AIOD Discounts & Free Gift
Build and manage Shopify discounts, free gifts, bundles, BOGO and conditional buy X get Y discounts rules directly from Claude.
- Category
- Pending
- Primary Subcategory
- Pending
Integration details
Description
AIOD connects Claude to Shopify promotion and discount workflows. Use natural language to work with automatic discounts, discount codes, free gifts with purchase, BOGO / Buy X Get Y offers, volume and quantity discounts, tiered promotions, fixed-price offers, shipping discounts and advanced conditional discount rules. AIOD is designed for Shopify merchants who need promotion logic beyond Shopify's standard discount setup. Rules can include conditions based on cart value, product or collection, quantity, customer, market and other supported Shopify attributes. Example requests: “Create 10% off when customers buy 3 or more items.” “Give a free gift when the cart reaches $150.” “Create a BOGO offer for this collection.” “Give VIP customers 20% off, excluding sale products.” “Create a tiered offer: spend $100 get 10% off, spend $200 get 20% off.” AIOD is built on Shopify's discount infrastructure and gives ecommerce and marketing teams a conversational way to create and manage sophisticated promotional logic without writing custom code.
- Integration type
- Connector
- Verification status
Community connector- Platform
- Claude
- Category
- Pending
- Primary Subcategory
- Pending
- Secondary Subcategories
- None listed
- Brand
- Unknown
- Access
- Account required
- First tracked
- 2026-09-02
- Tool count
- 7
- Geography
- US
The broad Category that contains the Primary Subcategory.
The Primary Subcategory used for this profile’s headline score.
Other Subcategories where the Integration is listed.
Claude Discoverability Score
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What discovery looks like

Claude can surface verified Connectors when they match a user’s Prompt.
How Claude Connector discovery works
Your Connector will compete to appear for users’ Prompts once Claude verifies it
Competitive lineup
7 tools agents can invoke
How do I improve a Community connector's discoverability?
The levers are the listing surface agents actually read: names, descriptions, keywords, tool metadata, and registry health. Which lever matters depends on where discovery breaks, which is what continuous measurement shows.
Where is this profile measured?
This profile uses the geography attached to the latest public registry snapshot: US. Locale tags are intentionally omitted.