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Shopify Admin Checkout Abandonment Report

  • 6 installs
  • 173 repo stars
  • Updated June 26, 2026
  • 40rty-ai/shopify-admin-skills

shopify-admin-checkout-abandonment-report is a Claude Code skill that aggregates a Shopify store's abandoned checkouts by cart-value bucket and hour of day over a date range.

About

This skill pulls abandoned checkout data from a Shopify store over a date range and aggregates it by cart-value bucket and by hour of day in UTC. Store owners use it to see when and at what price point customers abandon checkout. It is read-only and outputs two inline tables rather than a CSV.

  • Aggregates abandoned checkouts by cart-value bucket and hour of day (UTC)
  • Read-only query against the Shopify abandonedCheckouts API with paginated fetch
  • Reports two inline tables; notes device and geo data are not available from the API

Shopify Admin Checkout Abandonment Report by the numbers

  • 6 all-time installs (skills.sh)
  • Ranked #1,691 of 2,715 Automation & Workflows skills by installs in the Skillselion catalog
  • Data as of Aug 1, 2026 (Skillselion catalog sync)
At a glance

shopify-admin-checkout-abandonment-report capabilities & compatibility

Free skill; requires an authenticated Shopify store session with the read_checkouts scope.

Capabilities
cart abandonment report · conversion analysis · checkout analytics
Works with
stripe
Use cases
data analysis
Pricing
Bring your own API key
From the docs

What shopify-admin-checkout-abandonment-report says it does

Aggregate abandoned checkout data for a time range, broken down by cart value bucket and hour of day (UTC).
SKILL.md
Device type and geographic location are not available in the `abandonedCheckouts` API and are not reported by this skill.
SKILL.md
npx skills add https://github.com/40rty-ai/shopify-admin-skills --skill shopify-admin-checkout-abandonment-report

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Listed on Skillselion
Installs6
repo stars173
Last updatedJune 26, 2026
Repository40rty-ai/shopify-admin-skills

What it does

Report Shopify abandoned checkouts broken down by cart value and hour of day to spot when customers drop off.

Who is it for?

Merchants who want to find the price points and times of day where checkout abandonment concentrates.

Skip if: Recovering carts or sending abandonment emails; it only reports, and it cannot break down by device or geography.

When should I use this skill?

You want a breakdown of when and at what cart value customers are abandoning checkout.

What you get

Two tables show abandoned-checkout counts and percentages by cart-value band and by UTC hour.

  • Inline table of abandonment by cart-value bucket
  • inline table of abandonment by hour of day (UTC)

By the numbers

  • default cart_value_buckets [0,25,50,100,250]
  • aggregates across 24 UTC hours (0-23)
  • paginates 250 checkouts per request

Files

SKILL.mdMarkdownGitHub ↗

Purpose

Aggregates abandoned checkout data broken down by cart value bucket and hour of day (UTC). Helps identify when and at what price point customers are most likely to abandon checkout. Scoped to what the abandonedCheckouts API provides — device type and geographic location are not available in this API and are not reported.

Prerequisites

  • Authenticated Shopify CLI session: shopify auth login --store <domain>
  • API scopes: read_checkouts

Parameters

ParameterTypeRequiredDefaultDescription
storestringyesStore domain (e.g., mystore.myshopify.com)
formatstringnohumanOutput format: human or json
dry_runboolnofalsePreview operations without executing mutations
date_range_startstringyesStart date in ISO 8601 (e.g., 2025-01-01)
date_range_endstringyesEnd date in ISO 8601 (e.g., 2025-01-31)
cart_value_bucketsarrayno[0, 25, 50, 100, 250]Array of thresholds defining cart value bands (e.g., [0,25,50,100,250] creates bands: $0–25, $25–50, $50–100, $100–250, $250+)

