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Cart Abandonment Analyzer

作者 LeroyCreates · GitHub ↗ · v1.1.0 · MIT-0
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/install aes-cart-abandonment-analyzer
功能描述
Identify reasons for cart abandonment and build multi-touch recovery sequences across email, SMS, and push.
使用说明 (SKILL.md)

Cart Abandonment Analyzer

Diagnose the likely causes of cart abandonment for your specific store and product mix, then build tailored multi-touch recovery sequences across email, SMS, and push notification channels to win back lost revenue systematically.

Quick Reference

Decision Strong Acceptable Weak
Root cause diagnosis Data-driven analysis of checkout funnel with stage-specific drop-off identification General category identification (price, shipping, trust) "People just aren't buying" with no diagnosis
Recovery sequence 3-5 touch multi-channel sequence with timing, copy, and incentive escalation Single recovery email with discount code No recovery flow or single generic reminder
Email copy Personalized subject lines, product-specific body, objection-handling, A/B variants Decent reminder email with product image Generic "You left something behind" template
SMS strategy Compliant opt-in, timed to complement email gaps, concise with deep link Basic cart reminder text No SMS or non-compliant messaging
Incentive ladder Escalating offers (free shipping → % off → $ off) based on cart value and customer segment Single discount offer Same discount for everyone or no incentive
Segmentation By cart value, customer type (new/returning), product category, abandonment stage Basic new vs. returning split No segmentation — same flow for everyone
Timing optimization Data-informed send times with timezone awareness and channel-specific cadence Reasonable timing (1hr, 24hr, 48hr) Random timing or too aggressive/too late
Measurement Recovery rate, revenue recovered, incrementality testing, channel attribution Basic open/click/conversion tracking No measurement or vanity metrics only

Solves

  1. 70%+ cart abandonment rates — The average ecommerce store loses 7 out of 10 potential sales at checkout; systematic diagnosis identifies the specific friction points causing abandonment in your store
  2. Generic recovery emails that don't convert — Template "you forgot something" emails get ignored; personalized, well-timed recovery sequences with escalating incentives recover 5-15% of abandoned carts
  3. Unknown abandonment causes — Most sellers know their abandonment rate but not why shoppers leave; funnel stage analysis reveals whether the problem is shipping costs, payment friction, trust gaps, or comparison shopping
  4. Single-channel recovery — Relying only on email misses shoppers who don't open emails; coordinated multi-channel sequences (email + SMS + push) increase recovery rates by 30-50% over email alone
  5. Profit-destroying discount habits — Offering 20% off to everyone who abandons trains customers to abandon intentionally; smart incentive ladders and segmentation protect margins while recovering sales
  6. Poor timing — Sending the first recovery email 24 hours later is too late for most impulse purchases; optimized send timing based on product type and customer behavior captures time-sensitive intent
  7. No measurement of what works — Without tracking recovery rate by channel, sequence step, and customer segment, you can't optimize; proper attribution reveals which touches actually drive recovered purchases

Workflow

Step 1: Analyze Cart Abandonment Data

Review checkout funnel data to identify where shoppers drop off: cart page, shipping info, payment page, or order review. Calculate abandonment rates by stage, device type, traffic source, and customer segment (new vs. returning).

Key inputs: Checkout funnel data, abandonment rate by stage, device breakdown, traffic source data, customer segmentation

Step 2: Diagnose Root Causes

Map the most common abandonment reasons to your specific funnel data. Cross-reference drop-off stages with likely causes: unexpected shipping costs (shipping page drop-off), payment trust issues (payment page drop-off), comparison shopping (cart page bounce), or account creation friction (registration step).

Key outputs: Ranked list of probable abandonment causes with evidence and impact estimates

Step 3: Design Recovery Sequence Architecture

Build a multi-touch recovery sequence with channel selection (email, SMS, push), timing cadence, and content strategy for each touch. Define segmentation rules for different customer types, cart values, and product categories.

Key outputs: Sequence timeline with channel, timing, content type, and incentive for each touch

Step 4: Write Recovery Messages

Create copy for each message in the sequence: subject lines (with A/B variants), preview text, body copy, CTA buttons, and SMS text. Each message should have a distinct purpose — reminder, social proof, incentive, or urgency.

Key outputs: Complete copy for all messages across all channels with A/B test variants

Step 5: Define Incentive Strategy

Design an incentive escalation ladder based on cart value thresholds and customer lifetime value. Determine when to offer free shipping, percentage discounts, or dollar-off coupons. Set rules for customers who should never receive discounts (recent full-price buyers, already-discounted items).

Key outputs: Incentive decision matrix with thresholds, exclusions, and escalation rules

Step 6: Set Up Measurement Framework

Define KPIs for each sequence step: delivery rate, open rate, click rate, recovery rate, revenue recovered, and incremental revenue (vs. customers who would have returned anyway). Plan holdout testing to measure true incrementality.

