Evaluate acquisition channels using unit economics, customer quality, and scalability. Use when deciding whether to scale, test, or kill a growth channel.

Purpose Guide product managers through evaluating whether to scale, test, or kill an acquisition channel based on unit economics (CAC, LTV, payback), customer quality (retention, NRR), and scalability (magic number, volume potential). Use this to make data driven go to market decisions and optimize channel mix for sustainable growth. This is not a channel strategy framework—it's a financial lens for channel evaluation that helps you avoid scaling unprofitable channels or killing channels with fixable problems. Use when deciding how to allocate marketing budget across channels. Input Works best with: The acquisition channel you're evaluating (e.g., paid search, outbound SDR, partner referrals). Also useful: Any metrics you already have — CAC, LTV, payback period, retention/NRR by channel — plus company stage and the decision on the table (scale, test, or kill). Anything supplied with the invocation itself — text after the skill name, a pasted context dump, or an appended ARGUMENTS: line — counts as answers already given. Use it and skip whatever it covers; don't re ask. Arriving empty handed? That works too. The advisor opens by asking which channel you're evaluating and what data you have. Example invocation: Evaluate our paid LinkedIn channel: CAC $2,400, LTV $9,000, 14 month payback, flat retention vs. organic. Key Concepts The Channel Evaluation Framework A systematic approach to evaluate acquisition channels: 1. Unit Economics — What does it cost to acquire, and what's the return? CAC (Customer Acquisition Cost) LTV (Lifetime Value) LTV:CAC ratio Payback period 2. Customer Quality — Do customers from this channel stick around and expand? Cohort retention rate (by channel) Churn rate (by channel) NRR (Net Revenue Retention by channel) Expansion rate 3. Scalability — Can this channel sustain growth at the volume you need? Magic Number (S&M efficiency) Addressable volume (TAM of channel) Saturation risk (diminishing returns) CAC trend (increasing, stable, decreasing) 4. Strategic Fit — Does this channel align with your go to market strategy? Customer segment match (SMB vs. enterprise) Sales motion compatibility (PLG vs. sales led) Brand positioning alignment Decision Matrix LTV:CAC Payback Customer Quality Scalability Decision 3:1 <12mo Good retention High volume Scale aggressively 2 3:1 12 18mo Average retention Medium volume Test & optimize <2:1 18mo Poor retention Low volume Kill or fix Anti Patterns (What This Is NOT) Not vanity metrics: "We got 10,000 signups!" means nothing if they churn in 30 days Not CAC only thinking: Low CAC with terrible retention is worse than high CAC with great retention Not ignoring payback: 5:1 LTV:CAC with 36 month payback is a cash trap Not scaling broken channels: Pouring money into inefficient channels accelerates failure When to Use This Framework Use this when: Evaluating whether to scale a new channel (content, paid, events, etc.) Deciding how to allocate marketing budget across channels Assessing whether to kill an underperforming channel Comparing channels to optimize ROI Planning annual marketing budget allocation Don't use this when: Channel is brand new (<3 months, <100 customers) — not enough data You're testing channel fit (this is for evaluation, not experimentation) Strategic channels (e.g., enterprises require field sales regardless of CAC) You don't have channel level data (need to track CAC, retention by source) Facilitation Source of Truth Use [ workshop facilitation ](../workshop facilitation/SKILL.md) as the default interaction protocol for this skill. It defines: session heads up + entry mode (Guided, Context dump, Best guess) one question turns with plain language prompts progress labels (for example, Context Qx/8 and Scoring Qx/5) interruption handling and pause/resume behavior numbered recommendations at decision points quick select numbered response options for regular questions (include Other (specify) when useful) This file defines the domain specific assessment content. If there is a conflict, follow this file's domain logic. Application This interactive skill asks up to 4 adaptive questions , offering 3 5 enumerated options at decision points. Step 0: Gather Context Agent asks: "Let's evaluate this acquisition channel. Please provide: Channel details: Channel name (e.g., Google Ads, content marketing, outbound sales, partnerships) How long have you been using this channel? (months) Current monthly spend on this channel Customer acquisition: Customers acquired per month (from this channel) CAC for this channel (if known, otherwise we'll calculate) Business context: Blended CAC (across all channels) Blended LTV Current MRR/ARR Target growth rate (% MoM or YoY) You can provide estimates if you don't have exact numbers." Step 1: Evaluate Unit Economics Agent calculates (if not provided): Agent asks: "Now let's compare this channel's unit economics to your blended metrics. Channel Unit Economics: Channel CAC: $ Blended CAC (all channels): $ Channel LTV: $ (if known; otherwise we'll use blended LTV as proxy) Blended LTV: $ Questions: 1. Do customers from this channel have similar LTV to other channels? Similar (use blended LTV) Higher (they upgrade more, stick around longer) Lower (they churn faster or are smaller deals) Unknown (need to analyze cohort data) 2. What's the payback period for this channel? We can calculate: CAC / (Monthly ARPU × Gross Margin %) Or you can provide it" Based on answers, agent calculates: LTV:CAC ratio