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
shopify store auth --store --scopes read_customers,write_customers read_customers, write_customersParameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| store | string | yes | — | Store domain (e.g., mystore.myshopify.com) |
| format | string | no | human | Output format: human or json |
| dry_run | bool | no | true | Preview matching customers and the planned tag changes without executing mutations |
| filter | string | conditional | — | Customer query filter (e.g., tag:newsletter, total_spent:>=500); required if customer_ids is omitted |
| customer_ids | array | conditional | — | Explicit list of customer GIDs; required if filter is omitted |
| add_tags | array | no | [] | Tags to add (union with existing tags) |
| remove_tags | array | no | [] | Tags to remove (set difference) |
| mode | string | no | merge | Tag write mode: merge (apply add/remove to existing) or replace (overwrite tags entirely with add_tags only) |
| max_customers | integer | no | 1000 | Run-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
customers — query Inputs: When filter is set: query: , first: 250, pagination cursor. When customer_ids is set: batch query with query: "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.
mode: merge: target = (existing ∪ add_tags) \ remove_tagsmode: replace: target = add_tags (remove_tags ignored) Skip the customer if target == existing (no-op).
customerUpdate — mutation Inputs: For each customer with a non-empty diff: input: { id:
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_ 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
| Error | Cause | Recovery |
|---|---|---|
THROTTLED | API rate limit exceeded | Wait 2 seconds, retry up to 3 times |
userErrors on customerUpdate | Invalid input or read-only customer | Log error, skip customer, continue |
match_count > max_customers | Filter is too broad | Refine filter or raise max_customers deliberately |
Both filter and customer_ids empty | No selection | Abort with parameter error |
| Tag is empty string | Whitespace-only entry | Strip and skip empty values |
| Case-mismatched remove_tag | Tags are case-sensitive | Re-run with exact casing |
Best Practices
dry_run: true first — review the matched count and a sample of previous_tags → new_tags diffs before committing.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.VIP and vip are distinct in Shopify. Standardize casing in your taxonomy.cohort-2026-Q2) so historical cohorts remain identifiable as new tags accumulate.vip-customer-identifier or customer-spend-tier-tagger to feed segment tags from analytics outputs into the customer record.remove_tags as the cleanup pass after a campaign — leaving stale campaign tags clutters segmentation in marketing tools.customer_ids is supplied directly (e.g., from another skill's CSV), the run is fully deterministic — no filter ambiguity.