Find the growth loop

To: Rachel Dunn and the exec team From: Staff PM Re: How we grow, and the plan to triple paid

Bottom line

Our main growth engine is search and reviews, and it is leaking at the entry point. New tutors aren't getting booked, so they don't get reviews, so they don't rank. Tripling paid would add roughly $1.1M of spend over six months, bring in perhaps 2,000 to 3,000 extra parents, and still leave us well short of 50,000. I recommend holding paid at $90k a month and putting the next two quarters into fixing the primary loop.

1. How we actually grow

``` PRIMARY: SEARCH + REVIEWS New tutor profile → first booking → completed paid lesson → review ▲ (61% of new profiles: no booking in 60 days) │ Organic parent ← search ranking ← 3+ reviews (81% of organic profile sessions) ←┘ │ └→ books → completed lesson → (loop repeats)

REFERRAL (PARENTS) Booking parent → 0.31 invites/mo → 14% book → new parent → invites

SUPPLY (TUTOR REFERRAL) Tutor → refers tutor → onboarding ($50) → new tutor → needs bookings

PAID (NO LOOP) Spend → paid click → new parent → 22% still booking at six months ```

Why search and reviews is primary: it is the largest source, it carries no per-parent cost, and it is the only loop that gets stronger as reviews accumulate. Profiles with three or more reviews get 81% of organic profile sessions; profiles with none get 4%.

Where it's leaking: - 61% of profiles created in the last six months had no booking within 60 days, so they never accumulate reviews. - Click-through on our top 200 keywords fell from 6.1% to 5.0% (−18%) after the March results-page changes. Organic sessions are up 40%, but that growth is concentrated in established profiles. - Supply grew 62% (14,200 to 23,000 active tutors), while bookings per active tutor fell from 9.1 to 6.8 a month (−25%). Total monthly bookings rose only about 21% (129k to 156k, my calculation). At 18% of $40, net revenue went from about $0.93M to $1.13M a month. We are growing supply faster than we are converting it.

Two numbers to correct before the offsite: - The 2.2 LTV:CAC mixes two different things. It divides blended LTV ($210) by average CAC ($95). Paid parents are worth $120 in LTV. At today's marginal paid CAC of $109, paid returns about 1.1x, not 2.2x. - Referral data doesn't reconcile. Each active parent sends 0.31 invites a month and 14% of invites book, which is about 0.043 new parents per active parent. Across 37,000 active parents, that implies roughly 1,600 referred parents a month. The reported 9% share implies roughly 200 a month, given paid's ~800 new parents a month at 39% of the mix. One of these figures is wrong by roughly 8x. We should not scale referral spend until attribution is fixed.

2. The plan to triple paid

• The gap is large. Reaching 50,000 means +13,000 parents (+35%) in six months. Over the last twelve months we added a net 6,000.
• Costs rise faster than spend. Raising spend 50% ($60k to $90k) pushed CAC up 33% ($82 to $109). If that curve holds, tripling spend implies a CAC of roughly $200 to $235. This is a rough extrapolation, and marginal CAC is probably higher.
• The output is small. Tripling adds roughly 320 to 520 parents a month, or 2,000 to 3,000 over six months, for about $180k more spend each month. At 22% six-month retention, no more than about 700 of those would still be booking at the end.
• The realistic outcome is 40,000 to 42,000 by month six, on current trend plus the squad plan. That is my estimate, and it assumes no step-change in organic growth.

Recommendation: Do not triple. Hold paid at $90k a month. Pause any campaign or keyword whose CAC is above $120, since that is roughly the break-even point on its own LTV. Report paid on marginal CAC and payback, not blended LTV:CAC. Redirect the freed budget to referral credits and search fixes.

3. Where the three squads should go

Squad 1: Reviews and first bookings (primary loop entry) - Test: Give zero-review profiles a first-booking boost in search and discovery, using non-review signals such as verified credentials, availability, and response time. Automatically prompt parents to review after each completed paid lesson, with no incentive attached. Move the $50 tutor referral payout from onboarding to first completed booking. - Threshold: Share of new profiles booked within 60 days rises from 39% to 50% or more by the end of Q1. Review rate on completed lessons rises 20% relative to a baseline we measure in week one. - Stop: No lift in first-booking rate after eight weeks, or cancellations or complaints on boosted profiles worse than control.

Squad 2: Search click-through recovery - Test: A holdout on the top 200 keywords that reverts the March results-page changes for half the keywords, while testing profile snippet and structured-info variants on the rest. - Threshold: Click-through back to 5.6% or higher within eight weeks (recovering about half the drop), and 6.1% by the end of Q2. - Stop: No recovery after two test cycles, or organic bookings per session falling.

Squad 3: Parent referral (cheapest acquisition) - Test: First, reconcile referral attribution in weeks one and two. Then test a review-free prompt after a parent's first completed lesson, and a $30 versus $20 referrer credit. Credits reward bookings, not reviews, so this stays within our rules. - Threshold: Referral share of new parents rises from 9% to 12% by the end of Q2, with an all-in cost per referred booker under $40 (against $109 for paid). - Stop: Invite-to-booker conversion stays below 14% after eight weeks, or cost per referred booker exceeds $40.

Paid stays with the existing team and is not one of the three squads.

4. Decisions for the offsite

1. Reject tripling. Hold paid at $90k a month with a $120 CAC ceiling.
2. Reset the 50,000 target. Commit to about 42,000 at the raise and show investors marginal paid CAC, bookings per active tutor, and organic share of new parents. A smaller number with clean unit economics is a stronger story than a target that paid spend cannot reach.
3. Fix referral attribution this week before any referral spend is scaled.

To: Rachel Dunn and executive team From: Staff PM, Tutorly Subject: Grow completed lessons and repeat demand—not acquisition spend Decision requested: Do not triple paid acquisition. Allocate the three squads to organic conversion, marketplace activation, and parent referrals for the next two quarters.

1. How Tutorly actually grows

Our primary growth mechanism is successful lessons generating review-rich profiles that attract more parents. Paid acquisition feeds this mechanism; it is not itself a compounding loop.

