Improving e-commerce experiences
Transforming Customer Experiences with AI for a Leading Grocery Retailer in Malaysia
Our client is one of Malaysia’s largest grocery retailers, catering to over 100,000 customers daily in both physical stores and online. Operating across 50 stores in 8 states, our client manages two dozen grocery retail brands, 5 manufacturing locations, and 10 distribution facilities, contributing to an annual revenue exceeding $100 million.
10%
1.5x
30+
1PM+
Customer and transaction data analyzed
Key Takeaways
- IProcessed terabytes of customer data and shopping behaviors to build an AI recommendation model.
- IDeveloped distributed data pipelines on Azure Cloud for ETL, enrichment, and prediction.
- IRealized a measurable Return on Investment (ROI) by increasing basket size through recommended products.
- IEstablished model training and tuning mechanisms using user-generated signals and feedback.
Challenge
Our client identified a prevalent issue among customers: the challenge of finding products that align with their preferences. As a result, customer interaction and interest dwindled, leading to decreased engagement, reduced loyalty, and a decline in repeat business. The subpar search experience resulted in customer frustration, dissatisfaction, and potential revenue loss. Additionally, they encountered difficulties in fully leveraging the extensive data at their disposal, including customer, transaction, and behavioral data, to generate valuable insights and enhance convenience for each customer across all channels.
Solution
In just four weeks, we designed data cleaning operations and implemented a machine learning engine that provided real-time recommendations and personalized upsell and cross-sell suggestions to millions of customers using the client’s web or mobile apps. Every interaction a customer had with the client’s products generated feedback for the engine, contributing to the continuous enhancement of performance and accuracy in recommendations and the overall shopping experience.
How we did it
Analytics & AI/ML
- Real time data analysis
- Predictive analytics
- Deep learning
- Neural Networks
- 2D & 3D Mapping
- Generative Adversarial Networks
Strategy
- Product Strategy
- Data Strategy
- Analytics & AI/ML Strategy
- Roadmapping
Technologies
- PySpark
- Solr
- Cockroach
- Docker
- Kubernetes
- Python
- FastAPI
- Spacy
- NLTK
- Gensim
- Pandas
- PyTorch
- Requests
Engineering
- Native mobile on IOS & Android
- Web app development
- Automation framework & manual QA
- REST API backend
- Front end development
- ADA Accessible UI
- IoT development with Raspberry Pi