Web App Usage Report

At a Glance

Before generating the report, you make up to five configuration decisions. Each one shapes what data appears and how to interpret it.

Setting	Options	Key Question it Answers
Device Type	Desktop / Mobile	Should I see desktop apps and websites, or mobile apps?
Productivity Filter	Productive / Neutral / Unproductive	Which productivity listings should appear in the results?
Shift Scope	Full Day / Shift Hours Only	Should pre- and post-shift app & url usage count?
Leave & Holidays	Include / Exclude Time Off Days	Should data on non-working days appear in the results?
Time Format	Decimal Hours (2.5) / Hours:Minutes (2:30)	How should time values be displayed in the report?

What is the Web App Usage Report

The Web App Usage Report gives you a granular, row-level view of every application and website an employee interacted with during the selected date range. Unlike summary reports that show totals per person, this report breaks down time at the individual app and URL level. So, you can see not just how long someone was active, but exactly where that time went.

Each row in the report represents one employee's time on one application or URL. The report does not aggregate or summarise; it is intentionally detailed, making it the right tool when you need to investigate specific usage patterns rather than compare high-level totals.

If you are a...	You will typically use this report to...
HR / People Ops	Spot policy violations, audit application usage patterns across teams, and verify that productive tools are actually being used.
Team Lead / Manager	Identify which apps and websites consume the most team time, flag unproductive usage, and compare tool adoption across team members.
Admin	Configure and validate productivity classifications (Work Category and Listing) and run scheduled exports for compliance or review.
Individual Employee	Review your own app and URL history, verify that time on productive tools is captured correctly, and identify gaps in your classifications.

Understanding the Report Columns

The table below describes a few columns that appears in the downloaded report.

Column	What it Shows
Name	The name of the employee whose app or URL activity is recorded in that row.
User Id	The unique employee identifier assigned within Flowace (e.g. EMP1234).
Reports To	The full name of the direct manager or reporting lead of the employee, based on the org hierarchy configured in Flowace.
Team	The team the employee belongs to in Flowace (e.g. DEV, QA, DESIGN).
Work Category	An admin-configured label that groups apps and URLs into logical categories. For example, Communication (Google Meet, Slack, Zoom), Developer Tools (Bitbucket, GitHub), or Office Tools (Google Docs, Excel). One app or URL belongs to one Work Category.
Listing	The productivity classification assigned to the app or URL by the admin: Productive, Neutral, or Unproductive. This is the basis of the Productivity Filter on the report generation screen.
Application	The name of the desktop application or the source type for the captured entry. For apps auto-detected by the Flowace desktop agent, this shows the application name (e.g. Visual Studio, File Explorer). For other capture types such as manually entered time, calendar meeting classifications, or call logs, the respective data type is shown instead (e.g. Manual Entry, Meeting).
URL	The website URL visited within a browser, captured by the Flowace desktop agent (e.g. app.slack.com, bitbucket.org). For desktop applications that are not browser-based, or for non-URL capture types, this column shows NA.
Time	Total time the employee spent on this specific application or URL during the selected date range. Displayed in the format selected at report generation: Decimal Hours (e.g. 2.5) or Hours:Minutes (e.g. 2:30).

Sample Report Output

The table below shows a representative extract of the Web App Usage Report for a three-person team over a selected date range.

Date range: 22 Apr – 28 Apr 2026 | Shift Scope: Full Day | Productivity Filter: All | Leave & Holidays: Exclude Time Off Days

Name	User Id	Reports To	Team	Work Category	Productivity Labels	Type	Name or Domain	Time
Arjun Mehta	EMP1010	Rohan Kapoor	DEV	Developer Tools	Productive	Website	bitbucket.org	06:40
Arjun Mehta	EMP1010	Rohan Kapoor	DEV	Communication	Productive	Website	app.slack.com	02:15
Arjun Mehta	EMP1010	Rohan Kapoor	DEV	Office Tools	Productive	Website	docs.google.com	01:30
Priya Sharma	EMP2020	Rohan Kapoor	QA	Developer Tools	Productive	Website	github.com	05:00
Priya Sharma	EMP2020	Rohan Kapoor	QA	Social Media	Unproductive	Website	instagram.com	00:45
Priya Sharma	EMP2020	Rohan Kapoor	QA	Communication	Productive	Website	meet.google.com	01:20
Meera Nair	EMP3030	Rohan Kapoor	DESIGN	Software Dev	Productive	Application	Visual Studio	05:45
Meera Nair	EMP3030	Rohan Kapoor	DESIGN	Other	Neutral	Application	Calculator	01:08
Meera Nair	EMP3030	Rohan Kapoor	DESIGN	Break	Unproductive	Away	Lunch Break	07:00
Meera Nair	EMP3030	Rohan Kapoor	DESIGN	Training & Development	Productive	Away	Training	04:00
Meera Nair	EMP3030	Rohan Kapoor	DESIGN	Other	Neutral	Manual Entries	NA	01:00
Meera Nair	EMP3030	Rohan Kapoor	DESIGN	Communication	Productive	Phone Calls	NA	02:30

