Offer Engine

Project Overview

The Offer Engine was a foundational platform initiative aimed at transforming how promotions, discounts, and coupons are created, managed, and experienced across Decathlon’s ecosystem.

Previously, offers were managed through fragmented systems with limited flexibility, poor scalability, and inconsistent user experience. This led to missed revenue opportunities, poor discoverability of offers, and frequent customer frustration.

The new Offer Engine was designed as a centralized, scalable, and intelligent system that:

• Enables business teams to create complex promotional rules

• Automatically surfaces the most relevant offers to users

• Integrates seamlessly across web, app, and in-store journeys

It was not just a backend revamp—but a full-stack UX + system redesign impacting both internal tools (BO) and customer-facing experiences (FE).

My Role: I led the UX/UI design across both the customer experience and the internal offer management system. My work involved simplifying complex promotional logic into intuitive interfaces, designing scalable UI patterns for multiple offer types, and ensuring seamless integration of offers across discovery, cart, and checkout journeys. I collaborated closely with product, engineering, and business teams to align user needs with technical capabilities and business goals, while also contributing to the adoption of Decathlon’s new design system.

Problem Statement:

Decathlon’s existing offer and coupon system was fragmented, difficult to scale, and limited in supporting modern promotional strategies. From a user perspective, offers were often hard to discover, understand, or apply—leading to missed savings and reduced trust.

From a business standpoint, the system lacked flexibility to create complex campaigns, personalize offers, or respond quickly to market needs. Additionally, performance issues and system limitations during high-traffic periods negatively impacted conversion and reliability.

The challenge was to design a unified system that could balance business complexity, technical scalability, and user clarity.

Existing app Pain Points:

Customer Experience Issues:

• Difficulty discovering relevant offers across the journey

• Confusing coupon application with unclear eligibility rules

• Hidden conditions (min cart value, product restrictions)

• Coupons failing or expiring unexpectedly

• Poor visibility of applied discounts at cart and product level

👉 ~10–13% of customer issues were related to coupons/offers

Business & System Issues:

• Limited ability to create complex promotional rules

• No centralized system → fragmented offer creation

• Poor scalability during high-traffic events (sales, campaigns)

• High dependency on engineering for launching campaigns

• Lack of personalization and targeting capabilities

Information architecture:

The system was redesigned into two key layers:

1. Offer Creation & Management (Back Office)

• Centralized dashboard to create, manage, and monitor offers

• Modular structure for:

  • Product-level offers

  • Cart-level offers

  • Customer-level offers

• Bulk upload capabilities (CSV-based)

• Role-based access for different stakeholders

2. Offer Discovery & Application (Customer Experience)

• Offers surfaced across:

  • Product Listing Page (PLP)

  • Product Detail Page (PDP)

  • Cart & Checkout

• Automatic application of eligible offers

• Clear visibility of discounts and savings

Wireframes Mockups:

• Explored multiple ways to present offers:

  • Inline vs dedicated offer section

  • Auto-applied vs manual coupon entry

• Tested clarity of offer descriptions (auto-generated vs manual)

• Iterated on prioritization logic (“Best offer for you”)

• Designed UI for complex scenarios like:

  • Multi-buy

  • Bundles

  • Tiered discounts

Final Direction: A system-driven, auto-applied offer experience with clear visibility and minimal user effort.

Solution:

Key Features:

• Centralized Offer Engine: Single platform to create, manage, and track all promotions

• Flexible Offer Types:

  • Percentage & fixed discounts

  • Bundles & sets

  • Tiered pricing

  • BOGO

  • Coupon codes (visible & invisible)

• Smart Eligibility & Personalization:

  • Based on cart value, product type, user segment

  • Channel-specific offers (web, app, in-store)

• Auto-Apply Best Offer Logic: System automatically selects the most relevant offer

• Real-Time Validation Engine: Faster, reliable coupon application even at scale

UI Design Highlights

Customer Experience (FE):

• Offer visibility across journey (PLP → PDP → Cart)

• Short descriptions on product cards improved clarity & CTR

• Offer descriptions auto-generated for consistency

• Clear breakdown of discounts at product and cart level

• “i” icon for expandable offer details

Back Office (BO):

• Dashboard with filters for offer status (Active, Draft, Expired)

• Simplified offer creation flow with modular inputs

• Auto-generated descriptions based on inputs

• CSV upload for bulk campaign creation

• Channel selection for omni-channel promotions

Outcomes & Impact:

• Improved Offer Discoverability → Higher CTR on product listings

• Reduced coupon-related complaints by targeting a 30% reduction goal

• Increased successful coupon application rate by ~20%

• Enabled system to handle ~500 TPS (transactions per second)

• Increased conversion and AOV through better offer visibility and application

• Reduced dependency on engineering → faster campaign launches

• Built foundation for 35% revenue contribution from offers

  
  

Key Learnings:

• Designing for promotions is a balance between business flexibility and user clarity

• Automation (auto-apply offers) significantly reduces cognitive load

• Transparency (clear savings, conditions) builds user trust

• Internal tools UX is as critical as customer-facing UX

• Scalable systems require thinking beyond screens → into rules, logic, and architecture