Bulk Customer Tag Update

Adds and/or removes tags across a filtered set of customers — supports query-based selection, explicit ID lists, and union/replace tag modes.

shopify-admin-bulk-customer-tag-update


Purpose

Applies bulk tag changes (add, remove, or both) to customers selected by a query filter (e.g., total_spent:>=500, tag:newsletter) or by an explicit list of customer GIDs. Tags are how Shopify segments customers for discounts, marketing, and support workflows; this skill makes batch changes safe, dry-runnable, and auditable. Use when migrating from one tag taxonomy to another, when retiring a campaign-specific tag, or when applying a new segment tag identified by an analytics report.


Prerequisites

  • Authenticated Shopify CLI session: shopify store auth --store --scopes read_customers,write_customers
  • API scopes: read_customers, write_customers

  • Parameters


    ParameterTypeRequiredDefaultDescription
    storestringyesStore domain (e.g., mystore.myshopify.com)
    formatstringnohumanOutput format: human or json
    dry_runboolnotruePreview matching customers and the planned tag changes without executing mutations
    filterstringconditionalCustomer query filter (e.g., tag:newsletter, total_spent:>=500); required if customer_ids is omitted
    customer_idsarrayconditionalExplicit list of customer GIDs; required if filter is omitted
    add_tagsarrayno[]Tags to add (union with existing tags)
    remove_tagsarrayno[]Tags to remove (set difference)
    modestringnomergeTag write mode: merge (apply add/remove to existing) or replace (overwrite tags entirely with add_tags only)
    max_customersintegerno1000Run-size cap; abort if filter matches more than this

    Safety


    > ⚠️ Step 2 executes one customerUpdate mutation per customer in the matched set. Tag changes are immediate and visible to staff and to any apps reading customer tags (loyalty, marketing automation, segmentation). mode: replace overwrites existing tags entirely — manually-applied operational tags will be lost. The default is dry_run: true and mode: merge. Always run dry-run first, review the matched count, and confirm add_tags/remove_tags are spelled correctly — Shopify tags are case-sensitive.


    Workflow Steps


  • OPERATION: customers — query
  • Inputs: When filter is set: query: , first: 250, pagination cursor. When customer_ids is set: batch query with query: "id: OR id: ..." (chunk into batches of 25 IDs). Select id, displayName, defaultEmailAddress { emailAddress }, tags.

    Expected output: Customer list with current tags. Abort if match_count > max_customers.


  • For each matched customer, compute the target tag set:
  • If mode: merge: target = (existing ∪ add_tags) \ remove_tags
  • If mode: replace: target = add_tags (remove_tags ignored)
  • Skip the customer if target == existing (no-op).


  • OPERATION: customerUpdate — mutation
  • Inputs: For each customer with a non-empty diff: input: { id: , tags: }

    Expected output: customer.id, customer.tags, userErrors; collect failures


    GraphQL Operations


    # customers:query — validated against api_version 2025-01
    query CustomersForBulkTagging($query: String!, $after: String) {
      customers(first: 250, after: $after, query: $query) {
        edges {
          node {
            id
            displayName
            firstName
            lastName
            defaultEmailAddress {
              emailAddress
            }
            tags
            numberOfOrders
            amountSpent {
              amount
              currencyCode
            }
          }
        }
        pageInfo {
          hasNextPage
          endCursor
        }
      }
    }
    

    # customerUpdate:mutation — validated against api_version 2025-01
    mutation CustomerTagsUpdate($input: CustomerInput!) {
      customerUpdate(input: $input) {
        customer {
          id
          displayName
          tags
        }
        userErrors {
          field
          message
        }
      }
    }
    

    Session Tracking


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


    On start, emit:

    ╔══════════════════════════════════════════════╗
    ║  SKILL: Bulk Customer Tag Update             ║
    ║  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>
    

    If dry_run: true, prefix every mutation step with [DRY RUN] and do not execute it.


    On completion, emit:


    For format: human (default):

    ══════════════════════════════════════════════
    BULK TAG UPDATE OUTCOME
      Filter:           <filter or "<n> explicit IDs">
      Mode:             <merge|replace>
      Add tags:         <list>
      Remove tags:      <list>
      Customers matched: <n>
      Customers updated: <n>  (or "skipped — dry_run")
      No-op (already in state): <n>
      Errors:           <n>
      Output:           bulk_tag_update_<date>.csv
    ══════════════════════════════════════════════
    

    For format: json, emit:

    {
      "skill": "bulk-customer-tag-update",
      "store": "<domain>",
      "started_at": "<ISO8601>",
      "completed_at": "<ISO8601>",
      "dry_run": true,
      "mode": "merge",
      "outcome": {
        "matched": 0,
        "updated": 0,
        "noop": 0,
        "errors": 0,
        "add_tags": [],
        "remove_tags": [],
        "output_file": "bulk_tag_update_<date>.csv"
      }
    }
    

    Output Format

    CSV file bulk_tag_update_.csv with columns:

    customer_id, name, email, previous_tags, tags_added, tags_removed, new_tags, status


    The status column reports updated, noop, or error: .


    Error Handling

    ErrorCauseRecovery
    THROTTLEDAPI rate limit exceededWait 2 seconds, retry up to 3 times
    userErrors on customerUpdateInvalid input or read-only customerLog error, skip customer, continue
    match_count > max_customersFilter is too broadRefine filter or raise max_customers deliberately
    Both filter and customer_ids emptyNo selectionAbort with parameter error
    Tag is empty stringWhitespace-only entryStrip and skip empty values
    Case-mismatched remove_tagTags are case-sensitiveRe-run with exact casing

    Best Practices

  • Always run with dry_run: true first — review the matched count and a sample of previous_tagsnew_tags diffs before committing.
  • Prefer mode: merge (the default) for almost all use cases — mode: replace is appropriate only when fully resetting a customer's tag taxonomy and you have an audited backup of prior tags.
  • Tags are case-sensitive: VIP and vip are distinct in Shopify. Standardize casing in your taxonomy.
  • For ongoing operational segments, prefer date-stamped tag names (e.g., cohort-2026-Q2) so historical cohorts remain identifiable as new tags accumulate.
  • Pair with vip-customer-identifier or customer-spend-tier-tagger to feed segment tags from analytics outputs into the customer record.
  • Use remove_tags as the cleanup pass after a campaign — leaving stale campaign tags clutters segmentation in marketing tools.
  • When customer_ids is supplied directly (e.g., from another skill's CSV), the run is fully deterministic — no filter ambiguity.