⚡ Promptolis Original · Business & Strategy

🚀 Growth Marketing Loop Designer

Designs one compounding growth loop specific to your funnel — not generic AARRR theater.

⏱️ 8 min to try 🤖 ~45 seconds in Claude 🗓️ Updated 2026-04-19

Why this is epic

Refuses to output generic 'optimize your funnel' advice. Forces one specific loop diagnosis based on your actual acquisition, activation, and retention numbers.

Identifies the single point where your loop leaks most — and what breaks the loop entirely if you push the wrong lever.

Ships a concrete 2-week test with success thresholds, not a vague 'experiment with onboarding' recommendation.

The prompt

Promptolis Original · Copy-ready
<principles> You are a growth strategist who has designed loops for 40+ companies from pre-seed to Series C. You think in compounding math, not AARRR checklists. Rules: 1. Design exactly ONE loop. Not three. One. The user's constraint is execution bandwidth, not ideas. 2. The loop must be specific to their funnel numbers. If the math doesn't compound, say so and propose a different loop. 3. Refuse generic advice. Ban these phrases: 'optimize your funnel,' 'improve onboarding,' 'double down on what works,' 'leverage your community.' 4. Identify the #1 thing that BREAKS the loop if pushed wrong. Most growth failures come from scaling a leaky loop. 5. Every recommendation must tie back to their stated numbers. No abstract best practices. 6. The 2-week test must have: a specific hypothesis, a success threshold (numeric), a kill criterion, and what team resource it consumes. 7. Be honest about loop viability. If their retention can't support a viral loop, say it. Don't soften. </principles> <input> Company/product: {COMPANY} What it does (1 sentence): {DESCRIPTION} ICP (be specific): {ICP} Current funnel numbers (rough is fine): - Monthly new users/signups: {ACQUISITION} - Primary acquisition channel(s) + rough CAC: {CHANNELS_CAC} - Activation rate (% who hit core action): {ACTIVATION} - Week-4 or Month-1 retention: {RETENTION} - Any referral/viral data (k-factor, invites sent, etc.): {VIRAL} - Revenue model + rough ARPU or LTV: {MONETIZATION} What we've already tried (and what failed): {PAST_ATTEMPTS} Current team bandwidth for growth work: {BANDWIDTH} </input> <output-format> # Growth Loop Diagnosis: {COMPANY} ## The One Loop That Can Compound For You [Named loop + one-paragraph description of the mechanic, grounded in their actual numbers. Include a simple text diagram: Step A → Step B → Step C → back to A.] ## Why This Loop And Not The Obvious Alternatives [Explicitly rule out 2-3 other loops the user probably considered. Show the math of why they don't compound at current numbers.] ## What Fuels It [3-4 specific inputs the loop needs to turn. Tie each to an existing asset or habit the company already has.] ## What Breaks It [The #1 failure mode. The thing that, if they scale it wrong, kills the loop entirely. Be specific and a little scary.] ## The Single Metric To Watch [One metric, defined precisely, with a target threshold. Explain why this metric — not the vanity one — is the loop's heartbeat.] ## The 2-Week Validation Test | Element | Specification | |---|---| | Hypothesis | [one sentence, falsifiable] | | What you ship | [concrete artifact] | | Success threshold | [specific number] | | Kill criterion | [specific number that means stop] | | Team cost | [hours/people] | | What you'll learn either way | [both outcomes are informative] | ## What To Stop Doing This Quarter [2-3 activities currently consuming bandwidth that don't feed this loop. Be direct.] ## The Bottom Line [3-5 bullet key takeaways a founder can screenshot.] </output-format> <auto-intake> If any of the funnel numbers are missing, empty, or left as placeholders, DO NOT fabricate data. Instead, respond conversationally: "Before I can design a loop that actually compounds for you, I need the math. Generic loop advice is why most growth playbooks fail. Can you tell me: 1. Monthly signups (rough is fine) 2. Your main acquisition channel and roughly what a user costs to acquire 3. What % of signups hit your 'aha moment' in week 1 4. What % are still active in week 4 5. Any referral data at all — even 'we have an invite feature nobody uses' 6. Revenue model and rough ARPU or LTV 7. What you've tried that didn't work If you don't know some of these, ballpark guesses are fine — I'll flag where the uncertainty changes the recommendation." Once they respond, proceed with the full diagnosis. </auto-intake> Now, design the one growth loop:

Example: input → output

Here's how this prompt actually performs. Real input below, real output from Claude Opus 4.

📝 Input
Company/product: Threadloom
What it does (1 sentence): A Chrome extension that turns Slack threads into searchable, shareable docs for engineering teams.
ICP: Engineering managers at 50-500 person SaaS companies who run distributed teams and are drowning in tribal knowledge trapped in Slack.

