Find the growth loop

Memo: How Tutorly actually grows, and why I would not triple paid

To: Rachel Dunn, exec team From: Staff PM, Growth

Bottom line

1. Our engine is the organic search → profile → review loop. It is stalling at the review step, not at the top of the funnel.
2. Don't triple paid. The last $30k/month we added bought parents at about $319 each, against a $120 paid-parent LTV.
3. 50,000 by the raise isn't reachable with either plan. A credible number is about 41–43k, with a better quality story for diligence.

1. Growth loops

``` PRIMARY: Search/review loop (52% of new parents) Tutor profile -> bookings -> paid lessons -> 3+ reviews ^ | | v more tutors <- tutor earnings <- new parents <- organic profile sessions LEAK: 61% of new profiles get no booking in 60 days -> no reviews -> 4% of sessions

SECONDARY: Parent referral (9%) active parent -> 0.31 invites/mo -> 14% book -> new parent

SUPPLY FEED: Tutor referral (44% of new tutors, $50 at onboarding) -> more profiles

NOT A LOOP: Paid (39%) spend -> parent -> 22% still booking at 6 months. Stops when spend stops. ```

Why organic is primary. It is the largest source and has the best retention, and its output (reviews) feeds its own input (ranking and trust). It compounds for tutors who already have reviews. Profiles with 3+ reviews get 81% of organic sessions, and those with none get 4%.

Why it is weakening: - Tutors grew 62% against parents' 20%, so bookings per tutor fell from 9.1 to 6.8. - Most new supply never gets a first booking, so it never gets reviews or traffic. - Organic sessions grew 40% but parents only 20%. - Top-200-keyword click-through fell from 6.1% to 5.0% (−18%) after the results-page changes.

Parent referral is real but small. Each active parent yields about 0.043 new booking parents a month (0.31 × 14%). Even over 12 months that is about 0.5 per parent, so k is below 1 and it contributes rather than compounds. It is also cheap ($20 credit) and retains well, so it is worth improving.

Data flag: 37,000 parents × 0.043 implies about 1,600 referred parents a month. The 9% attribution implies roughly 150–190. One of these is wrong, and we must reconcile it before it appears in a Series B deck.

Tutor referral pays $50 for onboarding, not for a booking. At least 3,900 of last year's net 8,800 new tutors came this way, so we spent at least ~$190k buying supply that mostly isn't booked.

2. Response to tripling paid

The 2.2 isn't the paid ratio. It divides blended LTV ($210) by paid CAC ($95). Paid parents are worth $120, so paid LTV:CAC is 1.3 on average and 1.1 at the current $109.

The marginal number is worse. Spend went from $60k to $90k, and CPA went from $82 to $109: - New paid parents moved from about 732 to 826 a month. - So $30k bought about 94 extra parents, or roughly $319 each. That is 0.38× their LTV.

If the same curve holds (CPA scaling with spend^0.7, my extrapolation), $270k gives a CPA near $235 and about 1,150 parents a month. The extra $180k a month then buys about 320 parents, roughly $560 each.

The 50k math doesn't work: - We need +13,000 active parents in six months. Last year we added 6,000 in twelve. - Trend alone gets us to about 40k. - The extra ~$1.1M buys about 1,900 gross parents. With 22% still booking at six months, that is roughly +1,000 active parents at the raise, so about 41k. - Even with CPA frozen at $109, which won't happen, it is about 4–5k active and ~45k.

It also dilutes quality. Paid would rise from 39% to roughly 47% of new parents, and blended LTV would fall from $210 to about $195. Series B diligence will cut by source and cohort, and this is the cut that looks worst.

Caveats: this is one quarter of data. Seasonality, competitors and the CTR drop may explain part of the CPA rise. A holdout will tell us how much.

Recommendation: - Return paid to about $60k/month now. - Re-fund only campaigns where measured marginal CAC is ≤$60 (2:1 on $120). - Redeploy about $30k/month into the tests below. - Reframe the raise target as about 42k active parents, rising organic share, and recovering bookings per tutor. I would rather show that than 45k bought at 1.1×.