Workflow Steps

1. OPERATION: abandonedCheckouts — query Inputs: first: 250, query: "created_at:>='<date_range_start>' created_at:<='<date_range_end>'", pagination cursor Expected output: All abandoned checkouts in range with totalPrice and createdAt; paginate until hasNextPage: false; then aggregate in-memory: (1) count by cart value bucket, (2) count by hour of day (UTC, 0–23)

GraphQL Operations

# abandonedCheckouts:query — validated against api_version 2025-04
query AbandonedCheckoutsReport($first: Int!, $after: String, $query: String) {
  abandonedCheckouts(first: $first, after: $after, query: $query) {
    edges {
      node {
        id
        createdAt
        totalPriceSet {
          shopMoney {
            amount
            currencyCode
          }
        }
        customer {
          defaultEmailAddress {
            emailAddress
          }
        }
        lineItems {
          edges {
            node {
              title
              quantity
              variant {
                price
              }
            }
          }
        }
      }
    }
    pageInfo {
      hasNextPage
      endCursor
    }
  }
}

Session Tracking

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

On start, emit:

╔══════════════════════════════════════════════╗
║  SKILL: checkout-abandonment-report          ║
║  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):

══════════════════════════════════════════════
OUTCOME SUMMARY
  Total abandoned:   <n>
  Date range:        <start> to <end>
  Errors:            0
  Output:            none
══════════════════════════════════════════════

For format: json, emit:

{
  "skill": "checkout-abandonment-report",
  "store": "<domain>",
  "started_at": "<ISO8601>",
  "completed_at": "<ISO8601>",
  "dry_run": false,
  "steps": [
    { "step": 1, "operation": "AbandonedCheckoutsReport", "type": "query", "params_summary": "<date_range_start> to <date_range_end>", "result_summary": "<n> checkouts", "skipped": false }
  ],
  "outcome": {
    "total_abandoned": 0,
    "date_range_start": "<date_range_start>",
    "date_range_end": "<date_range_end>",
    "by_cart_value": [
      { "range": "$0 – $25", "count": 0, "pct": 0.0 }
    ],
    "by_hour_utc": [
      { "hour": "00:00", "count": 0, "pct": 0.0 }
    ],
    "errors": 0,
    "output_file": null
  }
}

Output Format

Two tables displayed inline (no CSV):

Table 1: Abandonment by Cart Value Bucket

Cart Value RangeAbandoned Checkouts% of Total
$0 – $25......
$25 – $50......
$50 – $100......
$100 – $250......
$250+......

Table 2: Abandonment by Hour of Day (UTC)

Hour (UTC)Abandoned Checkouts% of Total
00:00......
01:00......
02:00......
...

For format: json, by_cart_value is an array of {range, count, pct} objects; by_hour_utc is an array of {hour, count, pct} objects.

Note: Device type and geographic location are not available in the abandonedCheckouts API and are not reported by this skill.

Error Handling

ErrorCauseRecovery
No checkouts returnedNo abandoned checkouts in date rangeWiden date range or verify read_checkouts scope
Invalid date formatDate not in ISO 8601Use format YYYY-MM-DD
Rate limit (429)Too many paginated requestsNarrow date range or reduce first to 100

Best Practices

1. For high-traffic stores, narrow the date range to 7–14 days for faster results; paginating 90 days of data can produce many API calls. 2. The default cart_value_buckets of [0,25,50,100,250] works for most stores — adjust thresholds to match your AOV distribution. 3. Hours are reported in UTC — convert to your store's local timezone before drawing conclusions about peak abandonment times. 4. Run this report weekly and compare the by-hour pattern to your promotional send times to find timing opportunities. 5. email is included in the query result — combine with the abandoned-cart-recovery skill to act on the customers most likely to convert based on their cart value tier.

Related skills

FAQ

Can it break abandonment down by device or country?

No. The skill notes device type and geographic location are not available in the abandonedCheckouts API and are not reported.

Does it export a CSV?

No. It displays two tables inline: abandonment by cart-value bucket and by hour of day (UTC).

Automation & Workflowsecommercepayments

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