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Loyalty Program

Persona

Role: Loyalty Program Director at a regional retail chain.

You manage a customer rewards program across 80 stores. Members earn points on purchases, advance through tiers based on spending, and redeem points for discounts and exclusive products. The existing program runs on a legacy vendor platform with limited flexibility -- adding new reward types requires a multi-week vendor engagement.

Business Problem

The legacy platform charges per-transaction fees that scale poorly, does not support custom tier rules, and provides limited visibility into member behavior. Marketing wants to launch seasonal promotions and partner rewards, but the vendor's configuration options are too rigid. You need:

  • A flexible member registry with tier management and point balances.
  • Transaction-level point tracking that supports multiple earning sources.
  • A reward catalog with availability controls and dynamic point costs.

Four-Step Application

This scenario works best as a four-step, human-in-the-loop application. The existing object model already gives this scenario a strong delivery backbone through Member, PointTransaction, and Reward.

  • Mission metric focus: better conversion, lower service friction, and stronger margin protection.
  • Human + AI pattern: Each step combines structured workflow data with chat assistance, background generation, document understanding, and accessible interaction patterns when they improve the experience.

Step 1. Capture demand and context

  • Goal: Make it easy for the user to start the Loyalty Program journey with complete, trusted context.
  • Required data: Member context such as the core workflow data.
  • AI support: Use chat to guide intake, generate clearer prompts, create accessible summaries, and assist with voice or vision-led capture when a form alone is not the best experience. EAI can support structured intake, chat workflows, and document-centred capture today; richer native multimodal capture may still need workflow extensions or connected services.
  • Business impact: Improve completion rate, reduce first-touch effort, and raise customer or staff confidence in the UX from the very first interaction.
  • EAI delivery: Model the intake as tenant-isolated object types and resources, then use actions, chat workflows, and document indexing or classification to keep the initial record complete and usable.

Step 2. Prepare the decision

  • Goal: Turn the captured context into the next best action for Loyalty Program without forcing the human reviewer to assemble the case manually.
  • Required data: Member state and history.
  • AI support: Run background summarisation, extraction, classification, recommendation drafting, and answer generation so a reviewer sees a prepared case instead of raw fragments. EAI delivers the structured records and AI workflow hooks for this today; specialised scoring engines, external rules, or advanced reasoning controls may still need integration work.
  • Business impact: Reduce cycle time, improve quality and consistency, and protect the mission-critical metric before the case moves into execution.
  • EAI delivery: Link records across the scenario, persist decision state as resources, and use workflow actions plus chat assistance to keep humans in control while AI prepares the work.

Step 3. Execute and collaborate

  • Goal: Coordinate the actual work, handoffs, approvals, and user updates needed to deliver the service or outcome.
  • Required data: PointTransaction execution state.
  • AI support: Draft replies, produce work packets, monitor exceptions in the background, and surface the next action for each operator. EAI can orchestrate tenant-isolated records, actions, chats, and document workflows today; deeper system-to-system automation may require additional connectors or workflow capability.
  • Business impact: Increase operator productivity, reduce rework across handoffs, and improve service consistency across the application journey.
  • EAI delivery: Use linked object types, actions, resource updates, and workflow-triggered AI assistance so the team can execute in one model instead of splitting work across disconnected tools.

Step 4. Resolve, explain, and improve

  • Goal: Close the loop with a clear outcome, an understandable explanation, and feedback that improves the next case.
  • Required data: final status, outcome, audit history, and follow-up signals across Member, PointTransaction, and Reward.
  • AI support: Generate outcome summaries, customer-friendly answers, compliance-ready notes, management insights, and accessible follow-up content. EAI can store outcome records and support answer generation today, while richer proactive agents, advanced analytics, or channel-specific accessibility features may need additional product capability.
  • Business impact: Increase trust, quality, and measurable business value through better conversion, lower service friction, and stronger margin protection.
  • EAI delivery: Keep the full audit trail in structured resources, use AI workflows to explain outcomes, and feed the resulting signals into future product, service, and operational improvement work.

EAI Platform Support By Step

EAI provides the safe service boundary for Loyalty Program through Object Types, tenant-scoped resources, document processing, chat workflows, and CLI verification. For this scenario, the main records are Member, PointTransaction, and Reward.

