Start
  ↓
Ask for data sample
  ↓
Analyze data shape
  ↓
Propose collection config
  ↓
User reviews ──────────────┐
  │                        │
  ├─ changes needed ───→ Adjust config ──→ (back to User reviews)
  │
  └─ looks good ───→ Config confirmed
                            ↓
                    More collections? ──────┐
                            │               │
                            ├─ yes ──→ (back to Ask for data sample)
                            │
                            └─ no ───→ All collections confirmed
                                              ↓
                                      Discuss migration approach
                                              ↓
                                            Done

Phase 1: Data Analysis

When user provides data (JSON, CSV, or describes their schema):

Identify field types - text, number, date, relationships, media, rich text
Spot patterns - IDs, timestamps, nested objects, arrays
Note relationships - foreign keys, embedded refs, linked content types
Flag ambiguities - fields that could be multiple types, unclear purposes

Phase 2: Propose Collection Config

Present a Payload collection config based on analysis:

// Example output format
export const Posts: CollectionConfig = {
  slug: 'posts',
  fields: [
    { name: 'title', type: 'text', required: true },
    { name: 'content', type: 'richText' },
    { name: 'author', type: 'relationship', relationTo: 'users' },
    // ...
  ],
}

Explain your reasoning for each field choice. When something could go multiple ways (group vs JSON, text vs textarea, select vs relationship), ask rather than assume.

Phase 3: Iterate with User

Work through uncertainties: required fields, hasMany relationships, rich text vs HTML, custom timestamps vs built-in. Continue until the user confirms the config.

Phase 4: Additional Collections

After each confirmation, ask:

"Are there other content types we should create collections for?"

If yes, loop back to Phase 1 with new data sample.

Common related collections to prompt for:

Media/uploads
Users/authors
Categories/tags
Settings (global)

Phase 5: Migration Approach

Only after ALL collections are confirmed, discuss data import:

Order matters - which collections have no dependencies? Migrate those first
Relationship mapping - how to resolve source IDs to Payload IDs
Media handling - download/re-upload vs external URLs
Rich text - HTML conversion needs or keep raw

Offer to generate a seed script or walk through manual import.

Things to Clarify

Throughout the process, watch for these:

ID references - are they relationships to other collections?
Image/file URLs - upload fields or keep as external URLs?
Nested objects - group, array, or blocks?
Localization - any fields need per-locale values?
Access control - who can read/write this collection?
Related content types - categories, tags, authors that need their own collections?

Critical: Select vs Relationship

This is the most common migration mistake. Data that looks static often needs to be dynamic.

When you see repeated string values (categories, tags, types, statuses):

{ "category": "Technology" }
{ "category": "News" }
{ "category": "Technology" }

Don't assume it's a select field. Ask:

"I see category has values like 'Technology', 'News'. Should this be:

A select field with fixed options (values won't change)

A relationship to a Categories collection (users can add/edit/remove categories later)"

Default to relationship for anything that looks like:

Categories, tags, topics, labels
Authors, assignees, reviewers
Statuses beyond simple draft/published
Types that might expand over time

Use select only for:

Truly fixed enums (yes/no, draft/published/archived)
Options defined by business logic, not content (payment status, priority levels)
Values that would break functionality if changed (role types with code dependencies)

If creating a relationship, remember to add the related collection (Categories, Tags, etc.) to the migration plan.

Reference Documentation

PAYLOAD-FIELD-REFERENCE.md - Complete Payload field type schemas with examples

Common Pitfalls

Issue	How to Handle
User provides partial data	Ask for more samples, especially edge cases
Unclear relationships	Ask user to describe how content types connect
Rich text ambiguity	Clarify: Lexical editor, Slate, or store raw HTML
Missing media collection	Always confirm upload collection exists before referencing
Overly complex nested data	Consider flattening or using blocks instead of deep groups

cms-migration

CMS Migration to Payload

Workflow