Traffic By Page Report

Purpose

Queries Shopify's built-in analytics engine (ShopifyQL) to surface session-level traffic data scoped to product and collection pages. Shows which pages are attracting the most traffic, how many sessions convert to orders, and where visitors are bouncing — ready input for SEO prioritisation, merchandising focus, and A/B test targeting. Read-only — no mutations are executed.

Prerequisites

Parameters

Workflow Steps

Inputs: ShopifyQL string FROM sessions SHOW sessions, conversion_rate GROUP BY landing_page_path SINCE -d UNTIL today ORDER BY sessions DESC LIMIT 250; sessions and conversion_rate are the confirmed available metrics for this data source

Expected output: All landing pages with session counts and conversion rates; paginate via OFFSET if result count equals 250

> Note: ShopifyQL does not support LIKE, WHERE string prefix filters, or aggregate aliases that shadow reserved column names (sessions, conversion_rate). All page-type filtering must be done in-memory after fetching all rows.

GraphQL Operations

# shopifyqlQuery:query (page traffic) — validated against api_version 2025-01
query TrafficByPage($query: String!) {
  shopifyqlQuery(query: $query) {
    parseErrors
    tableData {
      columns {
        name
        dataType
        displayName
      }
      rows
    }
  }
}

The $query variable (single call — all landing pages, filtered in-memory):

FROM sessions
SHOW sessions, conversion_rate
GROUP BY landing_page_path
SINCE -<days_back>d
UNTIL today
ORDER BY sessions DESC
LIMIT 250

Then filter rows in-memory:

> Confirmed live against 2025-01: sessions (INTEGER) and conversion_rate (PERCENT) are the available metrics. WHERE … LIKE, bounce_rate, converted_sessions, and aggregate aliases that shadow reserved names are not supported in ShopifyQL FROM sessions.

Session Tracking

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

On start, emit:

╔══════════════════════════════════════════════╗
║  SKILL: traffic-by-page-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
  Lookback window:      <days_back> days
  Page type:            <products|collections|both>
  Pages analysed:       <n>
  Top session page:     <path> (<n> sessions)
  Top converting page:  <path> (<pct>%)
  Errors:               0
  Output:               traffic_by_page_<date>.csv
══════════════════════════════════════════════

For format: json, emit:

{
  "skill": "traffic-by-page-report",
  "store": "<domain>",
  "started_at": "<ISO8601>",
  "completed_at": "<ISO8601>",
  "dry_run": false,
  "steps": [
    { "step": 1, "operation": "ProductPageTraffic", "type": "query", "params_summary": "products, last <days_back> days", "result_summary": "<n> product pages returned", "skipped": false },
    { "step": 2, "operation": "ProductPageTraffic", "type": "query", "params_summary": "collections, last <days_back> days", "result_summary": "<n> collection pages returned", "skipped": false }
  ],
  "outcome": {
    "days_back": 30,
    "page_type": "both",
    "pages_analysed": 0,
    "results": [],
    "errors": 0,
    "output_file": "traffic_by_page_<date>.csv"
  }
}

Output Format

CSV file traffic_by_page_.csv with one row per page:

For format: human, a ranked table is printed inline truncated to top_n, followed by a short list of optimisation candidates flagged with high_traffic_low_conversion.

Error Handling

Best Practices