Process stepWhat EAI providesCalling pattern
Step 1. Capture demand and contextTenant-scoped intake resources for Member context such as the core workflow data. Object Type validation, starter forms, optional document intake, and chat-guided capture keep the first record complete.Define fields in src/eai.config/object-types.ts, run eai types validate and eai types seed, create initial Member records with useResources('Member') or eai resources create Member, and keep browser calls behind /api/eai/....
Step 2. Prepare the decisionLinked resource queries over Member state and history. Search, schema checks, document classification or RAG indexing, and chat summaries turn raw context into a prepared decision.Use useResources('Member') list/query/search patterns, verify shape with eai resources schema, use useDocuments().upload/classify/ragIndex, eai docs upload, eai docs classify, and eai docs index where supporting material exists, and send decision-support prompts through useChat(workflowId, 'chat') or eai chat send.
Step 3. Execute and collaborateResource updates and actions for PointTransaction execution state. Status changes, assignments, notes, generated work packets, and chat support keep humans in control during execution.Model actions in the Object Type code, call client.resources.executeAction(type, id, action) or the app hook equivalent, update records through the app service layer, and verify with eai resources get/list/query.
Step 4. Resolve, explain, and improveOutcome resources for final status, outcome, audit history, and follow-up signals across Member, PointTransaction, and Reward. Audit-friendly links, indexed final documents, reporting snapshots, and answer generation make the result explainable and reusable.Persist outcomes as resources, index final material with eai docs index or useDocuments().ragIndex, send explanation prompts with useChat or eai chat stream, and use eai resources aggregate/search for reporting checks.

Prompt, Code, And Service Pattern Mapping

The Object Type code example on this page is the implementation contract for the EAI platform services. eai-gofer should read that code as the source of truth for which resource, document, and chat calls belong in the app.

Use this prompt shape when asking eai-gofer or another coding agent to implement the scenario:

Use the EAI App Template. Model Loyalty Program with Object Types for Member, PointTransaction, Reward. Use useResources for records and actions, useDocuments for uploads/classification/RAG where documents appear, useChat for workflow assistance, and verify with eai types/resources/docs/chat commands. Use eai publicapi only when no named command covers the required platform call.
Scenario artifactHow it maps to EAI service calls
Four-step processStep 1 becomes resource creation, Step 2 becomes resource query/search plus optional document or chat preparation, Step 3 becomes resource update/action calls, and Step 4 becomes outcome persistence plus explanation/reporting calls.
Object Type definitionseai types validate, eai types seed, and eai resources schema make the model available and checkable before UI work starts.
Properties and indexesFields become useResources payloads, filters, list views, and eai resources create/list/query/search checks. Indexed fields should support lookup and triage, not duplicate canonical records.
Links between Object TypesRelationships become linked-resource UI, timeline context, and audit trails that app code loads through resource queries rather than separate bespoke stores.
Actions and status fieldsWorkflow buttons and operator transitions call resource action/update helpers, then verify state with eai resources get/list/query.
Document and chat promptsPrompts should call the platform documents and chat patterns: useDocuments().upload/classify/ragIndex, eai docs upload, eai docs classify, and eai docs index for documents, and useChat, eai chat send, or eai chat stream for conversational assistance.

Object Types

NameKey PropertiesLinksActions
Membercustomer, tier, points, joinDatehas many PointTransactionsenroll, upgrade-tier, deactivate
PointTransactionmember, amount, source, descriptionbelongs to Memberearn, redeem, adjust
Rewardname, pointsCost, category, availability(standalone)create, update-availability, retire

CLI Workflow

  1. Scaffold the app

    eai init loyalty-program
  2. Authenticate and pull environment

    eai login
    eai env pull --include-secrets
    If you are an external developer, see [Configuration](/docs/configuration) for login and local environment setup.
  3. Define Object Types

    Add Member, PointTransaction, and Reward to src/eai.config/object-types.ts.

