Acquisition Channel Advisor

• Cohort retention rate (by channel)
• Churn rate (by channel)
• NRR (Net Revenue Retention by channel)
• Expansion rate

Decision Matrix

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 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):

CAC = Monthly Spend / Customers Acquired per Month

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: ___ months 🚨 (>18 months = cash trap)

Problem:

• You're spending $___ to acquire a customer worth $___
• [Losing money / Barely breaking even / Taking too long to recover cost]

Customer Quality:

• Retention: [Worse than blended]
• NRR: [Lower]
• ICP Fit: [Poor]

What's broken: [Specific diagnosis:]

• CAC too high (spending $___ vs. blended $___)
• LTV too low (customers churn at ___% vs. blended ___%)
• Both (bad unit economics from both sides)

Should you fix or kill?

Fix if:

• You have a hypothesis to improve CAC by 50%+ (better targeting, conversion)
• You have a hypothesis to improve LTV by 50%+ (better onboarding, ICP focus)
• This is a strategically important channel (e.g., enterprise requires field sales)

Kill if:

• No clear path to 3:1 LTV:CAC
• Better channels available (reallocate budget there)
• Small addressable volume (not worth fixing)

Recommendation: Kill and reallocate budget

Reallocate to:

• Channel X (LTV:CAC = ___:1, can scale)
• Channel Y (Magic Number = ___, efficient)

What to do with budget:

• Current channel spend: $___/month
• Reallocate to [top-performing channel]
• Expected impact: [better CAC, better LTV, faster payback]

Exception: If this channel is <10% of total S&M spend, just pause it. Not worth fixing."

Recommendation Pattern 4: Invest to Learn (Strategic Channel)

When:

• Poor unit economics BUT
• Strategic importance (enterprise channel, brand building, long-term)

Recommendation:

"Continue, but cap investment — Strategic value > short-term ROI

Financial Reality:

• CAC: $___
• LTV: $___
• LTV:CAC: ___:1 (below 3:1 threshold)
• Payback: ___ months (long)

Why continue despite poor economics:

• [Strategic reason: e.g., "Enterprise segment requires field events, but deals are 12-month sales cycles"]
• [Brand building: e.g., "Conferences build brand awareness that drives inbound long-term"]
• [Market positioning: e.g., "Need to be present in this channel for credibility"]

How to manage:

1. Cap spend — Don't scale until economics improve
   • Current: $___/month
   • Cap at: $___/month (hold steady)
2. Track leading indicators — Don't just look at short-term CAC/LTV
   • Pipeline influence
   • Brand awareness lift
   • Referral rate from this channel
3. Re-evaluate quarterly
   • If economics improve (LTV:CAC >3:1): scale
   • If economics stay poor: reconsider strategy

Timeline:

• Give it [6-12 months] to show results
• If no improvement: kill or reduce drastically

Risk: You're subsidizing growth. Make sure it's worth it."

Step 5: Compare Across Channels (Optional)

If user has multiple channels, agent can generate:

Budget allocation recommendation:

1. Scale: Content (highest efficiency)
2. Scale: Google Ads (strong economics)
3. Optimize: Outbound (improve magic number)
4. Kill: Events (reallocate budget)

Examples

See examples/ folder for sample conversation flows. Mini examples below:

Example 1: Scale (Content Marketing)

Channel: Organic content (blog, SEO)

• CAC: $200
• LTV: $3,000
• LTV:CAC: 15:1
• Payback: 3 months
• Magic Number: 1.8
• Customer quality: High (lower churn, higher NRR)

Recommendation: Scale aggressively. Exceptional unit economics, fast payback, high-quality customers. Increase content spend 2-3x.

Example 2: Optimize (Paid Search)

Channel: Google Ads

• CAC: $800
• LTV: $2,000
• LTV:CAC: 2.5:1
• Payback: 14 months
• Magic Number: 0.6
• Customer quality: Lower (higher churn in first 90 days)

Recommendation: Test & optimize before scaling. CAC is high, onboarding is weak for this segment. Improve landing page, target higher-intent keywords, better onboarding for paid customers.

Example 3: Kill (Trade Shows)

Channel: Industry events

• CAC: $20,000
• LTV: $30,000
• LTV:CAC: 1.5:1
• Payback: 30 months
• Magic Number: 0.2
• Customer quality: Low (off-ICP, many tire-kickers)

Recommendation: Kill. CAC too high, payback too long, poor customer quality. Reallocate budget to content and paid search.

Common Pitfalls

Pitfall 1: Scaling Broken Channels

Symptom: "Let's 10x our Google Ads spend!" (LTV:CAC is 1.5:1)

Consequence: You accelerate cash burn without improving unit economics. Lose money faster.

Fix: Only scale channels with LTV:CAC >3:1 and payback <12 months. Fix broken channels before scaling.

Pitfall 2: Ignoring Customer Quality

Symptom: "CAC is only $100!" (but customers churn in 30 days)

Consequence: Low CAC means nothing if LTV is also low. You're acquiring churners, not customers.

Fix: Track cohort retention and NRR by channel. Low CAC + high churn = bad channel.

Pitfall 3: Celebrating Vanity Metrics

Symptom: "We got 10,000 signups from this campaign!" (5% convert to paid)

Consequence: Signups don't pay bills. CAC is calculated on paid customers, not signups.

Fix: Track CAC on paid customers only. Ignore vanity metrics like signups, impressions, clicks.

Pitfall 4: Averaging Across Channels

Symptom: "Blended CAC is $500" (but hiding that one channel is $10K CAC)

Consequence: Bad channels hide in blended metrics. You don't know which channels to kill.

Fix: Track CAC, LTV, payback by channel. Compare channels individually.

Pitfall 5: Short-Term CAC Optimization

Symptom: "We reduced CAC 50%!" (by targeting low-intent, low-LTV customers)

Consequence: CAC dropped but so did LTV. Unit economics got worse, not better.

Fix: Optimize for LTV:CAC ratio, not CAC alone. Higher CAC with higher LTV is better.

Pitfall 6: Ignoring Payback Period

Symptom: "LTV:CAC is 6:1, this channel is amazing!" (payback is 48 months)

Consequence: You run out of cash before recovering CAC. Great ratio, terrible cash flow.

Fix: Pair LTV:CAC with payback period. 3:1 with 8-month payback beats 6:1 with 36-month payback.

Pitfall 7: Killing Channels Too Early

Symptom: "This channel didn't work after 2 weeks"

Consequence: Channels need time to optimize. Killing too early wastes learning.

Fix: Give channels 3-6 months and 100+ customers before evaluating. Track trends, not snapshots.

Pitfall 8: Over-Relying on One Channel

Symptom: "90% of our customers come from Google Ads"

Consequence: Algorithm change, competitor outbids you, channel saturates = business grinds to halt.

Fix: Diversify channels. No single channel should be >50% of new customer acquisition.

Pitfall 9: Forgetting Incrementality

Symptom: "This retargeting campaign has great ROI!" (but customers would've converted anyway)

Consequence: You're paying for conversions that would happen organically. Inflated ROI.

Fix: Test incrementality with holdout groups. Only count truly incremental conversions.

Pitfall 10: Strategic Channels Without Limits

Symptom: "Enterprise events are strategic, we can't stop!" (losing $500K/year)

Consequence: "Strategic" becomes an excuse for burning cash indefinitely.

Fix: Cap spend on strategic channels. Set timeline for improvement (6-12 months). If no progress, kill.

References

Related Skills

• saas-economics-efficiency-metrics — CAC, LTV, payback, magic number calculations
• saas-revenue-growth-metrics — NRR, churn, cohort analysis by channel
• finance-metrics-quickref — Fast lookup for channel evaluation metrics
• feature-investment-advisor — Similar ROI framework for feature decisions
• business-health-diagnostic — Broader business health assessment

External Frameworks

• Brian Balfour (Reforge): Channel-product fit framework
• David Skok: "SaaS Metrics" — CAC, LTV, and payback for channels
• Tomasz Tunguz: SaaS channel benchmarking
• First Round Review: "How to Find and Scale Your Growth Channels"

Provenance

• Adapted from research/finance/Finance_For_PMs.Putting_It_Together_Synthesis.md (Decision Framework #2)
• Channel economics from research/finance/Finance for Product Managers.md