E-commerce
Customers
Repeat e-commerce buyers: identity, contact, default shipping, lifetime stats.
Schema
The canonical field set, printed as it ships.
9 fields with multilingual hints (DE / FR / IT / EN / ES) and field-level validators. Any source column that resolves to one of these is mapped by the cascade — most of them on the deterministic layers, with no LLM call.
customers_v1- fields
- 9
- required
- 2
- validated
- 2
- hints
- 28
| Canonical column | Type | Required | Validators | Header hints the cascade matches |
|---|---|---|---|---|
id | string | yes | — | matched on the column name |
email | yes | email | e-mailmailcorreocourriel | |
first_name | string | — | — | vornameprenomprénomnombregiven name |
last_name | string | — | — | nachnamenomcognomeapellidosurname |
phone | phone | — | phone | telefontéléphonetelefonophonemobile |
default_shipping_address_id | string | — | — | matched on the column name |
created_at | date | — | — | matched on the column name |
lifetime_orders | number | — | — | anzahl bestellungennombre de commandesnumero ordininúmero de pedidos |
lifetime_value | number | — | — | lifetime valueumsatz gesamtchiffre d'affaires totalricavi totalivalor total |
Read the same definition as JSON at GET /v1/templates/customers_v1. A hint match resolves on layer 2 — no LLM call, no token spend, just the flat per-map fee. Hover a validator id to see what it checks.
- 9 canonical fields
- 2 required
- 2 validated
- 28 header hints
- E-commerce pack
Try it
A real file, a real call, one template id.
8 rows, mixed headers, lifetime stats. Fully synthetic — safe to share, commit, and run in CI.
curl -X POST https://api.adaptivmapr.com/v1/uploads \
-H "Authorization: Bearer $ADAPTIVMAPR_API_KEY" \
-F "file=@customers_sample.csv" \
-F "template=customers_v1"adaptivmapr.match_headers({
template_id: "customers_v1",
headers: ["id", "email", "first_name", "last_name"]
})Ready when you are
Put customers in production — without shipping raw records.
Schema-only mapping leaves only headers and a handful of clamped samples. Add full-data when you need row-level AI, routed in-region under a BAA.