shopify-admin-average-order-value-trends

Calculate average order value trends segmented by new versus returning customers.

174|18|Updated Apr 11, 2026

Search Tags:#graphql #trend analysis #shopify #customer segmentation #aov #revenue analytics #read-only reporting

Ready to run

npx skills add https://github.com/40RTY-ai/shopify-admin-skills --skill shopify-admin-average-order-value-trends

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: shopify-admin-average-order-value-trends
Source: https://github.com/40RTY-ai/shopify-admin-skills/tree/main/skills/finance/shopify-admin-average-order-value-trends
Command: npx skills add https://github.com/40RTY-ai/shopify-admin-skills --skill shopify-admin-average-order-value-trends

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It removes guesswork from measuring how pricing, bundles, or shipping incentives change your Average Order Value over time, specifically separated for new versus returning customers.

Core Features & Use Cases

AOV trend reporting by time bucket: Calculates Average Order Value across configurable windows (daily, weekly, or monthly) so you can see when changes start impacting revenue.
Customer segmentation (new vs returning): Classifies orders using customer order history to quantify whether AOV gains are driven by first-time buyers or repeat customers.
Read-only analytics with CSV output: Produces a downloadable CSV (aov_trends_<date>.csv) and supports human or JSON output for dashboards or further automation.

Quick Start

Use the shopify-admin-average-order-value-trends skill for your store to generate a weekly AOV report for the last 90 days segmented into new and returning customers.

Frequently Asked Questions about shopify-admin-average-order-value-trends

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I track average order value trends for new versus returning customers on Shopify?▼

You can track average order value trends by classifying Shopify orders using customer order history to quantify whether AOV gains are driven by first-time buyers or repeat customers over time. This segmentation isolates revenue impact specifically for new versus returning customer groups.

What is the best way to measure the revenue impact of Shopify upsells and free-shipping thresholds?▼

Measuring the revenue impact of Shopify upsells and free-shipping thresholds requires time-bucketed AOV reporting using daily, weekly, or monthly windows. This approach calculates average order value changes over specific periods to show exactly when pricing incentives start impacting revenue.

Does this AOV trend analysis require write access to my Shopify store?▼

No, this AOV trend analysis requires only read-only Shopify Admin access to orders and customers. It safely queries your store data using created_at filtering with pagination to generate storefront analytics without modifying any store records.

Can I export Shopify AOV trend reports as CSV or JSON for dashboards?▼

Yes, you can export Shopify AOV trend reports as a downloadable CSV file named aov_trends_<date>.csv or as JSON output. These formats provide per-period AOV and segment AOV fields suitable for feeding into automated dashboards or further data analysis.

How do I generate a weekly AOV report for the last 90 days segmented by customer type?▼

To generate a weekly AOV report for the last 90 days segmented by customer type, configure the time bucket to weekly and apply created_at filtering to the specified date range. The output segments new versus returning customers to quantify revenue impact across each weekly period.

What limitations exist when using GraphQL for Shopify customer segmentation and AOV calculations?▼

When using GraphQL for Shopify customer segmentation and AOV calculations, you must handle pagination to process large order volumes and rely on created_at timestamps for accurate time-bucketed reporting. Complex store configurations may require careful query structuring to ensure complete data retrieval.