  4. Validate and seed

    eai types validate
    eai types seed
    Tenant: loyalty-program
    ✔ Member — 4 props, 1 link, 3 actions
    ✔ PointTransaction — 4 props, 1 link, 3 actions
    ✔ Reward — 4 props, 0 links, 3 actions

    ✔ All Object Types are valid
  5. Enroll a member

    eai resources create Member \
    --data '{"customer": "maria.garcia@example.com", "tier": "silver", "points": 0, "joinDate": "2026-03-01"}'
  6. Record a point transaction

    eai resources create PointTransaction \
    --data '{"member": "member-001", "amount": 150, "source": "purchase", "description": "In-store purchase at Downtown location"}'
  7. List available rewards

    eai resources list Reward --filter 'availability=available'
  8. Start local development

    eai dev

Code Example

// src/eai.config/object-types.ts
export const objectTypes = {
'loyalty-program': [
{
name: 'Member',
displayName: 'Member',
description: 'A loyalty program member with a tier level and point balance',
properties: [
{ name: 'customer', type: 'text' as const, required: true, indexed: true },
{ name: 'tier', type: 'select' as const, required: true, defaultValue: 'bronze',
options: [
{ label: 'Bronze', value: 'bronze' },
{ label: 'Silver', value: 'silver' },
{ label: 'Gold', value: 'gold' },
{ label: 'Platinum', value: 'platinum' },
],
},
{ name: 'points', type: 'number' as const, required: true },
{ name: 'joinDate', type: 'date' as const, required: true },
],
linkTypes: [
{ name: 'pointTransactions', target: 'PointTransaction', cardinality: 'many' as const },
],
actions: [
{ name: 'enroll', displayName: 'Enroll Member' },
{ name: 'upgrade-tier', displayName: 'Upgrade Tier' },
{ name: 'deactivate', displayName: 'Deactivate Member' },
],
status: 'published' as const,
},
{
name: 'PointTransaction',
displayName: 'Point Transaction',
description: 'A record of points earned, redeemed, or adjusted for a loyalty member',
properties: [
{ name: 'member', type: 'text' as const, required: true },
{ name: 'amount', type: 'number' as const, required: true },
{ name: 'source', type: 'select' as const, required: true,
options: [
{ label: 'Purchase', value: 'purchase' },
{ label: 'Promotion', value: 'promotion' },
{ label: 'Referral', value: 'referral' },
{ label: 'Redemption', value: 'redemption' },
{ label: 'Adjustment', value: 'adjustment' },
],
},
{ name: 'description', type: 'text' as const, required: false },
],
linkTypes: [
{ name: 'member', target: 'Member', cardinality: 'one' as const },
],
actions: [
{ name: 'earn', displayName: 'Earn Points' },
{ name: 'redeem', displayName: 'Redeem Points' },
{ name: 'adjust', displayName: 'Adjust Points' },
],
status: 'published' as const,
},
{
name: 'Reward',
displayName: 'Reward',
description: 'A redeemable reward in the loyalty program catalog',
properties: [
{ name: 'name', type: 'text' as const, required: true, indexed: true },
{ name: 'pointsCost', type: 'number' as const, required: true },
{ name: 'category', type: 'select' as const, required: true,
options: [
{ label: 'Discount', value: 'discount' },
{ label: 'Free Product', value: 'free-product' },
{ label: 'Experience', value: 'experience' },
{ label: 'Partner Offer', value: 'partner-offer' },
],
},
{ name: 'availability', type: 'select' as const, required: true, defaultValue: 'available',
options: [
{ label: 'Available', value: 'available' },
{ label: 'Limited', value: 'limited' },
{ label: 'Sold Out', value: 'sold-out' },
{ label: 'Retired', value: 'retired' },
],
},
],
linkTypes: [],
actions: [
{ name: 'create', displayName: 'Create Reward' },
{ name: 'update-availability', displayName: 'Update Availability' },
{ name: 'retire', displayName: 'Retire Reward' },
],
status: 'published' as const,
},
],
};

Key Takeaways

  • Flexible tier management. Member tiers are defined as select options, making it straightforward to add new tiers or adjust the tier structure without schema changes.
  • Multi-source point earning. PointTransactions track the source of every point change, enabling marketing to measure which earning channels drive the most engagement.
  • Reward catalog independence. Rewards are standalone objects with availability controls, allowing the marketing team to launch, limit, and retire rewards without affecting member records.
  • Full transaction history. Every point earn, redeem, and adjustment is recorded, providing the audit trail needed for financial reconciliation and fraud detection.