Key outputs: Measurement dashboard specification with KPIs, benchmarks, and testing plan

Step 7: Create Optimization Roadmap

Based on initial performance data, prioritize optimization opportunities: subject line testing, send time optimization, incentive level testing, and sequence length experiments. Define testing calendar and minimum sample sizes.

Key outputs: 90-day optimization roadmap with test priorities and expected impact

Example 1: DTC Skincare Brand (Shopify, $65 AOV)

Input:

  • Store: Direct-to-consumer skincare on Shopify
  • AOV: $65
  • Monthly cart abandonments: 3,200
  • Current recovery: Single email at 1 hour, 8% recovery rate
  • Abandonment rate: 74%
  • Top products abandoned: Vitamin C Serum ($30), Bundle Sets ($89), Moisturizer ($42)

Root Cause Diagnosis:

Drop-off Stage % of Abandonments Likely Cause Evidence
Cart page (before checkout) 35% Comparison shopping, not ready to commit High rate on first-time visitors, lower on returning
Shipping info page 25% Shipping cost surprise ($5.99 revealed here) Drop-off correlates with free-shipping threshold gap
Payment page 22% Trust concerns, limited payment options Higher for new customers, lower for returning
Order review 18% Final price shock, last-minute hesitation Correlates with higher cart values ($80+)

Recovery Sequence:

Touch Channel Timing Purpose Incentive Subject Line
1 Email 45 min Reminder + social proof None "Still thinking about [Product]? Here's what 2,000+ customers say"
2 SMS 2 hours Quick nudge with deep link None "Your [Product] is waiting! Complete your order → [link]"
3 Email 24 hours Address objections + free shipping Free shipping "We'll cover shipping on your [Product] — today only"
4 Push 48 hours Urgency + scarcity None "Low stock alert: [Product] is selling fast"
5 Email 72 hours Final offer + testimonial 10% off "Last chance: 10% off your [Product] + a note from a customer who was on the fence too"

Segmentation Rules:

Segment Cart Value Customer Type Sequence Modification
High-value new $80+ First purchase Full 5-touch sequence, skip SMS if no opt-in
Low-value new Under $50 First purchase 3-touch email only, free shipping offer at touch 2
Returning customer Any Previous purchase 3-touch sequence, no discount (they know the brand)
Bundle abandoner $89+ bundle Any Emphasize bundle savings vs. individual prices
Repeat abandoner Any Abandoned 3+ times Exclude from sequence (likely deal-hunting)

Projected Results:

  • Current: 8% recovery rate = 256 recoveries/month = $16,640/month
  • Projected: 14% recovery rate = 448 recoveries/month = $29,120/month
  • Incremental revenue: $12,480/month ($149,760/year)

Example 2: Electronics Accessories Store (WooCommerce, $35 AOV)

Input:

  • Store: Electronics accessories on WooCommerce
  • AOV: $35
  • Monthly cart abandonments: 8,500
  • Current recovery: None
  • Abandonment rate: 78%
  • Top products: Phone cases ($18), Chargers ($25), Screen protectors ($12), Bundles ($45)

Root Cause Diagnosis:

Drop-off Stage % of Abandonments Likely Cause Evidence
Cart page 45% Price comparison (commodity products) Very high Google Shopping traffic, low brand loyalty
Shipping info 30% Shipping cost exceeds product value perception $4.99 shipping on a $12 screen protector = 42% cost increase
Payment page 15% Limited payment options (no PayPal, no BNPL) Competitor analysis shows PayPal/Afterpay standard
Order review 10% Delivery time too long (5-7 business days) Competitors offer 2-day shipping

Recovery Sequence:

Touch Channel Timing Purpose Incentive Subject Line
1 Email 30 min Reminder + price match guarantee None "Your [Product] is reserved — here's why we're the right choice"
2 Email 6 hours Bundle suggestion + free shipping threshold Free ship at $30+ "Add [related item] and get FREE shipping on your entire order"
3 SMS 24 hours Flash urgency 15% off (high margin items only) "15% off your cart — today only! [link]"
4 Email 48 hours Social proof + comparison table 10% off all "See why 5,000+ customers chose us over Amazon"

Incentive Decision Matrix:

Cart Value Customer Type Max Incentive Rationale
Under $20 New Free shipping only Margin too thin for percentage discount
$20-40 New 10% off Enough margin to absorb; acquisition cost justified
$40+ New 15% off High-value cart; strong acquisition investment
Under $20 Returning None They know the brand; reminder is sufficient
$20+ Returning Free shipping Reward loyalty without training discount behavior

Common Mistakes

  1. Sending the first email too late — For impulse-purchase products (under $50), the purchase intent window is 1-2 hours. Sending the first recovery email at 24 hours misses the majority of recoverable shoppers. Aim for 30-60 minutes for low-consideration products.

