TikTok

Section: Social platforms and channels · tt

TikTok combines profile counters, publication rate, and video medians. When comparing accounts, keep total views separate from percentage quality metrics.

What this page includes

A metric table, worked examples, and short platform-specific notes.

How to read the examples

All numbers are illustrative. They are here to explain the formula, not to describe a specific account.

Which metrics this page shows

Metric	Key	Type	How to read it
Subscribers	`tt_count`	Count	A direct count without extra recalculation.
Publication rate	`tt_ppd`	Posting rate	How many publications come out per day on average within the selected period.
Views (total)	`tt_playCount`	Count	Total play count without converting it into a percentage.
VR (med.)	`tt_median_VR`	Percent	Typical VR across publications.
IR (by views)	`tt_interaction_rate_by_views`	Percent	Share of all reactions relative to views: (likes + comments + shares) / views * 100.
LR (med.)	`tt_median_LR`	Percent	Typical LR across publications.

Example: cadence and median calculation

For video platforms, posting frequency and typical per-video metrics are usually the most important. Below is a sample calculation.

Inputs

Period: 28 days
Videos: 16

Calculation steps

Publication rate
16 / 28
= 0.57 videos/day
VR (med.)
median([14.50, 18, 22.40, 27.10, 36])
= 22.40%
LR (med.)
median([1.60, 2, 2.40, 2.90, 3.40])
= 2.40%
Total views of the set
Sum of views across all videos included in the analysis
= 520 000 views

If there are no valid values for a median, dstat returns an empty field rather than a fake 0%.

Platform-specific nuances

tt_playCount shows raw view scale, while tt_median_VR and tt_median_LR show relative publication quality.
tt_interaction_rate_by_views follows the shared actions/views*100 formula.
If view data is partial, compare only the metrics that are filled for both sides.