3. Squads for the next two quarters

Squad 1: New-tutor activation (fix the review leak)

• Test:
• Reserve a results/matching slot for quality-gated tutors with fewer than 3 reviews on new parents' first-lesson bookings.
• Fund a small first-lesson credit for the parent, from the redeployed paid budget.
• The credit is paid at booking, never conditioned on a review. Ask only neutral post-lesson review prompts. Legal should sign off before launch.
• Second arm: move the $50 tutor-referral payout from onboarding to the referred tutor's first completed lesson.
• Threshold:
• The 60-day first-booking rate for new profiles rises from 39% to ≥50% versus control.
• Routed first lessons' rebooking and ratings stay within 3 points of control.
• Cost per referred tutor who gets a booking falls ≥30%.
• Stop: the lift is under 5 points at week 6, or the rebooking/rating guardrail is breached. Then drop the routing and keep only the payout change if that arm hit its threshold.

Squad 2: Search recovery

• Test:
• First, serve the pre-March results layout to 20% of traffic to find out whether the March change caused the CTR drop.
• In parallel, improve snippets on the top 200 keywords (rating and review count, titles, structured data), with keyword-level holdouts.
• Threshold:
• Treated-keyword CTR is ≥5.6% by week 6 while holdouts stay near 5.0%.
• Session-to-booking conversion is flat or better.
• Restoring 6.1% is worth up to +22% clicks on those terms, which is our cheapest growth.
• Stop: under +0.3 points after two iterations (about 8 weeks), or conversion falls. Then move the squad to Squad 1's ranking work.

Squad 3: Parent referral and paid measurement

• Weeks 1–2: reconcile the referral attribution gap, and set up the paid holdout (geo or campaign-level) with analytics.
• Test:
• Trigger the invite prompt after a 5-star or third completed lesson.
• Run a two-sided $20 credit arm against the current one-sided credit.
• Threshold:
• Referred share of new parents rises from 9% to ≥13%.
• Cost per referred booking parent is ≤$45.
• 90-day retention is on track for ≥45% at six months.
• Stop: cost per referred parent exceeds $60, or invites per parent are under 0.36 after six weeks. Then cut referral work to maintenance and move the squad to first-90-day retention of paid cohorts (22% at six months is our biggest leak).

What I'd ask the offsite to decide

1. Cut paid back to $60k and fund the holdout.
2. Approve the squad plan and the tutor-referral payout change.
3. Accept about 42k as the committed target, and have finance model the raise story on retained parents, organic share and bookings per tutor.

I'd revisit paid at the end of Q1 with holdout data. If marginal CAC is ≤$60 in any segment, I'd scale it there.

MEMORANDUM

TO: Rachel Dunn, CEO; Executive Team FROM: Staff Product Manager DATE: October 24, 2023 SUBJECT: Growth Engine Analysis, Paid Acquisition Response, and H1 Squad Allocations

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Executive Summary

Tripling paid acquisition to $270k/month will not get us to 50,000 sustained booking parents for Series B. It relies on a metric illusion: our blended LTV is $210, but Paid LTV is only $120, while our marginal Paid CAC has already climbed to $109. Tripling spend will push marginal CAC well above LTV, burning cash to acquire low-intent parents who churn at more than double the rate of organic parents (22% vs. 48% 6-month retention).

Meanwhile, our true growth engine—the organic SEO/Review loop—is choking on a tutor supply glut that we are actively subsidizing. We must reallocate our squads to repair organic search distribution and tutor activation, turning our primary compounding loop back on before going out for Series B.

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1. Tutorly’s Growth Engine: Loop Mapping & Health

