shopify-admin-price-elasticity-analyzer

SkillCommerce & finance

Read-only: analyzes the relationship between product pricing and sales velocity to identify optimal price points and price-sensitive products.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the shopify-admin-price-elasticity-analyzer skill

What this skill tells your AI

The instructions your AI receives, as published by 40rty-ai/shopify-admin-skills in skills/merchandising/shopify-admin-price-elasticity-analyzer/SKILL.md and read by ahel’s review.

Purpose

Analyzes price-to-velocity relationships across the product catalog to identify which products are price-sensitive and where optimal price points might exist. Compares products within the same category/vendor at different price tiers, and examines how products with compare-at prices (on sale) perform vs. full-price items. Read-only — no mutations.

Prerequisites

  • Authenticated Shopify CLI session: shopify store auth --store <domain> --scopes read_orders,read_products
  • API scopes: read_orders, read_products

Parameters

ParameterTypeRequiredDefaultDescription
storestringyesStore domain
days_backintegerno90Sales lookback window
group_bystringnoproduct_typeGroup comparison: product_type, vendor, or collection
formatstringnohumanOutput format: human or json

Safety

ℹ️ Read-only skill — no mutations are executed. Safe to run at any time.

Workflow Steps

  1. OPERATION: products — query Inputs: first: 250, status: ACTIVE, select id, title, productType, vendor, variants { price, compareAtPrice, inventoryQuantity }, pagination cursor Expected output: All active products with pricing data

  2. OPERATION: orders — query Inputs: query: "created_at:>='<NOW - days_back days>'", first: 250, select lineItems { variant { id, price }, quantity }, pagination cursor Expected output: Sales data per variant for velocity calculation

  3. For each product/variant, calculate:

    • Units sold per day (velocity)
    • Revenue per day
    • Current price point
    • Has compare-at price? (on sale indicator)
    • Sale discount % = (compareAtPrice - price) / compareAtPrice × 100
  4. Within each group (product_type or vendor):

    • Sort by price ascending
    • Calculate velocity at each price tier
    • Identify price-velocity correlation (negative = price-sensitive, flat = price-insensitive)
    • Compare sale items velocity vs. full-price velocity
    • Flag products where small price changes could significantly change volume
  5. OPERATION: productVariants — query (enrichment for variants with compare-at prices) Inputs: Variant IDs where compareAtPrice is set Expected output: Historical pricing context

GraphQL Operations

# products:query — validated against api_version 2025-01
query ActiveProductsWithPricing($after: String) {
  products(first: 250, after: $after, query: "status:active") {
    edges {
      node {
        id
        title
        productType
        vendor
        variants(first: 100) {
          edges {
            node {
              id
              price
              compareAtPrice
              sku
              inventoryQuantity
            }
          }
        }
      }
    }
    pageInfo { hasNextPage endCursor }
  }
}
# orders:query — validated against api_version 2025-01
query SalesVelocityData($query: String!, $after: String) {
  orders(first: 250, after: $after, query: $query) {
    edges {
      node {
        createdAt
        lineItems(first: 50) {
          edges {
            node {
              variant { id price }
              quantity
            }
          }
        }
      }
    }
    pageInfo { hasNextPage endCursor }
  }
}
# productVariants:query — validated against api_version 2025-01
query VariantsOnSale($query: String, $after: String) {
  productVariants(first: 250, after: $after, query: $query) {
    edges {
      node {
        id
        price
        compareAtPrice
        product { id title productType vendor }
      }
    }
    pageInfo { hasNextPage endCursor }
  }
}

Session Tracking

Claude MUST emit the following output at each stage. This is mandatory.

On start, emit:

╔══════════════════════════════════════════════╗
║  SKILL: Price Elasticity Analyzer            ║
║  Store: <store domain>                       ║
║  Started: <YYYY-MM-DD HH:MM UTC>             ║
╚══════════════════════════════════════════════╝

After each step, emit:

[N/TOTAL] <QUERY|MUTATION>  <OperationName>
          → Params: <brief summary of key inputs>
          → Result: <count or outcome>

On completion, emit:

For format: human (default):

══════════════════════════════════════════════
PRICE ELASTICITY ANALYSIS  (<days_back> days)
  Products analyzed:        <n>
  Product groups compared:  <n>
  ─────────────────────────────
  PRICE-SENSITIVE (high elasticity):
    "<product type>" — velocity drops <pct>% per $10 price increase
    Top candidate: "<product>" at $<price> — consider testing $<lower>

  PRICE-INSENSITIVE (low elasticity):
    "<product type>" — velocity stable across price range $<low>-$<high>
    Top candidate: "<product>" at $<price> — room to increase

  SALE EFFECTIVENESS:
    Products on sale: <n>  Avg discount: <pct>%
    Sale velocity lift: +<pct>% vs. full-price peers

  Output: price_elasticity_<date>.csv
══════════════════════════════════════════════

Output Format

CSV file price_elasticity_<YYYY-MM-DD>.csv with columns: product_id, product_title, product_type, vendor, current_price, compare_at_price, daily_velocity, revenue_per_day, group_avg_velocity, price_rank_in_group, elasticity_indicator, recommendation

Error Handling

ErrorCauseRecovery
THROTTLEDAPI rate limit exceededWait 2 seconds, retry up to 3 times
Small groupsOnly 1-2 products in a typeSkip group — insufficient data for comparison
No salesProduct has zero sales in windowInclude at velocity=0 for comparison

Best Practices

  • Best results require at least 5+ products per group for meaningful comparison.
  • Price-insensitive products are candidates for price increases — test with bulk-price-adjustment.
  • Price-sensitive products may benefit from promotional pricing — test with discount-ab-analysis.
  • Products on sale with minimal velocity lift are wasting margin — remove compare-at price.
  • Run quarterly to track how price sensitivity changes with seasons.

Signals

GitHub stars
187
Forks
18
Last commit
Aug 2026

ahel review

  • S4info
    community integration — published by 40rty-ai, not shopify

Automated review, not a security audit. Ruleset v1.

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skill
Gateway key
shopify-admin-price-elasticity-analyzer
Source
github.com/40rty-ai/shopify-admin-skills