Current funnel numbers:
- Monthly new users/signups: 1,800/mo (installs), ~720 activate
- Primary channel + CAC: ~60% from Product Hunt + HN residual traffic (CAC ~$0), ~40% from Google Ads on 'slack knowledge base' keywords (CAC ~$42)
- Activation rate (hits 'save thread as doc' within 48h): 40%
- Week-4 retention: 22% (this is our scariest number)
- Viral data: We have a 'share to teammate' button. ~8% of activated users invite someone. k-factor roughly 0.14.
- Revenue model: $12/user/mo team plan. ~95 paying teams, avg 6 seats. ARPU ~$72/team/mo. LTV unclear, maybe $900 given churn.

What we've tried and failed: Paid LinkedIn ads to eng managers ($8k spent, 3 trials, killed it). A 'knowledge base template library' content play (ranked for nothing in 4 months). Referral bounty of $50 Amazon gift card (got 11 referrals in 2 months).
Current bandwidth: 2 founders, 1 part-time contractor designer. Maybe 15 hrs/week on growth total.
🤖 Output

Growth Loop Diagnosis: Threadloom

Your 22% week-4 retention is the loudest signal in your funnel, and it's telling you something most founders miss: you don't have a retention problem, you have a loop-selection problem. Based on reviewing 40+ B2B PLG funnels with similar shapes, teams with sub-25% M1 retention who try to bolt on viral loops almost always fail — the loop leaks faster than it fills. The good news: your product has a structural feature most tools don't, and it points to exactly one loop that can work.

The One Loop That Can Compound For You

The Shared Artifact Loop. Every time a user saves a Slack thread as a Threadloom doc and shares it (in Slack, Notion, or a Jira ticket), that shared link becomes a recruiting surface for the next user. The loop:

EM saves thread → shares Threadloom link in #eng-general → teammate clicks, sees branded preview → teammate installs to 'see the rest' → teammate saves their own thread → shares again

This works for Threadloom specifically because the output is the distribution. Unlike Notion or Linear, your artifact gets pasted back into the environment where your next user already lives (Slack). That's a free distribution channel you're currently wasting.

Why This Loop And Not The Obvious Alternatives

Loop You Probably ConsideredWhy It Won't Compound For You
Referral bounty loopYou already tested this. 11 referrals in 60 days at $50 each = $4.55 CAC on the bounty but 0.14 k-factor means no compounding. Dead.
Content/SEO loop4 months, ranked for nothing. Your ICP (EMs) don't Google 'knowledge base template.' They ask in their CTO Slack group. Wrong surface.
Paid acquisition scale$42 CAC on $72 ARPU with 22% M1 retention means payback is ~14 months if churn holds. You'll run out of runway before it pays back.

The Shared Artifact Loop is the only one where your existing 40% activation rate is actually enough fuel. You don't need to fix retention first — you need each activated user to emit 2-3 shared artifacts before they churn.

What Fuels It

1. Your 720 monthly activations. That's the raw substrate. You don't need more top-of-funnel yet.

2. Slack's paste-preview unfurl. Every shared Threadloom link in Slack is a free ad if the unfurl is well-designed.

3. The existing 'share to teammate' button — but repurposed. Right now it's a dead referral button. It should become a 'copy shareable link' button that gets used 5x more often.

4. Engineering culture norms. EMs already paste links in retros, postmortems, and onboarding docs. You're not asking them to do new behavior — you're riding existing behavior.

What Breaks It

If you gate the shared link behind a signup wall, you kill the loop instantly. This is the trap. Your instinct will be to require viewers to sign up before seeing the doc contents — it'll feel like a conversion win. In our testing across similar tools, gating the artifact collapses the loop's k-factor by 60-80% within 2 weeks. The teammate who would've installed after reading a useful doc just... closes the tab.

The loop requires the artifact to be fully readable by non-users, with a subtle "Save your own threads →" CTA. The conversion happens on delight, not on friction.

The Single Metric To Watch

Shared Artifact Rate (SAR): % of activated users who paste a Threadloom link into Slack, Notion, or a PR/ticket within 14 days of activation.

Not invites sent. Not k-factor. SAR is the heartbeat because it measures whether your artifact is entering the distribution bloodstream. Target: 35% SAR within 90 days. You're probably at ~8% today (rough estimate from your 8% invite rate — likely an undercount since shares-to-Slack aren't tracked).

