That Girl: Become a Clean Girl

What this app looks like from outside

App	That Girl: Become a Clean Girl (Adventure Labs d.o.o.)
Released	2025-12-15 — 8 months old
Ratings now	4,617 at 4.78★ · as of 2026-08-21T18:00:08Z
Ratings a week earlier	4,445 · as of 2026-08-14T18:00:07Z
Movement	+172 in 7 days = +24.6/day, which is 0.55%/day against the base it started the week with

Both endpoints are single nightly observations, seven days apart, from full-coverage runs. Every number in this report is that: a stored observation with a timestamp, not a model output.

The number no dashboard gives you: where that sits among its peers

Your own analytics can tell you 4,617. It cannot tell you whether +24.6/day is fast. That only means something against apps doing comparable things — which requires measuring them too, nightly, for weeks.

Habit & Routine Builders released 2025-06-01 or later, same two runs:

#	app	ratings	7d ago	per day	%/day
1	Habuild: Online Yoga Everyday	1,435	1,373	+8.9	0.65%
2	That Girl	4,617	4,445	+24.6	0.55%
3	FivePrayer - Pray on Time	13,302	12,967	+47.9	0.37%
4	Chillio: Life Planner	1,767	1,731	+5.1	0.30%
5	PushClock - Loud Alarm Clock	5,719	5,634	+12.1	0.22%
6	Wayk: Alarm Clock to Wake Up	18,456	18,338	+16.9	0.09%
7	WIP: Social Habit Tracker	1,986	1,984	+0.3	0.01%
8	Self-Care Pet: Momo	2,267	2,267	+0.0	0.00%

The table can be read two ways: absolute additions show how many public ratings were added, while %/day judges that movement against each app’s earlier base. Those are different reference frames; neither is a download or revenue measure.

Against apps its own age — the cohort number

The peer table above compares That Girl with its niche. This compares it with every tracked app of comparable age (181–365 days old):

	as of 2026-08-24T18:00:11Z
7-day velocity	+22.2/day (Aug 18 → Aug 24)
Velocity vs. its age cohort	98.2nd percentile — faster than ~98 of every 100 apps its age
Rating-rate vs. its age cohort	92.9th percentile
Acceleration (this week ÷ last week)	0.80 — slowing, not speeding up

The percentile, rate percentile, and acceleration are separate archive measurements. Read together they provide context, but they do not turn this report into a forecast or a qualitative claim about the app.

Chart entries — the app and its niche

The archive records the first night an app appears on a US top chart.

• That Girl: no chart entry recorded in the archive (through 2026-08-24).
• Its niche (Habit & Routine Builders, 179 tracked apps): zero members entered a chart between 2026-08-14 and 2026-08-24, while 840 apps across all niches did. This is archive context only; it does not identify acquisition sources.

If this were a CurveSpotter call — a reference frame, not a call

Our public ledger fixes bars before outcomes are known. Applied to That Girl as of 2026-08-21, purely as a frame:

• D+21 bar: 2.0× baseline AND +50 absolute → 9,234 by 2026-09-11
• D+42 bar: 3.0× baseline → 13,851 by 2026-10-02

At the measured +24.6/day, D+21 arrives around 5,134 — far short of 9,234. That is the mechanical reading under these reference bars. This is not a call. No entry has been opened by this report; the ledger’s live calls are at curvespotter.com and were registered before their outcomes existed.

What we cannot see

Downloads, revenue, retention, MAU, where installs come from. Ratings are a public proxy and a lagging one; an app can grow users without ratings and can buy ratings without users. What this archive adds is not depth on your app — you have that — but the same measurement applied to everyone else, nightly, so your number has something to be compared against.

Method

Nightly snapshots of tracked US App Store apps are kept in the archive. Within one night an app may be measured several times; the published number is the highest that night observed, because a rating count does not fall and a cached response cannot unmake an earlier one (see the corrections register). Niche membership is our taxonomy, used for aggregation only.