[FEATURE] Timezone-aware analytics for hourly presence and activity

[Suyash-ka-github]

Feature Description

Currently, hourly analytics are calculated using server time (UTC), which causes users in different timezones to see activity mapped to incorrect hours (e.g., activity at 10 AM local time appearing as 4–5 AM).
This feature would allow analytics (hourly trends, peak hours, daily ranges) to be displayed according to the user’s local timezone.

Use Case / Problem Statement

BrowsePing is a globally usable browser extension, and users may be located in different timezones.
At the moment, hourly analytics such as Hourly Online Trend and Peak Hour are derived from server time rather than user-local time.

This leads to:

Confusing analytics (activity appears at unexpected hours)

Misleading “peak hour” information

Poor user experience for users outside UTC

For example:

A user browsing at 10:00 AM IST sees analytics showing activity at 4:00–5:00

This makes it appear as though usage happened at a completely different time

Timezone-aware analytics would ensure users see data that reflects their actual browsing behavior.

Proposed Solution

Capture the user’s timezone on the client side using:

Intl.DateTimeFormat().resolvedOptions().timeZone

Store the timezone as part of the user profile (e.g., Asia/Kolkata, America/New_York).

Continue storing all timestamps in UTC (no change to current storage approach).

During analytics calculation:

Convert UTC timestamps to the user’s timezone

Bucket activity by local hour (0–23) instead of server hour

Use timezone-aware date boundaries for daily/hourly aggregation

This ensures:

Hourly graphs match the user’s local clock

Peak hours are meaningful

Analytics remain consistent across regions

Alternative Solutions

Alternative Solutions

Display analytics strictly in UTC and label them as such (less user-friendly)

Additional Context

Additional Context

This is especially noticeable for users in non-UTC regions (e.g., Asia, Australia).

The issue becomes more prominent with features like Peak Hour and Hourly Trends.

Checklist

• I have checked existing issues for similar requests
• This feature would be useful for multiple users
• I have provided use cases and examples

[Suyash-ka-github]

Could You please Assign it to me under SWOC I would want to try this.

[akash-kumar-dev]

Hii @Suyash-ka-github , Thanks for opening this ticket! We were looking to create an issue for this, so great that you got ahead of us. I'm assigning this to you for further progress.

[Suyash-ka-github]

Hello @akash-kumar-dev I have fixed the issue But I also had to add few lines in the browser-extension So when the user logs in the timezone is sent to the backend and as per that the the analytics is changed So I have to create a pull request in the frontend too.