```text PRIMARY: ORGANIC / REPUTATION Organic discovery → parent books → completed paid lesson → parent review ↑ ↓ └──────── stronger public profile / discovery ──────┘ ↓ repeat paid lessons

PARENT REFERRAL Booking parent → invitation → new booking parent → further invitations └──────────────── repeat lessons ──────────────────┘

TUTOR SUPPLY Tutor → tutor referral → onboarding → more available tutors ↓ [only valuable if matched to demand] ↓ lessons and tutor earnings

PAID INPUT Spend → new booking parent → lessons, reviews, repeat bookings and referrals ↑ ↓ └──────────────── reinvestable contribution ─────────────────────────┘ ```

Organic/reputation: primary, compounding in structure—but constrained

Organic supplies 52% of new booking parents, with 48% still booking at six months and $260 net LTV. Profiles with at least three reviews receive 81% of organic profile sessions; reviewless profiles receive only 4%. Successful transactions can therefore create an asset that attracts subsequent transactions.

However, this is evidence consistent with the loop—not proof that reviews alone cause traffic. Established tutors may differ in other ways.

The loop has two leaks:

• 61% of profiles created in the last six months had no booking within 60 days. Without a completed paid lesson, they cannot earn reviews.
• Search CTR on our top 200 keywords fell from 6.1% to 5.0%, an 18% relative decline. Restoring it would mean 22% more clicks at unchanged impressions, not necessarily 22% more bookings.

Organic sessions grew 40%, but we lack channel-specific booking-conversion history to establish whether the loop’s yield improved. This is our strongest compounding mechanism, not an unlimited growth engine.

Parent referrals: contributing, not demonstrated to be self-sustaining

Each active parent generates 0.31 × 14% = 0.0434 new booking parents per month. At 37,000 active parents, that is approximately 1,606 gross acquisitions monthly, assuming those rates hold.

A parent active for all six months would generate only 0.26 direct recruits in that period. We cannot calculate lifetime reproduction without active-lifetime data; current evidence does not establish a self-sustaining viral loop.

Nevertheless, referrals provide 9% of new booking parents, 51% six-month retention, and $275 net LTV—our best observed acquisition quality. The $20 credit is an incentive cost, not fully loaded CAC.

Tutor referrals: contributing supply, with decaying productivity

Tutor referrals generated 44% of new tutors, at $50 per completed onboarding. But onboarding does not create parent demand.

Active tutors rose 62%, versus 20% growth in booking parents. Monthly bookings per active tutor fell 25%, from 9.1 to 6.8. Multiplying the supplied figures implies total monthly bookings rose only about 21%. We are spreading demand across substantially more supply.

