Challenge Statement

Design and develop an Al-driven, location-based, multi-tenant Loyalty

System that enables organizations across industries to create, manage,

and scale intelligent customer engagement programs that drive

retention, behavior-based insights, and personalized service delivery

Assignment Objective

Participants must build a prototype that:

-Creates dynamic, customer-centric loyalty programs based on behavior,

location, and long-term engagement.

-Leverages Al to personalize offers, predict churn, reactivation, and segment

users based on real-time data.

-Integrates with existing digital ecosystems (e.g., mobile apps, payment

systems, CRMs) for real-time activity tracking and automated service offers.

-Includes a centralized Loyalty Operations Dashboard for configuring rules,

monitoring performance, and managing customer interactions using datadriven insights.

Core Functional Modules to Include

1. Loyalty Engine

- Logic for earning and redeeming points, badges or service-based benefits

- Support for models like points, tiers, milestones

- Rules based on customer actions (e.g., purchases, check-ins, referrals)

Al-driven behavior analysis to adapt rewards dynamically

2. Customer Wallet & Profile

- Tracks points, service eligibility, and engagement history

Loyalty tier and location-based activity logs

- Optional: referral tracking

- Al-powered segmentation for personalized experiences

ability to redeem thier point via the channel

3. Admin Dashboard

Configure loyalty rules and monitor program performance

-View customer activity and manage eligibility-based offers

Manual override tools (e.g., adjust points, approve offers)

- Al insights and churn prediction to guide decision-making

-logic to allow for redemption of points based on rules set by admin

4. User Interface (Web or Mobile)

-View points, service eligibility, and location-based offers

-Notifications for new benefits, tier upgrades, or expiring points

-Optional: gamification (badges, progress bars)

-Al-generated recommendations for offers or actions

Security Requirements

Participants must implement:

- Authentication & access control

- Data encryption (in transit and at rest)

- Fraud prevention for point/service transactions

- Secure APIs and audit logging

- Controls for point transfers or resale (if applicable)

Al Integration Suggestions

Participants are encouraged to include Al features such as:

- Behavior prediction for proactive engagement

- Churn detection to trigger retention workflows

- Smart segmentation for targeted campaigns

- Natural language summarization of user feedback

- Location-aware intelligence for context-based offers

Points Earning Logic

Define how users earn points or qualify for services:

- Based on customer actions relevant to the organization (e.g.,

purchases, visits, referrals, digital engagement)

- Location-based triggers (e.g., store visits, event check-ins)

- Include limits, verification, and secure logging

Technology Suggestions (Optional)

Frontend

- React

- Flutter

- Angular

Backend

- Node.js

- Python (FastAPI or Flask)

- Java Spring

Database

- PostgreSQL

- MongoDB

- Firebase

Hosting & Deployment

- Localhost for demo Dartiredrla bers

- Optional: Docker, Render, Heroku, or cloud platforms

Deliverables

- Working prototype (web or mobile)

- Source code (GitHub or ZIP)

-Demo video (3-5 minutes)

- Final presentation slide deck

Target Users

-Enterprise Teams (e.g., Marketing, Customer Service, IT Ops, Compliance)

-Digital Transformation Departments

-Innovation Labs

Awards and Opportunities

-Cash Prizes & Tech Gadgets

-Access to Xplug's AI Lab & APIs for further development

Judging Criteria

-Innovation & Originality

25%

-Technical Implementation

25%

-UI/UX and Human Interaction

20%

-Scalability & Architecture

10%

-Presentation & Demo

10%

-Team Collaboration

10%

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