``` [Loop A: SEO / Review Loop (Primary Engine)] Parent books lesson ──> Completes paid lesson ──> Leaves review ▲ │ │ ▼ Organic search session ◄── Profile ranks higher / gains CTR

[Loop B: Parent Referral Loop (Secondary)] Active parent ──> Shares invite ($20 credit) ──> New parent books

[Loop C: Paid Acquisition (Linear/Diminishing)] Ad spend ($) ──> Paid clicks ──> First-time booking parent (High churn)

[Counter-Loop: Supply Glut / Dilution] $50 Tutor referral bounty ──> +62% Tutors ──> 61% zero-booking profiles │ │ ▼ ▼ Search dilution & drop in tutor earnings ◄── Suppressed profile liquidity ```

#### Loop Health & Classification

Why Loop A is Primary: Organic search generates 52% of our demand at superior economics ($260 LTV vs. $120 Paid). It is our only structurally compounding loop: bookings generate reviews, which improve search ranking and page conversion, generating more bookings. However, it is currently decaying due to supply misallocation and SERP degradation.

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2. Evaluating the Plan to Triple Paid Acquisition

Rachel's proposal states: "Our LTV to CAC is 2.2... Triple it to $270k a month and we hit 50,000 parents."

This relies on two critical errors:

1. The Blended LTV Fallacy: Rachel calculates LTV:CAC using blended LTV ($210) against historical blended CAC ($95) ($210 / $95 = 2.21$). But channel economics reveal a different reality: * Paid LTV is $120, driven by dismal 6-month retention (22%). * When we increased monthly spend from $60,000 to $90,000, our average Paid CAC rose from $82 to $109. * The marginal cost of those incremental acquisitions was: $$\text{Incremental CAC} = \frac{\$90,000 - \$60,000}{\Delta \text{Acquisitions}} = \frac{\$30,000}{\left(\frac{90,000}{109}\right) - \left(\frac{60,000}{82}\right)} = \frac{\$30,000}{825 - 731} \approx \$319$$ * At $109 average CAC against $120 LTV, current paid spend is barely breaking even ($1.1\times$). At $270k/month, Paid CAC will exceed Paid LTV on a fully loaded basis. 2. Quality of Growth for Series B: Pushing paid acquisition will inflate 30-day top-line numbers with unprofitable users who churn before the Series B diligence team reviews our cohorts. Series B investors will immediately spot cohorts decaying to 22% retention and discount our valuation.

Recommendation: Cap paid acquisition at $60,000/month (where CAC was sustainable at $82) and reallocate capital toward fixing marketplace liquidity and discovery.

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3. Squad Allocation for the Next Two Quarters

To reach 50,000 booking parents sustainably, we must fix our core SEO loop and activate idle supply. We allocate our three squads as follows:

``` ┌─────────────────────────────────────────────────────────────┐ │ Squad 1: Marketplace Liquidity & Cold Start │ │ Objective: Solve the 61% unbooked tutor barrier │ ├─────────────────────────────────────────────────────────────┤ │ Squad 2: Search Experience & Organic Distribution │ │ Objective: Reverse SERP CTR drop from 5.0% to >6.5% │ ├─────────────────────────────────────────────────────────────┤ │ Squad 3: Parent Retention & Referral Compounding │ │ Objective: Expand organic retention and boost referral K-factor│ └─────────────────────────────────────────────────────────────┘ ```

#### Squad 1: Marketplace Liquidity & Cold Start * Problem: 61% of new tutors get no bookings in 60 days, yielding 0 reviews. Unreviewed tutors capture only 4% of traffic. We are paying $50 to onboard tutors into dead ends, depressing utilization to 6.8 bookings/tutor. * Focus: Route high-intent parent demand to unreviewed, vetted tutors using new-tutor introductory match discounts (funded by retiring the $50 tutor referral bounty) and smart onboarding guarantees. * Test: Launch a "First Lesson Booking Guarantee" matching algorithm on category pages, pairing new vetted tutors with price-sensitive parents. * Threshold: $\ge$35% of newly onboarded tutors secure their first completed lesson within 14 days (up from <15%), achieving $\ge$1 review within 21 days. * Stop Condition: If introductory match initiatives do not lift first-booking rates within 60 days without reducing existing tutor earnings below 6.5 bookings/month, halt automated discounting and shift to a curated intake cap.

#### Squad 2: Search Experience & Organic Distribution * Problem: Organic search profile sessions grew +40%, but CTR on top 200 keywords plummeted from 6.1% to 5.0% (-18% relative) following recent SERP changes. This represents hundreds of lost bookings per week. * Focus: Audit and roll back damaging SERP redesigns; implement rich review schema markups; optimize localized long-tail tutor directory pages (e.g., "Math Tutors in [City]"). * Test: A/B test SERP layout rollback vs. a structured review-first layout displaying verified subject ratings and badge endorsements compliant with consumer review regulations. * Threshold: Restore top-200 keyword CTR to $\ge$6.2% within 8 weeks, yielding $\ge$15% incremental organic booking volume. * Stop Condition: If technical SERP changes fail to move CTR by $\ge$0.5 percentage points after 6 weeks of clean indexation, freeze front-end adjustments and redirect squad to on-site landing page conversion and booking-funnel friction.

#### Squad 3: Parent Retention & Referral Compounding * Problem: Paid parent retention is poor (22%), while referral parents yield $275 LTV and 51% retention. However, referral volume is constrained (only 0.31 invites/parent/month). * Focus: Embed referral prompts directly after high-satisfaction milestones (e.g., 5-star lesson completions) and introduce parent-to-parent study group mechanics rather than generic link-sharing. * Test: Introduce dynamic milestone-based referral prompts (post-5-star rating) offering dual-sided $25 credits, combined with an automated re-booking reminder cadence for churn-risk cohorts. * Threshold: Increase invite velocity from 0.31 to 0.50 invites/active parent/month, sustaining an invite-to-booking rate $\ge$14% (lifting referral share of new parents from 9% to 15%). * Stop Condition: If CAC via referral incentives exceeds $45 per booking parent, or invite rate does not cross 0.40 within 60 days, kill the programmatic milestone incentives and pivot to lesson package re-engagement.

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Series B Target Trajectory

By fixing our cold-start liquidity and reversing the SERP CTR loss, we will approach 47,000 highly retained, profitable booking parents. This presents a bulletproof Series B narrative: expanding gross margins, compounding organic discovery, and capital efficiency.