for channel Payback period Comparison to blended metrics Agent flags: ✅ If LTV:CAC 3:1 and payback <12 months: "Strong unit economics" ⚠️ If LTV:CAC 2 3:1 or payback 12 18 months: "Marginal unit economics" 🚨 If LTV:CAC <2:1 or payback 18 months: "Poor unit economics" Step 2: Assess Customer Quality Agent asks: "How do customers from this channel perform compared to other channels? Retention & Expansion: 1. What's the churn rate for customers from this channel? Lower than blended (they stick around longer) Same as blended (no difference) Higher than blended (they churn faster) Unknown (need cohort analysis) 2. What's the NRR for customers from this channel? Higher than blended (they expand more) Same as blended (no difference) Lower than blended (they contract or churn more) Unknown (need cohort analysis) 3. What's the customer profile from this channel? Ideal customer profile (ICP) — perfect fit Close to ICP — mostly good fit Off ICP — many poor fit customers Unknown" Based on answers, agent evaluates: ✅ High quality: Lower churn, higher NRR, ICP match ⚠️ Medium quality: Similar to blended, mostly good fit 🚨 Low quality: Higher churn, lower NRR, off ICP Agent flags: If high quality: "Premium channel—customers are better than average" If low quality: "Quality problem—customers aren't sticking or expanding" Step 3: Evaluate Scalability Agent asks: "Can this channel scale to meet your growth targets? Efficiency & Volume: 1. What's the S&M efficiency for this channel (Magic Number)? Calculate: (New MRR from channel × 4) / Channel S&M Spend Or provide if known 2. What's the addressable volume for this channel? Large (can scale 10x+ from current spend) Medium (can scale 2 5x) Small (near saturation, maybe 1.5x) Unknown 3. What's the CAC trend for this channel? Decreasing (getting more efficient over time) Stable (consistent CAC) Increasing (diminishing returns, saturation) Unknown (too early to tell) 4. How much growth do you need from acquisition? We'll calculate: Target growth expansion/retention growth = acquisition gap" Based on answers, agent evaluates: ✅ Highly scalable: Magic number 0.75, large volume, stable/decreasing CAC ⚠️ Moderately scalable: Magic number 0.5 0.75, medium volume, stable CAC 🚨 Not scalable: Magic number <0.5, small volume, increasing CAC Step 4: Deliver Recommendations Agent synthesizes: Unit economics (LTV:CAC, payback) Customer quality (retention, NRR, ICP fit) Scalability (magic number, volume, CAC trend) Strategic fit Agent offers 3 4 recommendations: Recommendation Pattern 1: Scale Aggressively When: LTV:CAC 3:1 AND Payback <12 months AND Customer quality good or better AND Magic Number 0.75 AND Addressable volume large Recommendation: " Scale this channel aggressively — Excellent economics + scalability Unit Economics: CAC: $ LTV: $ LTV:CAC: :1 ✅ ( 3:1 threshold) Payback: months ✅ (<12 months) Customer Quality: Retention: [Better than / Same as / Worse than] blended NRR: [Higher / Same / Lower] ICP Fit: [High / Medium / Low] Scalability: Magic Number: ✅ ( 0.75 = efficient) Addressable Volume: Large CAC Trend: [Stable / Decreasing] Why this is a winner: Every $1 spent returns $ in LTV Payback in under a year = fast cash recovery [Customer quality insight] Can scale 5 10x from current spend How to scale: 1. Increase budget by 50 100% next month Current: $ /month → Target: $ /month 2. Monitor key metrics weekly: CAC (should stay <$ ) Magic Number (should stay 0.75) Customer quality (retention, NRR) 3. Scale until: CAC increases 20% (saturation signal) Magic Number drops <0.75 (efficiency declining) Volume caps out Expected impact: Current: customers/month Target (2x spend): customers/month MRR impact: +$ /month Payback: Still ~ months even at 2x scale Risk: Low. Strong unit economics support aggressive scaling." Recommendation Pattern 2: Test & Optimize When: LTV:CAC 2 3:1 OR Payback 12 18 months OR Customer quality average OR Magic Number 0.5 0.75 Recommendation: " Test & optimize before scaling — Marginal economics, fixable Current State: CAC: $ LTV: $ LTV:CAC: :1 ⚠️ (2 3:1 = marginal) Payback: months ⚠️ (12 18 months) Magic Number: ⚠️ (0.5 0.75 = acceptable, not great) Customer Quality: Retention: [Same as blended / Slightly worse] NRR: [Same / Lower] Issue: [Specific problem, e.g., "Higher churn in first 90 days"] Diagnosis: [One of these:] High CAC: Spending too much to acquire Low LTV: Customers churn too fast or don't expand Poor targeting: Attracting off ICP customers Inefficient conversion: High cost per click but low conversion rate How to optimize: If CAC is the problem: 1. Improve conversion rate (optimize landing pages, offer, onboarding) 2. Reduce cost per click (better targeting, ad creative) 3. Shorten sales cycle (faster qualification, better demos) If LTV is the problem: 1. Improve onboarding for customers from this channel 2. Target higher value segments within channel 3. Add expansion plays (upsell, cross sell) If targeting is the problem: 1. Narrow audience (exclude poor fit segments) 2. Improve messaging (attract better fit customers) 3. Add qualification step (reduce poor fit signups) Timeline: Spend 4 8 weeks optimizing Track CAC and LTV weekly Target: LTV:CAC 3:1, payback <12 months If you hit targets: scale If you can't fix it: consider killing Don't scale yet: Current economics are break even at best. Fix first, then scale." Recommendation Pattern 3: Kill or Pause When: LTV:CAC <1.5:1 AND No clear path to improvement Recommendation: " Kill this channel (or pause) — Economics don't support investment Why: CAC: $ LTV: $ LTV:CAC: :1 🚨 (<2:1 = unsustainable) Payback: mon

acquisition-channel-advisor