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Loyalty Revamp

Reimagining the loyalty program to boost retention and repeat purchases

Role

Product Analytics

Data-led strategy

Type

Retention System

Redesign

Tiers

7 → 4

Simplified

Target

+5% CEA

ROI >100%

The Problem

The existing loyalty program was underperforming on both user value and business economics.

User Problems

Rewards did not feel meaningful or differentiated across tiers
Low clarity on progression and benefits
Weak motivation to upgrade tiers or stay engaged

Business Problems

Suboptimal ROI (~60%) on loyalty spends
Low retention of high-value Gold / Black tier users
Increasing competition offering better reward programs

Objective

🎯

Improve retention of high-value users (Gold / Black tiers)

📈

Increase Customer Engagement Actions (CEA) by +4%

💰

Achieve >100% ROI at the program level

Key Insight

The problem wasn't just rewards — it was system design.

01

Too many tiers

Low comprehension

02

Weak progression

No aspiration

03

Poor visibility

Low perceived value

04

Misaligned economics

High spend, low returns

Approach

Data-driven research across three workstreams.

📊

User Segmentation via Clustering

Used k-clustering to analyze user behavior distribution — identified 4 optimal tiers instead of 7

🌍

Industry Benchmarking

Studied 20+ loyalty programs across industries to derive best practices: tier simplification, instant gratification, strong upgrade nudges

💰

Economic Modeling

Analyzed benefit claim rates and reward spends vs. ROI — found higher ROI at lower tiers, lower at higher tiers → led to redistribution of benefits strategy

Solution

Redesigned as a simplified, high-visibility, behavior-driven loyalty program.

🏅 Tier Simplification: 7 → 4

Bronze
Silver
Gold
Black

~81%

Bronze users

~16%

Silver users

~2%

Gold users

~1%

Black users

Instant Gratification Layer

Rewards start from first contest join — leverages endowment effect and early engagement loops

Progression Nudges

Dynamic UI: 'Play X more to upgrade' and maintain vs. upgrade indicators embedded in contest flows, home screen, and reward shop

Visibility & Value Communication

Show total rewards earned (₹ + coins), active benefits, and next-tier benefits (FOMO) to increase perceived value

Spend Optimization Strategy

More benefits for lower tiers (higher ROI), controlled spends for higher tiers — bonus coin structures + non-monetary benefits (exclusive contests)

Gamification + Retention Hooks

Tier-based locked rewards, upgrade animations, and feedback loops to drive continuous re-engagement

Experimentation & Metrics

Primary Metric

CEA (Customer Engagement Actions)

Target: +5% uplift

Secondary Metrics

  • Tier upgrade rate
  • Retention by tier
  • Benefit claim rate
  • ROI per tier

Guardrails

Maintain overall program ROI >100%Avoid excessive reward leakage

My Role

Product Analytics — led the data-driven structuring of the loyalty system.

User Segmentation

Performed clustering analysis to identify optimal tier structure (7 → 4)

ROI & Spend Analysis

Analyzed benefit claim rates and spends per tier to inform the redistribution strategy

Industry Benchmarking

Researched 20+ loyalty programs to extract best practices and competitive benchmarks

Tier Redesign

Contributed to threshold exploration and level progression logic for the new 4-tier system

Experiment Planning

Supported metric definition, guardrail design, and experiment measurement framework

Key Product Decisions

01

Reduce Tier Complexity

Fewer tiers improved user comprehension and created clearer progression — making upgrade motivation more tangible

02

Start Rewards Early

Introduced rewards from the first contest join to leverage the endowment effect and increase engagement at the lower funnel

03

Optimize for ROI, Not Just Rewards

Shifted benefit allocation toward lower tiers (higher ROI) while controlling spends at higher tiers — balancing business and user value

04

Embed Loyalty into the Core Loop

Made loyalty a part of gameplay, not a standalone feature — nudges embedded in contest flows, home screen, and reward shop

Challenges

Determining optimal tier thresholds given complex user distribution
Balancing user aspiration with sustainable business cost
Migrating existing users to new tiers without breaking their experience
Designing for both power users and casual players simultaneously

Outcome

Retention signals

High-value tier improvement

≥100%

Target ROI

Program-level economics

4 tiers

Simplified from 7

Improved comprehension

Key Learnings

🏗️

Loyalty is a system problem, not a feature problem — it requires end-to-end redesign, not patches

Simplicity drives engagement more than complexity — fewer tiers with clear value beats elaborate structures

Early rewards significantly impact retention — the endowment effect kicks in from the very first interaction

📐

Economics must be built into product design — ROI is not an afterthought, it's a design constraint