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Output
MEMORANDUM
TO: Sam Okoro, Head of Growth FROM: Product Manager, Pollen DATE: March 30, 2026 SUBJECT: Growth Analysis & Q3 Engineering Allocation
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1. Our Primary Growth Loop and Compounding Status
Pollen’s primary growth loop is the Viral Product-Led Growth (PLG) Badge Loop.
Here is how it functions: 1. Creation: A creator builds and publishes a form on Pollen. 2. Distribution: Creators send their forms out, generating an average of 120 respondents per form (40,000 forms $\times$ 120 = 4.8 million monthly respondent impressions). 3. Acquisition: 0.9% of those respondents click the "Made with Pollen" badge, and 11% of those clickers sign up. This currently yields approximately 4,752 sign-ups per month at zero media cost. 4. Activation & Retention: 38% of those sign-ups publish a form within 30 days, and 85% of those active creators retain into the following month, immediately re-feeding the top of the loop.
Is it compounding? Yes, it is structurally a compounding loop, but its current compounding velocity is fragile. Because our monthly creator retention is strong (78% overall, and 85% for badge cohorts), every cohort of users added to the system continually outputs thousands of new forms, generating millions of new respondent impressions month after month.
However, the loop’s current conversion efficiency means it is barely breaking even with natural churn. To accelerate compounding, we need to increase the velocity of respondents turning into active creators. That brings us to our Q2 engineering allocation.
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2. Where the Two Engineers Should Go
We have four ideas on the table. We should allocate both engineers to Idea 4: Replace the badge with 'Make a form like this' (Cloning Loop).
Here is why we must reject the other three: * Idea 1 (Double Paid Search): Generates 2,100 sign-ups at $38/ea ($79.8k/month additional spend). While profitable over a 14-month Pro lifespan (9% conversion $\times$ $20/mo $\times$ 14 mos = $25.20 LTV vs. $38 CAC—wait, our LTV is actually around $252, making CAC look fine on paper), paid search yields lower activation (21%) and worse retention (64%) than organic loops. It is linear growth, not compounding. * Idea 2 (200 SEO Template Pages): Good, but it relies on static editorial content. It lacks a viral coefficient and has a lower activation rate (14%) and month-2 retention (71%) than the badge loop. * Idea 3 (Referral Programme): A $10 Pro credit is structurally misaligned for a product where 91% of our base is on a free tier. Free users cannot easily utilize Pro credits, rendering this incentive largely inert for the vast majority of our creators.
Why Idea 4 is the clear winner: The pilot data for "Make a form like this" is exceptional. By reducing friction and showing respondents a working replica of the exact form they just successfully interacted with, we saw: * Badge clicks nearly doubled: From 0.9% to 1.6%. * Sign-up rate held steady: 11% conversion. * Activation surged: 52% of sign-ups published within 30 days (up from 38% on the old badge).
This isn't just an incremental tweak; it transforms our passive watermark into an active, high-intent replication engine. It directly attacks the weakest link in our primary loop (activation) while supercharging top-of-funnel discovery.
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3. How We Will Know It Worked (Success Metrics)
We will roll this out to 100% of published forms on day one of the quarter. We will measure success across three core KPIs over a 60-day post-launch window:
- Primary Metric (Loop Velocity): Monthly Free-to-Published Creator conversion from badge traffic. Target: A sustained lift in 30-day activation from the baseline 38% toward the pilot’s 52% benchmark.
- Secondary Metric (Top-of-Funnel Conversion): Respondent-to-sign-up volume. Target: Maintain or exceed the pilot's 1.6% click-through rate across our full 4.8M monthly respondent pool, yielding ~8,400 sign-ups/month from the badge alone (nearly double current output).
- Downstream Revenue Impact: Monthly Recurring Revenue (MRR) added via Pro upgrades from this specific acquisition channel. Target: Since 9% of publishing creators upgrade to Pro ($20/mo), the uplift in activated creators from this loop must translate directly to an accelerated net-new Pro ARR growth rate compared to Q1.
Put both engineers on Idea 4. Let's compound the loop.
Grades and run details
Decision model 32
Decision model checks
- failUses the supplied evidence correctly80%
- partialAddresses the actual decision36%
- failRespects explicit constraints81%
- failIdentifies material uncertainty44%
- failAvoids unsupported claims95%
- partialProduces the required deliverable70%
- partialCalls out the paid maths54%
- partialPicks the lever with the most yield99%
- passA closed loop, not a channel25%
- failThe loop maths holds95%
- partialProposes tests that could fail53%
Run
- Run
- #1
- Time to output
- 6 s
- Submitted
- 2 Oct 2026