Forum Discussion
Optimizing Microsoft 365 Licenses Using Behavior Data (E3/E1/F3)
Hi everyone,
We are currently working on a Microsoft 365 license optimization initiative and would appreciate insights from the community and Microsoft experts.
Our approach focuses on two main areas: (1) Revoking licenses for inactive users, and (2) Reviewing active users to ensure their assigned license (E3, E1, or F3) aligns with actual usage and collaboration needs.
From a data perspective, we are leveraging Microsoft 365 usage signals such as Teams activity, Outlook email interactions, meetings, and SharePoint/OneDrive collaboration. While usage reports provide raw metrics, we are looking for guidance on how these signals should be interpreted and combined in a meaningful and fair way.
Specifically, we would like to understand: (1) Which usage metrics best represent user collaboration behavior? (2) Are there any recommended thresholds or patterns that help distinguish light, standard, and heavy collaboration users to map E3, E1, or F3?
Any best practices, references, or real-world experiences would be greatly appreciated. I'm sorry if this is the wrong forums to ask for. Thanks in advance for sharing your insights.
2 Replies
On the "no fixed thresholds" point: that's actually correct, and for a good reason. Tier fit (E3 vs E1 vs F3) isn't really a light/standard/heavy *volume* question, it's a *feature-entitlement* question: does the user actually use the capabilities the higher tier uniquely provides? Someone who sends five emails a day but relies on desktop Excel still needs E3. Someone hammering Teams all day but only in the browser could sit on E1. So usage volume is useful to find *candidates*, but the confirming test is feature need.
The two hard discriminators to key off:
1. Desktop Office apps. This is the E1-vs-E3 line. Office 365 E1 has no desktop client apps (web + mobile only); E3 includes them. So if a user never activates or uses desktop Word/Excel/Outlook, E3's main premium is wasted on them and E1 becomes viable.
2. Mailbox size / archive. E3 = 100 GB mailbox + auto-expanding archive (Exchange Online Plan 2). E1 = 50 GB, no archive (Plan 1). F3 = 2 GB (Exchange Online Kiosk), Outlook on the web only. If a mailbox is over 50 GB or relies on archive/hold, that user is effectively locked to E3.
A workable signal-to-tier flow, using data you already have in the M365 usage reports / Graph:
- Pull the Microsoft 365 Apps usage report (desktop vs web activation per app), Exchange activity + mailbox size, and Teams/SharePoint/OneDrive last-activity.
- Then decide by need, not by a raw count:
- Uses desktop Office apps, or mailbox > 50 GB / needs archive -> stays E3.
- Web/mobile only, desk worker, real mail + collaboration, mailbox < 50 GB -> E1 candidate.
- Frontline/shift/mobile pattern, minimal email, shared or mobile device, no real desktop footprint -> F3 candidate (2 GB mailbox, OWA only).
- Teams-only "kiosk" with no mailbox need -> F1, but note F1 has no Exchange mailbox rights at all.
Two things worth baking in before you act on it:
- Use a long enough lookback (90 to 180 days) and treat borderline cases as review, not auto-downgrade. Behavior data misses occasional/seasonal desktop use, e.g. the person who opens Excel once a quarter still needs E3.
- Check mailbox size before any downgrade. E3 -> E1 halves the mailbox cap (100 -> 50 GB), and E1/E3 -> F3 drops it to 2 GB. If the mailbox is bigger than the target tier's cap you'll hit over-quota issues. Mixed plans in one tenant are fully supported, so per-user tiering is legitimate.
Source for the plan differences (desktop apps, Exchange plan per tier): Microsoft 365 and Office 365 plan options (service description):
https://learn.microsoft.com/en-us/office365/servicedescriptions/office-365-platform-service-description/office-365-plan-options
A structured approach to optimizing Microsoft 365 licensing (E3, E1, F3) involves leveraging Microsoft’s official usage reports and Adoption Score insights. Key indicators include Teams meetings and chat activity, Outlook email volume, and SharePoint/OneDrive collaboration patterns. While Microsoft does not prescribe fixed thresholds to classify “light,” “standard,” or “heavy” users, best practice is to evaluate these signals collectively to establish a balanced and accurate profile of user collaboration behavior.
https://learn.microsoft.com/en-us/graph/reportroot-concept-overview
https://learn.microsoft.com/en-us/microsoft-365/admin/adoption/adoption-score?view=o365-worldwide
https://download.microsoft.com/download/3/D/4/3D42BDC2-6725-4B29-B75A-A5B04179958B/Licensing_guide_Microsoft_365_Enterprise.pdf
