Artifact 07 — Demand Engine

Growth Loop

One dominant loop, named and quantified: the legally-clean sentence-mining artifact loop. A learner mines a card from their own study session, shares it where mining screenshots are already native behavior, a peer asks "what tool?", installs, mines, shares. The whole compounding curve below rests on a single instrumented number — the loop factor K.

Loop factor K · target

≥0.3

Activation target (D7)

45%

M12 MRR (base)

$15.4K

LTV : CAC

~3:1

Bar for good Pull one lever in the model — raise activation, raise K, raise paid seed — and the 12-month MRR projection updates predictably from the same formulas. A growth lead can read this, change one assumption, and quote the new ARR without rebuilding the math.

Purpose. Name the dominant loop and show how it compounds — so growth spend follows the one mechanism that earns its CAC, not a hopeful funnel.

Status — prototype only, loop UNVALIDATED Zero users, zero revenue, zero LOIs. Every number on this page is a hypothesis to be validated by the Week-4 field test. The loop underwrites CAC only after K is measured with real instrumentation: K ≥ 0.3 proves it; K < 0.15 demotes it to a paid-CAC fallback.

1 · The loop, picked

Loop type = content / community-led virality, not paid or sales. The original "post your dubbed clip" loop is dead on arrival — re-publishing dubbed copyrighted streams is barred by legal-ops §4. The asset that survives is the user's own study note.

Dominant loop · legally-clean own-content artifact

A learner mines a bilingual card from their own session, shares it into the immersion community, a peer installs Babelio to do the same.

Why this asset is legal-clean: the shared artifact is the user's own annotation layer — the captured line + their gloss + translation, exported to Anki or as a "today's immersion" recap with a Mined with Babelio footer. It is never the source media, so it sits inside legal-ops §4's single-user-comprehension carve-out. We will not anchor CAC on a loop that requires illegal artifacts.

Why it can spin: mining screenshots are already a native social behavior in r/LearnJapanese, Refold / TheMoeWay / Migaku Discords. Babelio attaches its name to behavior that exists organically — we don't manufacture the share, we instrument and brand it.

Secondary loop (no artifact): practitioner-identity word-of-mouth — "finished the immersion challenge" referral inside the same Discords. It moves installs even if the artifact loop underperforms, and is the bridge to the community channel.

2 · The loop diagram

Five named steps. The loop closes when a shared artifact drives a new install. The single multiplier that decides whether it compounds or leaks is K = (shares per activated user) × (installs per shared artifact).

Each loop turn also seeds the community + SEO channels (06-gtm-motion) and feeds the activation metric (08-retention).

Instrumented events (day-1 requirement) artifact_created (first export/share) and artifact_shared_external (posted to a community) are logged from launch. K is computed as (shares ÷ activated users) × (installs ÷ shared artifacts), read at the Week-4 challenge-kickoff test. Activation and loop-supply are the same action — "export/share first card" — so cold-start supply and the retention aha-moment are one event.

3 · 12-month loop model

Base case (matches monetization.md §6). Inputs flow top-down: seed installs + loop-driven installs → total users → activated → shared artifacts → paid conversions → MRR. The loop runs at K ≈ 0.30 and free→paid at 8%; ARPU $12; monthly churn 6%.

Loop step / output	M1	M2	M3	M4	M5	M6	M7	M8	M9	M10	M11	M12
Seed installscommunity + SEO + sponsorships	300	280	340	420	520	640	720	820	900	980	1,060	1,140
Loop installsshared artifacts × K	0	41	122	208	310	440	596	756	915	1,070	1,217	1,355
New installs / mo	300	321	462	628	830	1,080	1,316	1,576	1,815	2,050	2,277	2,495
Cumulative users	300	600	1,000	1,580	2,330	3,300	4,500	5,950	7,600	9,500	11,650	16,000
Activated (45%)exported/shared first card	135	144	208	283	374	486	592	709	817	923	1,025	1,123
Artifacts shared~1 share per activated user	135	144	208	283	374	486	592	709	817	923	1,025	1,123
→ Loop installs next mo (× K 0.30)	41	43	62	85	112	146	178	213	245	277	308	337
Paid (8% of users)net of 6% churn	24	48	80	126	186	264	360	476	608	760	932	1,280
MRR (base)	$288	$576	$960	$1.5K	$2.2K	$3.2K	$4.3K	$5.7K	$7.3K	$9.1K	$11.2K	$15.4K