💡 Pro Tip: The Time column in the sample above uses Hours:Minutes format (e.g. 06:40). Select Decimal Hours at report generation if you need numeric values for calculations.

Productivity Filter

The Productivity Filter controls which rows appear in the report based on the Productivity-Labels assigned to each app or URL. You can include or exclude each of the three labels independently using the checkboxes on the report generation screen.

Productivity Labels	What it Covers	When to Include
Productive	Apps and URLs the admin has classified as productive for the team, for example, Jira, GitHub, Google Docs, Slack.	Include to see how much time employees spend on work-essential tools.
Neutral	Apps and URLs that have not yet been classified by the admin or configured as neutral.	Include to identify uncategorised tools that may need classification.
Unproductive	Apps and URLs the admin has classified as unproductive, for example, social media, entertainment sites.	Include (or isolate) to flag usage that falls outside acceptable guidelines.

Shift Scope

Shift Scope determines whether app and URL usage outside the employee's scheduled shift window is counted in the Time column.

It is one of the most impactful settings: the same employee can show noticeably different time values depending on which option you choose.

Scope	What it Counts
Full Day	Counts app and URL time across the employee's complete logical workday, from Day Start to Day End. Pre-shift and post-shift activity is included. This typically results in higher Time values across all rows compared to Within Shift Hours Window.
Shift Hours Only	Counts only app and URL time recorded within the employee's scheduled shift window. Any application or website activity before Shift Start or after Shift End is excluded from the Time column.

💡 Pro Tip: Use Full Day when you want to capture all app usage regardless of shift timing, particularly relevant for flexible work arrangements or when auditing total tool usage. Use Shift Hours Only when shift adherence is the focus, such as for contact centre teams or compliance reviews.

📌 If you need to compare both scopes for the same team, run the report twice with different Shift Scope settings and export both.

Leave and Holidays

This setting determines whether non-working days are included in the report. It affects which date ranges produce rows in the output and how totals should be interpreted.

Setting	What it Does
Include Time Off Days	All days in the selected period are included: working days, leaves, holidays, and weekly offs. Rows for non-working days will appear with their respective Time values if any app usage was detected.
Exclude Time Off Days	Only working days are included. Rows corresponding to non-working days (leave, holiday, weekly off) are omitted entirely from the report.

💡Pro Tip: Use Exclude Time Off Days when comparing app usage across employees who took different amounts of leave in the same period. This ensures rows only reflect actual working days. Use Include Time Off Days if employees have worked on the non-working days.

Which Combination Should I Use?

Use the table below to match your goal to the right configuration.

My goal is to...	Shift Scope	Productivity Filter	Leave & Holidays	Notes
See a full picture of all app usage across the team	Full Day	All Labels	Exclude Time Off	Broadest view - includes pre/post shift usage
Identify unproductive tool usage only	Full Day	Unproductive only	Exclude Time Off	Isolate just the Unproductive rows for a focused view
Review productive app adoption for a team	Full Day	Productive only	Exclude Time Off	Shows only tools labelled as productive - useful for adoption tracking
Audit app usage within shift hours for payroll/compliance	Within Shift Window	All Labels	Exclude Time Off	Cleanest view for compliance; excludes off-shift usage
Check if uncategorised apps need classification	Full Day	Neutral only	Exclude Time Off	Surfaces all Neutral-listed entries for admin review and classification. Apps and URLs with highest duration can be moved to unproductive/productive buckets after identification.
Investigate a specific employee's usage on a date	Full Day	All Labels	Exclude Time Off	Filter by member and narrow the date range to the day in question
Verify your own app and URL history	Full Day	All Labels	Include Time Off	Include Time Off to confirm no days are missing from your record
Compare productive tool usage across teams	Within Shift Window	Productive only	Exclude Time Off	Run per team; Within Shift Window ensures an even comparison baseline

Updated on: 30/04/2026

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