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Aes Cart Abandonment Analyzer

CommunityPopular
LeoYeAI
aes-cart-abandonment-analyzer

Identify reasons for cart abandonment and build multi-touch recovery sequences across email, SMS, and push.

Overview

PublisherLeoYeAI
Repositoryopenclaw-master-skills
Skill nameaes-cart-abandonment-analyzer
Stars
2.2K
Forks
324
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by LeoYeAI on GitHub. Read the source before you install it.

Installation

Install the Aes Cart Abandonment Analyzer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/aes-cart-abandonment-analyzer
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git /tmp/openclaw-master-skills
mkdir -p .claude/skills
cp -r /tmp/openclaw-master-skills/skills/aes-cart-abandonment-analyzer .claude/skills/aes-cart-abandonment-analyzer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Aes Cart Abandonment Analyzer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Aes Cart Abandonment Analyzer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Aes Cart Abandonment Analyzer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Cart Abandonment Analyzer

Cart abandonment is one of the most expensive leaks in any ecommerce funnel — average abandonment rates hover around 70%, meaning seven out of ten shoppers who add items to their cart leave without purchasing. This skill diagnoses the likely causes of cart abandonment for your specific store and product mix, then builds tailored multi-touch recovery sequences across email, SMS, and push notification channels to win back lost revenue systematically.

Use when

  • Your Shopify, WooCommerce, or BigCommerce store shows a cart abandonment rate above 65% and you need to identify the root causes beyond just "they weren't ready to buy"
  • You want to design a complete abandoned cart recovery flow with timed email sequences, SMS follow-ups, and push notifications but are unsure about optimal timing, copy angles, or incentive escalation
  • Your existing cart recovery emails have an open rate below 40% or a click-through rate below 5% and you want fresh copy, subject lines, and send-time strategies to improve performance
  • A marketing manager needs a documented cart recovery playbook they can hand off to the email marketing team or load into Klaviyo, Omnisend, or Mailchimp automation workflows

What this skill does

This skill takes your store details, product category, average order value, and current abandonment data to perform a structured root-cause analysis of why shoppers are leaving. It examines pricing friction, shipping cost surprises, checkout complexity, trust gaps, payment method limitations, and mobile experience issues. Based on the diagnosis, it generates a complete multi-channel recovery sequence with specific message copy for each touchpoint, recommended send timing relative to the abandonment event, subject lines and preview text for emails, SMS message templates within character limits, and push notification copy. The sequence includes an incentive escalation ladder that starts with reminders and progressively introduces discounts or free shipping offers.

Inputs required

  • Store platform and product category (required): Which platform you sell on and what types of products you sell. Example: "Shopify store selling premium skincare products, AOV around $65."
  • Current abandonment rate (required): Your approximate cart abandonment rate and any known patterns. Example: "72% abandonment, spikes on mobile, most drop off at shipping calculation step."
  • Existing recovery efforts (required): What you currently do to recover abandoned carts — email flows, retargeting ads, nothing at all. Example: "One generic reminder email sent 24 hours after abandonment, 18% open rate."
  • Available channels (optional): Which channels you can use for recovery — email, SMS, push, WhatsApp, retargeting. Defaults to email and SMS if not specified.
  • Discount budget (optional): Maximum discount or incentive you are willing to offer in recovery sequences. Example: "Up to 15% off or free shipping on orders over $50."

Output format

The output begins with a Root-Cause Diagnosis section that identifies the three to five most likely abandonment drivers for this specific store and product type, with reasoning for each. Next comes the Recovery Sequence Blueprint — a timeline-based plan showing each touchpoint across all channels, with exact timing relative to the cart abandonment event. For each touchpoint, the output provides the channel, send time, subject line or message hook, full message body copy, CTA text and destination, and any incentive offered. The output also includes a Segmentation Guide explaining how to split recovery flows by cart value, product type, and customer status (new versus returning). Finally, a Performance Benchmarks section sets realistic open rate, click rate, and recovery rate targets for each message in the sequence.

Scope

  • Designed for: ecommerce operators, email marketers, retention specialists, Shopify and WooCommerce store owners
  • Platform context: Shopify, WooCommerce, BigCommerce, Klaviyo, Omnisend, Mailchimp, Attentive, platform-agnostic
  • Language: English

Limitations

  • Cannot access your actual analytics or cart data in real time; analysis is based on the information you provide plus established ecommerce benchmarks for your product category
  • Recovery copy is template-ready but may need adjustment to match your exact brand voice and comply with SMS marketing regulations in your jurisdiction
  • Does not directly integrate with or configure your email service provider or marketing automation tool — output is designed to be implemented manually or pasted into your existing workflows

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Aes Cart Abandonment Analyzer AI skill do?

Identify reasons for cart abandonment and build multi-touch recovery sequences across email, SMS, and push.

Why use Aes Cart Abandonment Analyzer on TypingMind?

Because you install it once and use it with any model. Aes Cart Abandonment Analyzer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Aes Cart Abandonment Analyzer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/aes-cart-abandonment-analyzer. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Aes Cart Abandonment Analyzer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Aes Cart Abandonment Analyzer?

As many as you like. As long as a model supports skills, you can use Aes Cart Abandonment Analyzer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Aes Cart Abandonment Analyzer AI skill free?

Yes. It is published on GitHub by LeoYeAI under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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