Token导航 LogoToken导航

Agent Skill · 待分类

acquisition-channel-advisor(收购渠道顾问)

acquisition-channel-advisor 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

acquisition-channel-advisor 是待分类类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在待分类类的 11,209 个 Skill 里排第 387。

总安装 17,993周安装 765GitHub Stars 3,895下载 6,304核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:acquisition-channel-advisor(收购渠道顾问)
来源仓库:https://github.com/deanpeters/product-manager-skills
仓库路径:skills/acquisition-channel-advisor
安装命令:
npx skills add https://github.com/deanpeters/product-manager-skills --skill acquisition-channel-advisor
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/deanpeters/product-manager-skills --skill acquisition-channel-advisor

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

通过单位经济效益、客户质量和可扩展性来评估获取渠道,以决定是否扩展、测试或终止。

评估三个核心维度:单位经济效益(CAC、LTV、投资回收期、LTV:CAC 比率)、客户质量(保留、流失、渠道 NRR)和可扩展性(幻数、可寻址量、CAC 趋势) 提供以下四个建议之一:积极扩展(LTV:CAC >3:1,投资回收期<12个月)、测试和优化(具有可修复问题的边际经济效益)、终止或暂停(不可持续的单位经济效益)或继续实施上限(短期投资回报率较差的战略渠道) 标记常见的陷阱,例如扩展破碎的渠道、忽视客户质量、庆祝虚荣指标以及过度依赖单一渠道 支持跨采购组合的多渠道比较和预算重新分配

来源仓库内路径:skills/acquisition-channel-advisor

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/deanpeters/product-manager-skills --skill acqu…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

acquisition-channel-advisor 怎么安装?

在终端执行 npx skills add https://github.com/deanpeters/product-manager-skills --skill acquisition-ch…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

acquisition-channel-advisor 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

acquisition-channel-advisor 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

acquisition-channel-advisor 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

acquisition-channel-advisor 用的人多吗?

公开数据是累计安装 17,993 次,近一周安装 765 次,下载 6,304 次,GitHub 3,895 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

acquisition-channel-advisor 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 来源仓库有 3,895 星,维护活跃度相对可查。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理待分类类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
acquisition-channel-advisor

收购渠道顾问 · 本页

17,9933,895只读未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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:

  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

  1. 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

  1. 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)

  1. 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:CACPaybackCustomer QualityScalabilityDecision
>3:1<12moGood retentionHigh volumeScale aggressively
2-3:112-18moAverage retentionMedium volumeTest & optimize
<2:1>18moPoor retentionLow volumeKill 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:

  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)

  1. 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)

  1. 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)

  1. 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

  1. 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

  1. 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)

  1. 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

  1. Monitor key metrics weekly:

- CAC (should stay <$___) - Magic Number (should stay >0.75) - Customer quality (retention, NRR)

  1. 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)

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

- Pipeline influence - Brand awareness lift - Referral rate from this channel

  1. 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:

ChannelCACLTVLTV:CACPaybackMagic NumberQualityRecommendation
Google Ads$500$2,0004:18mo0.9HighScale
Content$200$1,5007.5:14mo1.2HighScale
Outbound$10K$50K5:118mo0.6MediumOptimize
Events$15K$30K2:124mo0.3LowKill

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

平台分布

Codex

36.28%
按下载量换算2,287

Claude

31.88%
按下载量换算2,010

Cursor

17.71%
按下载量换算1,116

Gemini CLI

10.11%
按下载量换算637

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills