Real-Time Coupon Recommendation System Delivers Personalised Shopping Experiences

Industry

Retail

Services

AI & Machine LearningRecommendation SystemsData Engineering

Technologies

PythonTensorFlowApache KafkaRedisAWS

Challenge

A retail chain issued the same coupons to large customer segments, with low redemption and wasted discounts.

It had rich transaction data but no way to personalise offers in real time:

Generic, low-performing coupons.
Wasted discount budget.
No real-time personalisation.
Unused transaction data.

The retailer wanted relevant offers for each shopper.

Solution

Winklix delivered a real-time coupon recommendation system using Winklix's AI accelerators.

Customer models

Machine learning models learn each shopper's preferences from purchase history.

Real-time scoring

Offers are scored and selected in real time at checkout and in the app.

Campaign controls

Marketers set budgets, rules and constraints.

Measurement

Redemption and uplift are tracked to improve models.

Retail Chain solution delivered by Winklix

The Approach

Discovery and planning — We started by understanding business goals, users, constraints and existing systems.
Agile delivery — The solution was built in short sprints with working releases and regular stakeholder demos.
Quality built in — Automated testing, code reviews and security checks were part of every release.
Long-term partnership — After launch, Winklix supported the client with monitoring, enhancements and continuous improvement.

Outcome

The engagement delivered clear, practical results for the client:

Personalised shopping experiences.
More relevant offers for shoppers.
Better use of discount budgets.
Continuous improvement from measured results.

Retail Chain

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Challenge

A retail chain issued the same coupons to large customer segments, with low redemption and wasted discounts.

It had rich transaction data but no way to personalise offers in real time:

Generic, low-performing coupons.

Wasted discount budget.

No real-time personalisation.

Unused transaction data.

The retailer wanted relevant offers for each shopper.

Solution

Winklix delivered a real-time coupon recommendation system using Winklix's AI accelerators.

Customer models

Machine learning models learn each shopper's preferences from purchase history.

Real-time scoring

Offers are scored and selected in real time at checkout and in the app.

Campaign controls

Marketers set budgets, rules and constraints.

Measurement

Redemption and uplift are tracked to improve models.

The Approach

Discovery and planning — We started by understanding business goals, users, constraints and existing systems.

Agile delivery — The solution was built in short sprints with working releases and regular stakeholder demos.

Quality built in — Automated testing, code reviews and security checks were part of every release.

Long-term partnership — After launch, Winklix supported the client with monitoring, enhancements and continuous improvement.

Related Case Studies:

Global Watch Brand

Global Watch Brand Gains a Competitive Edge Through Consumer Behaviour Insights

Read full post

American Snack Company

Fewer Errors and More Insights Through Automation and Dashboards for an American Snack Company

Read full post

HR Tech Start-up

Building an AI-Powered Recruitment SaaS Platform from the Ground Up

Read full post

Essential

Analytics

Marketing

Real-Time Coupon Recommendation System Delivers Personalised Shopping Experiences

Challenge