  2. Offering discounts in the first touch — Leading with a discount trains customers to abandon carts intentionally for a coupon. Start with value-add messaging (social proof, product benefits, free shipping) and reserve discounts for later touches.

  3. Same sequence for all abandoners — A first-time visitor who bounced from the cart page needs education and trust-building. A returning customer who dropped off at payment needs a different payment option or a simple reminder. Segment or lose relevance.

  4. Ignoring SMS as a recovery channel — SMS open rates are 90%+ compared to 20-30% for email. For high-value carts, a well-timed SMS between email touches can recover sales that email alone wouldn't reach.

  5. No suppression rules — Sending recovery emails to customers who already completed their purchase (via a different device or session) destroys trust. Implement real-time suppression that removes converters from the sequence immediately.

  6. Not testing incrementality — If your recovery sequence shows a 12% conversion rate, some of those customers would have returned anyway. Run holdout tests (10% of abandoners get no recovery emails) to measure the true incremental lift — typically 40-60% of attributed recoveries are truly incremental.

  7. Forgetting mobile checkout optimization — Before building recovery sequences, fix the abandonment causes. If 60% of mobile visitors abandon at the payment page, adding Apple Pay and Google Pay may recover more revenue than any email sequence.

  8. Too many emails, too fast — Sending 5 emails in 3 days creates unsubscribes and spam complaints. Space recovery touches across channels and time, with clear escalation logic. Most sequences should complete within 5-7 days.

  9. Static discount codes — Using the same "COMEBACK10" code for every abandoner means customers share it on coupon sites, eroding margins permanently. Use unique, single-use codes with expiration dates tied to the sequence timing.

Resources

安全使用建议
Review before installing. The skill content itself is a reasonable cart-abandonment playbook, but do not grant wallet, payment, purchase, or broad sensitive-credential access unless the publisher clearly explains why it is needed. If you use the skill, provide only the minimum customer/funnel data required and ensure any email, SMS, or push campaigns are approved and compliant before sending.
功能分析
Type: OpenClaw Skill Name: aes-cart-abandonment-analyzer Version: 1.1.0 The skill bundle is a collection of marketing strategy documents and templates designed to guide an AI agent in analyzing e-commerce cart abandonment. It contains no executable code, scripts, or instructions for network communication. The content consists entirely of business logic, workflow descriptions, and markdown templates (SKILL.md, email-templates.md) focused on customer recovery sequences, with no evidence of prompt injection or malicious intent.
能力标签
cryptorequires-walletcan-make-purchasesrequires-sensitive-credentials
能力评估
Purpose & Capability
The visible skill content is purpose-aligned for cart abandonment analysis and campaign copy, but the capability signals include wallet, sensitive-credential, crypto, and purchase authority that is not explained by the stated purpose.
Instruction Scope
The instructions design customer-facing email, SMS, and push recovery sequences. This is expected for the skill and includes consent/suppression guidance, but implementation could affect customers if automated without review.
Install Mechanism
There is no install spec and no code to execute, which lowers runtime risk. However, the source is unknown and there is no homepage, so provenance is limited.
Credentials
No credentials or environment requirements are declared, yet the capability signals mention wallet, sensitive credentials, and purchases. That authority is not proportional to an advisory marketing-analysis skill unless separately clarified.
Persistence & Privilege
The artifacts do not show persistence or background execution, but the unexplained wallet/credential/purchase signals create an ambiguous privilege boundary.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install aes-cart-abandonment-analyzer
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /aes-cart-abandonment-analyzer 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.1.0
v1.1.0: Major upgrade - expanded from 1 file (5KB) to 4 files (36KB). Added comprehensive SKILL.md with quick reference table, 7-step workflow, 2 fully worked examples (DTC Skincare Brand and Electronics Accessories Store with recovery sequences, segmentation rules, and projected revenue impact), 9 common mistakes, cart recovery report template, email/SMS/push copy templates for 5-touch sequences, and 67-item recovery audit checklist.
v1.0.0
Initial release.
元数据
Slug aes-cart-abandonment-analyzer
版本 1.1.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 2
常见问题

Cart Abandonment Analyzer 是什么?

Identify reasons for cart abandonment and build multi-touch recovery sequences across email, SMS, and push. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 83 次。

如何安装 Cart Abandonment Analyzer?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install aes-cart-abandonment-analyzer」即可一键安装,无需额外配置。

Cart Abandonment Analyzer 是免费的吗?

是的,Cart Abandonment Analyzer 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Cart Abandonment Analyzer 支持哪些平台?

Cart Abandonment Analyzer 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Cart Abandonment Analyzer?

由 LeroyCreates(@leooooooow)开发并维护,当前版本 v1.1.0。

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