acquisition-channel-advisor

SKILL.md

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.

Key Concepts

The Channel Evaluation Framework

A systematic approach to evaluate acquisition channels:

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

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

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)

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 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:

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)

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:

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)

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)

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:

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

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

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)

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:

Increase budget by 50-100% next month

Current: $___ /month → Target: $___ /month

Monitor key metrics weekly:

CAC (should stay <$___)

Magic Number (should stay >0.75)

Customer quality (retention, NRR)

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:

Improve conversion rate (optimize landing pages, offer, onboarding)

Reduce cost-per-click (better targeting, ad creative)

Shorten sales cycle (faster qualification, better demos)

If LTV is the problem:

Improve onboarding for customers from this channel

Target higher-value segments within channel

Add expansion plays (upsell, cross-sell)

If targeting is the problem:

Narrow audience (exclude poor-fit segments)

Improve messaging (attract better-fit customers)

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:

Cap spend — Don't scale until economics improve

Current: $___/month

Cap at: $___/month (hold steady)

Track leading indicators — Don't just look at short-term CAC/LTV

Pipeline influence

Brand awareness lift

Referral rate from this channel

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:

Channel
CAC
LTV
LTV:CAC
Payback
Magic Number
Quality
Recommendation

Google Ads
$500
$2,000
4:1
8mo
0.9
High
Scale

Content
$200
$1,500
7.5:1
4mo
1.2
High
Scale

Outbound
$10K
$50K
5:1
18mo
0.6
Medium
Optimize

Events
$15K
$30K
2:1
24mo
0.3
Low
Kill

Budget allocation recommendation:

Scale: Content (highest efficiency)

Scale: Google Ads (strong economics)

Optimize: Outbound (improve magic number)

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