“Never Miss a Customer” for a Multinational Fashion Company

Technology Stack

• VueJS
• NuxtJS
• Kotlin
• JVM
• SpringBoot
• Postgresql
• Python
• Docker
• Kubernetes

Problem

In the fast-paced retail environment, accurately matching products to consumer preferences is a significant challenge. Retailers need intelligent systems to offer personalized shopping experiences and ensure that customers find products they love.

Solution

Software Angels developed the "Never Miss a Customer" app, a powerful AI-based solution designed to enhance shopping experiences through advanced product similarity detection. This app integrates multiple data inputs to deliver precise product recommendations, ensuring customers never miss a product that suits their preferences.

Process

Data Integration:

• The app allows retailers to choose the AI similarity model via a sophisticated API.
• It processes four types of data to form a comprehensive feature vector:
  • Intrinsic Product Details: Material, color, type.
  • Computer Vision Embeddings: Visual patterns and features from product images.
  • Unique Product IDs
  • Manufacturer's Suggested Retail Price (MSRP)

Machine Learning Techniques:

• The app uses machine learning to optimize feature vectors by assigning weights to different data types.
• Principal Component Analysis (PCA) is employed to manage high-dimensional data, retaining essential characteristics while simplifying data processing.

Personalized Recommendations:

• The K-Nearest Neighbors (KNN) strategy identifies products with similar attributes, visual appearance, and price range.
• This approach ensures personalized and precise product recommendations.

"Never Miss a Customer" transforms shopping by understanding individual styles, preferences, and budgets, making every shopping experience tailored and enjoyable.

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