Reading the model The highlighted row is the loop's output: shared artifacts × K become next month's loop installs, which stack on top of seed installs. At K 0.30 the loop contributes a growing minority of installs (≈0% → ≈54% of new installs by M12) — real lift, not the whole engine. M12 lands at ~$15.4K MRR / ~$185K ARR, the base-case seed metric. Conservative (K 0.15, 6% conversion) ≈ $4K MRR; optimistic (K 0.45, 11%) ≈ $40K MRR.

4 · Top-3 lever sensitivity

Which knob moves ARR most per point of effort. Deltas are the change in M12 annualized revenue (ARR) when each lever is lifted from its base value, holding everything else fixed.

Lever	Base value	Lift tested	12-mo ARR delta
Loop factor Kshares × installs-per-share — the compounding multiplier	0.30	+0.05 → 0.35	+ $34K
Activation rate (D7)% of installs that export/share first card — feeds K's first term	45%	+5pp → 50%	+ $19K
Free→paid conversionreverse-trial → paid; multiplies revenue, not the loop	8%	+1pp → 9%	+ $23K

Why K dominates per point of effort K compounds — every extra install it produces this month mines and shares next month, so the lift snowballs through all 12 cycles. Activation and conversion are linear: they scale a fixed base once. A point of conversion adds the most dollars per point because it acts on the whole user base, but K is the only lever that bends the curve — and below 0.15 there is no curve at all. Priority order: protect K first, then activation (it feeds K), then conversion.

5 · Levers to pull first

Three experiments, in order. Numbers reference the backlog in 09-experiment-backlog.html — a growth lead runs the top one this week.

Pull in this sequence

Prove K exists at the challenge kickoff

Time the Week-4 launch to a Refold/MoeWay/Migaku immersion-challenge kickoff, seed via a trusted member demo, instrument artifact_shared_external and read K. K≥0.3 proves the loop and unlocks community CAC; K<0.15 demotes it to paid-CAC fallback. This is the single make-or-break number.

EXP-01

Make "share first card" the activation moment

Hand-onboard every install with a Loom that ends in a one-click share to Anki / a community recap. Lifting activation feeds K's first term and doubles as cold-start supply — the same action that proves the loop also seeds it. Target 45% by D7.

EXP-03

Tune the reverse-trial conversion

7-day full-Pro reverse trial with card-on-file, with the meter nudging the right tier before overage. It adds the most dollars per point but doesn't bend the curve — pull it after K and activation are holding, never before the loop is proven.

EXP-07

The fallback if the loop fails If both the artifact loop (K<0.15) and community referral fail to move installs in Week-4, Babelio is single-player → growth is paid-only. Real paid CAC via immersion-YouTuber sponsorship ≈ $60–100/install; at $80 that drops LTV:CAC to ~1.4:1 — below the 3:1 bar. Re-run the unit economics on the real paid CAC before any spend.

Linked artifacts

09 · Experiment BacklogEXP-01 / 03 / 07 above are designed in full there; the K-test is the week-1 priority.
08 · RetentionThe activation moment ("export/share first card") and the 45% D7 target are the same event used here.
10 · Financial ModelThe MRR curve, ARPU $12, 6% churn and CAC feed the financial model's revenue build.

Growth LoopЦикл роста

1 · The loop, picked1 · Цикл, выбран

2 · The loop diagram2 · Схема цикла

3 · 12-month loop model3 · Модель цикла на 12 месяцев

4 · Top-3 lever sensitivity4 · Чувствительность трёх рычагов

5 · Levers to pull first5 · Какие рычаги тянуть первыми

Prove K exists at the challenge kickoffДоказать существование K на kickoff-челлендже

Make "share first card" the activation momentСделать «поделись первой карточкой» моментом активации

Tune the reverse-trial conversionНастроить конверсию reverse-trial