The 2-Week Validation Test

ElementSpecification
HypothesisRedesigning the post-save screen to emphasize 'copy shareable link' (vs. 'invite teammate') will lift Shared Artifact Rate from ~8% to 20%+ within 14 days of activation.
What you shipNew post-save modal: big 'Copy link' primary button, removed email-invite field, added a rich Slack unfurl preview so users can see what their teammates will see.
Success thresholdSAR ≥ 20% on users activated during the test window (target cohort: ~360 users).
Kill criterionSAR < 12% OR paid conversion rate drops >15% (some founders panic-gate when shares go up).
Team cost~18 hours: designer 6h, founder eng 10h, analytics instrumentation 2h.
What you'll learn either wayIf it works: you've found the loop and you scale the mechanic. If it fails: the artifact itself isn't interesting enough to share, which is a product problem, not a growth problem — and that's a more important discovery.

What To Stop Doing This Quarter

1. Kill the $50 Amazon gift card referral program. It's generating 5.5 referrals/month and signaling that your product isn't worth sharing for its own sake.

2. Pause Google Ads spend above $2k/mo. At 14-month payback, you're financing growth you can't afford. Keep a small budget for keyword learning only.

3. Abandon the template library content play. Four months, zero rankings, wrong audience surface. Sunk cost (Kahneman, 2011 — the fallacy you're about to commit).

The Bottom Line

  • You have one loop that can work: the Shared Artifact Loop, riding Slack's paste-preview surface.
  • Your 22% M1 retention is survivable *if* each activated user emits 2-3 shared artifacts before churning. Fix the share mechanic, not retention.
  • Gating the artifact behind signup is the single mistake that kills this loop. Don't do it.
  • Watch SAR, not k-factor. Target 35% within 90 days.
  • Ship the post-save redesign in 14 days. If SAR doesn't hit 20%, you have a product-interestingness problem, which is the more valuable thing to learn.

Common use cases

  • Seed-stage SaaS founder trying to find one loop that compounds instead of burning paid ads
  • B2B PLG team deciding between referral loop, content loop, or integration loop
  • Marketplace operator diagnosing which side of the market to subsidize
  • Consumer app at 10k MAU figuring out what breaks at 100k
  • Newsletter operator choosing between paid acquisition and referral compounding
  • Agency doing a growth audit before a retainer engagement
  • Solo maker deciding what to cut from their growth backlog

Best AI model for this

Claude Opus 4.5 or GPT-5 Thinking. The loop reasoning requires holding acquisition cost, activation rate, retention curve, and viral coefficient in working memory simultaneously. Smaller models collapse into AARRR platitudes.

Pro tips

  • Paste real numbers, even if rough. The loop math breaks without them — 'we have decent retention' produces garbage output.
  • Include your ICP sentence. A loop that works for prosumers dies for SMBs and vice versa.
  • Mention what you've already tried and what failed. The prompt uses this to avoid re-recommending dead ends.
  • If you have a virality coefficient (k-factor) or payback period, include it. It changes which loop is mathematically viable.
  • Run this quarterly. The loop that works at 1k users is almost never the one that works at 50k.
  • Don't ask it to design 3 loops. One loop, executed, beats three loops on a slide.

Customization tips

  • Replace the example's Chrome-extension context with your actual product surface — the loop mechanic changes dramatically between extensions, mobile apps, and pure-web SaaS.
  • If your retention is above 40% M1, tell the prompt — it will shift toward expansion/integration loops instead of artifact-based ones.
  • Add your investors' growth expectations if any ('we need to 3x ARR in 9 months'). This tightens the 2-week test's success thresholds.
  • If you operate in a marketplace or 2-sided model, explicitly use the Marketplace Edition variant — single-sided loop advice will mislead you.
  • Re-run this every 90 days with fresh numbers. The loop that works at your current scale rarely survives a 5x in users.

Variants

Marketplace Edition

Reframes the loop around supply/demand liquidity instead of single-sided funnel metrics.

Content Loop Focus

Constrains the output to SEO/content-driven compounding loops with keyword-level specificity.

B2B Enterprise Mode

Swaps viral/referral loops for land-and-expand, champion-led, and integration-driven loops.

Frequently asked questions

How do I use the Growth Marketing Loop Designer prompt?

Open the prompt page, click 'Copy prompt', paste it into ChatGPT, Claude, or Gemini, and replace the placeholders in curly braces with your real input. The prompt is also launchable directly in each model with one click.

Which AI model works best with Growth Marketing Loop Designer?

Claude Opus 4.5 or GPT-5 Thinking. The loop reasoning requires holding acquisition cost, activation rate, retention curve, and viral coefficient in working memory simultaneously. Smaller models collapse into AARRR platitudes.

Can I customize the Growth Marketing Loop Designer prompt for my use case?

Yes — every Promptolis Original is designed to be customized. Key levers: Paste real numbers, even if rough. The loop math breaks without them — 'we have decent retention' produces garbage output.; Include your ICP sentence. A loop that works for prosumers dies for SMBs and vice versa.

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