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Case Studies

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Driving redemption growth through ML-powered targeting

Driving redemption growth through ML-powered targeting

Driving redemption growth through ML-powered targeting

How a specialty retailer used data-led insights to personalize campaigns and boost revenue

How a specialty retailer used data-led insights to personalize campaigns and boost revenue

Redemption increase

Households analyzed

Retargeting campaigns

Generic offers

The challenge

The challenge

UInlocking consumer data for better offer redemptions

UInlocking consumer data for better offer redemptions

A specialty retailer wanted to personalize pricing and promotions across its multiple business units. Massive volumes of siloed data – spanning customers, products, demographics, transactions, and more – led to disconnected campaigns and low redemption rates, limiting opportunities for incremental foot traffic and sales.

Key challenges

  • Siloed data across business units

  • Ineffective personalization strategies

  • Low visibility of localized assortment needs

  • Uncoordinated promotions hampered redemption

The solution

Creating a 360-degree customer view for retargeting campaigns

Creating a 360-degree customer view for retargeting campaigns

Customer markers

Multiple behavioral attributes

Purchase pattern tracking

Life stage and segment focus

Localized offers

ML-driven personalization

Store-level product mapping

Retargeting via customer intelligence

Implementation approach

Implementation approach

1

Unified data ecosystem

  • High household profiles

  • Cross-functional collaboration

  • Centralized data sources

2

AI-powered targeting

  • Dynamic ML models

  • Redemption pattern analytics

  • Targeting refinement

3

Continuous optimization

  • Data-driven tuning

  • Collaborative strategy

  • Iterative model updates

The impact

The impact

Redemption growth with localized targeting strategy

Redemption growth with localized targeting strategy

Revenue growth

Redemption boost

  • Optimized promotional outcomes

  • Boosted store visitation

  • Prompt revenue response

Increased ROI

Generic offer reduction

  • Refined audience relevance

  • Lowered offer redundancy

  • Greater customer stickiness

Campaign scale

Retargeting launches

  • Unified business functions

  • Consolidated targeting system

  • Improved cross-sell reach

Looking ahead

Looking ahead

Predictive analytics

  • Forecasting trends with precision

Dynamic customer profiles

  • Adapting to evolving preferences

Omni-channel expansion

  • Bridging digital and physical touchpoints

All rights reserved © 2025 Fractal Analytics Inc.

Registered Office:

Level 7, Commerz II, International Business Park, Oberoi Garden City,Off. W. E.Highway, Goregaon (E), Mumbai City, Mumbai, Maharashtra, India, 400063

CIN : U72400MH2000PLC125369

GST Number (Maharashtra) : 27AAACF4502D1Z8

All rights reserved © 2025 Fractal Analytics Inc.

Registered Office:

Level 7, Commerz II, International Business Park, Oberoi Garden City,Off. W. E.Highway, Goregaon (E), Mumbai City, Mumbai, Maharashtra, India, 400063

CIN : U72400MH2000PLC125369

GST Number (Maharashtra) : 27AAACF4502D1Z8

All rights reserved © 2025 Fractal Analytics Inc.

Registered Office:

Level 7, Commerz II, International Business Park, Oberoi Garden City,Off. W. E.Highway, Goregaon (E), Mumbai City, Mumbai, Maharashtra, India, 400063

CIN : U72400MH2000PLC125369

GST Number (Maharashtra) : 27AAACF4502D1Z8