E-commerce pack

Customers CSV import API

Import e-commerce customers from CSV. Email-validated, phone-validated, lifetime stats carried as numbers.

low riskcustomers_v1
30-second curl
curl -X POST https://api.adaptivmapr.com/v1/uploads \
  -H "Authorization: Bearer $ADAPTIVMAPR_API_KEY" \
  -F "template=customers_v1" \
  -F "file=@your_data.csv"
→ 9 canonical fields · 2 validated · low risk

Canonical columns

The whole schema, printed as it ships.

Every canonical column, the type each row carries, whether it is required, the field-level validators that fire on commit, and the multilingual header hints the cascade resolves against. This is the shipped definition, not a summary of it.

customers_v1
fields
9
required
2
validated
2
hints
28
Canonical columnTypeRequiredValidatorsHeader hints the cascade matches
idstringyesmatched on the column name
emailemailyesemaile-mailmailcorreocourriel
first_namestringvornameprenomprénomnombregiven name
last_namestringnachnamenomcognomeapellidosurname
phonephonephonetelefontéléphonetelefonophonemobile
default_shipping_address_idstringmatched on the column name
created_atdatematched on the column name
lifetime_ordersnumberanzahl bestellungennombre de commandesnumero ordininúmero de pedidos
lifetime_valuenumberlifetime 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, 5 languages

Why it exists

Written for the file you actually receive.

The Customers template is the buyer-side counterpart to Orders. Each row carries an id, a validated email (required), optional first and last names, an optional phone, an optional default shipping address id, a created_at timestamp, and two lifetime stats: lifetime_orders and lifetime_value. The lifetime fields are denormalised because most downstream tools expect them on the customer row rather than computed at query time; that denormalisation is per-workspace policy, and the template carries it cleanly. E-commerce teams use this template to migrate between platforms, to seed a CDP, to refresh an RFM segmentation, and to feed a loyalty program. The cascade catches multilingual "lifetime value" variants without escalation because that header is one of the most-localised in retail data.

email is required because cross-platform customer identity is built on email — phone-only customers belong in a separate template. lifetime_value carries the same locale-tolerant number parsing as the orders template. created_at is the customer's creation timestamp, not their first order — those two often diverge and the template preserves the difference.

Migration scenarios & the foreign headers they ship

Migration scenarios for the Customers template: cross-platform customer base migrations during a re-platforming project, CDP seeding for the first time (Segment, mParticle, RudderStack), refreshing an RFM segmentation before a marketing campaign, and feeding a loyalty program with a year of order-derived lifetime stats. Foreign headers we see weekly: "Customer ID / Kundennr / Numéro client / Email / E-Mail / Correo / Courriel / Vorname / Prénom / Nombre / Nachname / Nom / Apellido / Telefon / Téléphone / Teléfono / Default Shipping / Lieblings-Lieferadresse / Anzahl Bestellungen / Nombre de commandes / Número de pedidos / Lifetime Value / Umsatz Gesamt / Chiffre d'affaires total / Ricavi totali". The cross-platform header coverage is heavy on commerce-specific vocabulary that does not appear elsewhere in the catalogue.

The cascade

Five layers, and the cheapest one wins.

Layers run in order and stop the moment a column resolves. That is the single biggest cost lever in the system: a column caught on layer 2 never reaches the metered layer 5.

  1. L1Statisticsno LLM

    Auto-accepts a header that past confirmations already resolved the same way, at {minN:100, minRatio:0.95} or {minN:20, minRatio:1.00}.

  2. L2Heuristicno LLM

    Normalises accents, punctuation and whitespace, then compares against the column name, the label, and every registered hint (DE / FR / IT / EN / ES).

  3. L3Fuzzyno LLM

    Token-set ratio plus Levenshtein over the normalised strings. Auto-accepts at 0.80 — it absorbs typos and reordered words.

  4. L4Semanticcheap, cached

    Embedding cosine between the header and the field’s label + hints. Catches the long tail of paraphrases.

  5. L5LLMmetered

    Everything still unresolved goes up in ONE batched, collision-aware call, constrained to this template’s column set so it cannot invent a field.

Try it

One template id, two ways in.

REST for your import pipeline, MCP for your editor. Both run the same cascade and both honour the same schema-only clamp.

REST · POST /v1/uploads

Name the template; the cascade picks up the rest. The canonical definition is read-only at GET /v1/templates/customers_v1.

bash
curl -X POST https://api.adaptivmapr.com/v1/uploads \
  -H "Authorization: Bearer $ADAPTIVMAPR_API_KEY" \
  -F "template=customers_v1" \
  -F "file=@your_data.csv"
→ upload created · mappings ready · confirm before commit

MCP · Cursor / Claude Desktop

Drop AdaptivMapr into your editor and call the same cascade as a tool. Schema-only calls leave only column names and up to three clamped sample rows.

mcp
// In Cursor or Claude Desktop with the AdaptivMapr MCP server installed:
adaptivmapr.match_headers({
  template_id: "customers_v1",
  headers: ["id", "email", "first_name", "last_name"]
})
schema-only · headers and ≤3 rows, 80 chars each
MCP install instructions

Questions

Customers CSV import — FAQ

Use the CRM Accounts template alongside Customers — the e-commerce row is person-level; B2B accounts are company-level. Link via a custom field on a forked Customers row.
They can be left null on import and computed downstream. The template carries them if the source ships them; otherwise they stay null.
Add a `tags` array field via a fork. The canonical row stays narrow because tag taxonomies vary too much across teams.
They do not, automatically — the values reflect the moment of import. Most teams re-derive both at warehouse-load time from the orders table and overwrite the customer row periodically.

Ready when you are

Map customers in production — without shipping raw records.

Schema-only mode leaves only headers and a handful of clamped samples. Add full-data when you need row-level AI, routed in-region under a BAA.

No free tier · $10 prepaid wallet to start · every map draws a small flat fee, deterministic ones included