Interaction
- Threads Department Interaction
- Replying Department Interaction
- Active Teams Files and Chat
- Teams Channel Chat Activity
- Data Freshness Detail
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- Meeting Trends
- Meeting Detail
- Meetings Per User Trends
- Meeting Join Stats
- Meeting Join Dashboard
- Meeting Joins by Country
- Meeting Join Country Detail
- Meeting Joins by User
- Calls Per User Trends
- Call Stats
- Calls Dashboard
- Calls by Country
- Calls Country Detail
- Calls by Users (All)
- Calls by Users (Last 14 days)
- Interaction Overview (Last 14 days)
- Call Interactions (Last 14 days)
- Meeting Interactions (Last 14 days)
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- Querying the RAW JSON Call Records Files
- Data Issues with Microsoft Teams user activity Get user detail Endpoint
- Check Data Freshness from Microsoft Reporting API
- Get Call Record from Graph
- Calls and Meetings Database Schema
- Deploy a Calls & Meetings Automation scenario (CAT)
- CAT Installs – Customer Monitoring
- Configure Task Scheduler for Automation
- SQL Backups
- CAT Configuration Notes
- Data Nuances
- DeadLetterManager
- Calls and Meetings Aggregate Table Calculations
- Anonymisation of Selected Users PII Data
- Excluding teams from file scan
- Configure Custom User Attributes – Usage and Governance
- Configure Data Retention – Usage and Governance CAT
- Data Collection Configuration (Scan)
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- Call Queue and Auto Attendant data
- Collecting Logs – Usage and Governance
- Comparing Teamwork Analytics to other solutions
- Data Collection Explained Usage and Governance
- Data Dictionary and Reporting Capabilities Usage and Governance
- Decommission
- Determining current data collection state
- FAQ Usage and Governance
- Files / Drive Items
- Messages
- Monitoring and Maintenance Tasks Usage and Governance CAT
- Relative User Activity Thresholds
- Security Details
- Usage and Governance Data Collected and Capabilities
- Usage and Governance Dependencies
- Calls & Meetings Definitions
- Database Version
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Teams Audit
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Teams Chat Assist
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OneConsultation
Relative User Activity Thresholds
Relative User Activity Thresholds are for grouping users into Low, Medium, High and Very High usage categories
- They are good for;
- Comparing departments, groups, countries
- What % of their user Low, Medium, High and Very High
- They enables report such as;
- “Where are the highest Calls activity users located?”
- “How does London usage compare to France usage for Team Chat?”
- Category boundaries based on global usage, per modality, for the day/week or month
- Boundaries change as global usage trend changes
- Activity grouped into classifications based on percentiles
- The usage thresholds for each classification will change over time and for each modality.
- Zero usage users are not included in classifications
Classification Boundaries
We group users into either Low, Medium, High and Very High usage categories using the following percentiles.
These percentile classifications are based on Modality System previous experience with actioning usage data to drive improved adoption.
Classification | From Percentile | To Percentile | Description |
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Low | 0th | <= 10th | Users which need the most training and assistance |
Medium | > 10th | <= 60th | Users should be encouraged via indirect adoption methods such as posters, emails, self-service training etc. |
High | > 60th | <= 90th | Contains “Teams Champions” and those that can help others achieve |
Very High | > 90th | <= 100th | Extreme users which may be candidates for good news stories, case studies etc. |
Ranges are inclusive of the upper bound, but exclude the lower bound. For example, the Medium range can be read as “greater than the 10th Percentile and less than or equal to the 60th percentile”
Worked Example of Calculation
Consider the following table of usage for Team Messages;
User | Team Messages |
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Adam Barr | 1 |
Alan Steiner | 8 |
Chris Norred | 22 |
Christine Koch | 6 |
Dan Jump | 14 |
Dan Park | 1 |
Diane Tibbot | 3 |
Frank Martinez | 2 |
Jeff Hay | 7 |
Karim Manar | 16 |
Percentiles for usage are calculated using the PERCENTILE_CONT function in SQL, the equivalent in Microsoft Excel is PERCENTILE.INC. The percentile thresholds from this data are calculated as follows;
Percentile | Value |
---|---|
10th | 1 |
60th | 7.4 |
90th | 16.6 |
This results in the following classification of those users;
User | Team Messages | Classification |
---|---|---|
Adam Barr | 1 | Low |
Dan Park | 1 | Low |
Frank Martinez | 2 | Medium |
Diane Tibbot | 3 | Medium |
Christine Koch | 6 | Medium |
Jeff Hay | 7 | Medium |
Alan Steiner | 8 | High |
Dan Jump | 14 | High |
Karim Manar | 16 | High |
Chris Norred | 22 | Very High |