At $7.20 commission per lesson, monthly platform commission per active tutor fell from approximately $66 to $49, before costs. This is declining supply productivity, not proof that tutor-referral reproduction itself is shrinking. Broad supply recruitment should stop being a growth objective.

Paid: contributing acquisitions, decaying marginal efficiency

Paid contributes 39% of new booking parents, but only 22% remain booking after six months, with $120 net LTV. Its reinvestment loop has very little demonstrated surplus at current acquisition costs.

2. Why we should not triple paid

The quoted 2.2 LTV:CAC is $210 blended LTV divided by $95 paid CAC. It mixes populations. For paid parents, the historical ratio is $120/$95 = 1.26; at the latest CAC, it is $120/$109 = 1.10.

The recent spend increase is more concerning:

• $60,000 at $82 CAC bought approximately 732 parents/month.
• $90,000 at $109 bought approximately 826.
• The additional $30,000 bought only 94 additional parents: approximately $320 marginal CAC.

That is an observational comparison, potentially affected by seasonality or mix—not a controlled estimate. It nevertheless argues against extrapolating the average CAC into a tripling.

Even assuming CAC stays at $109, $270,000 buys approximately 2,477 gross new parents/month. The increase over current spend buys about 9,900 additional parents over six months, before attrition. That does not independently close the 13,000 monthly-active-parent gap. Organic growth and reactivation may help, but acquisition totals are not active-parent totals.

Recommendation: Cap paid at no more than $90,000 monthly and remove unprofitable marginal campaigns now. Marketing, Finance and Analytics should run incrementality tests and build a source-specific cohort bridge: retained existing parents + retained acquisitions + reactivations = monthly booking parents.

For further scaling, propose a 1.5× net-LTV/incremental-CAC hurdle—CAC no greater than $80 at today’s paid LTV—with cash-payback visibility. This is a proposed risk buffer, not an observed benchmark. Earn increases in small steps; do not fund them against blended LTV.

3. Three squads, two quarters

The thresholds below are proposed decision rules. Pre-register cohort definitions, sample sizes and retention guardrails. Quarter one establishes causality; quarter two scales only passing treatments. Do not wait six months for every decision: use 60-day repeat booking as an interim guardrail, then validate mature cohorts.

Squad 1 — Organic discovery to first booking

Test: Diagnose the CTR decline, distinguishing search-engine changes from our own changes. Use matched query/page cohorts to test truthful snippets, relevant profile information and booking-path improvements. Do not assume we control external search-result layouts.

Threshold: At least 15% more first-booking parents per eligible organic impression versus control, without worse 60-day repeat booking. CTR recovery toward 6.1% is diagnostic, not the success metric.

Stop: End unsuccessful variants after a powered test, capped at 12 weeks; stop earlier for material booking or quality harm. In quarter two, expand winners across qualified profiles.

Squad 2 — First-lesson liquidity, not tutor headcount

Test: In demand-constrained categories/geographies, match suitable new tutors to genuine parent needs using availability, fit and booking support. Pause broad tutor-onboarding bounties; retain exceptions only for demonstrated supply gaps. Request honest reviews neutrally after completed paid lessons—never reward reviews.

Threshold: Reduce new-profile 60-day no-booking rate from 61% to 45% or below, while increasing total completed lessons per exposed parent by at least 10% and maintaining cancellation and repeat-booking quality.

Stop: Stop if activation merely redistributes existing bookings without increasing total lessons, or requires negative-contribution subsidies. Evaluate the first matured cohort in quarter one; scale only incremental wins in quarter two.

Squad 3 — Parent referrals after successful lessons

Test: Randomize referral prompts following successful lessons, simplify sharing and redemption, and retain the existing $20 booking-triggered credit.

Threshold: Increase invite-to-book yield from 0.0434 to at least 0.065 per active parent-month, with positive incremental contribution after credits and no deterioration in 60-day repeat booking.

Stop: Stop by week 12 if lift is attribution switching rather than incremental acquisition, economics fail, or fraud increases. Expand successful treatments in quarter two and validate six-month retention.

Bottom line: Our scarce resource is durable parent demand. Strengthen the transaction-to-reputation loop, improve matching, and amplify satisfied parents before buying substantially more low-retention traffic.