Fast-Tracking Shopping Experience

Our Experience developing a Fast-tracking shopping experience

Customer Profile:

Our client is one of the leading retail company. Their business concept is to offer fashion and quality at the best price in a sustainable way. They focus on creating better experiences together, for their customers, their communities, and for each other. The client needed a solution that would reduce the complexity of purchase process and provide a better shopping experience to customers

Problem Statement:

In a traditional store, customers typically wait in line to purchase items. Long waiting times is a common complaint, and could be affected by the number of staff on duty or the number of customers present at the time. In fact, our research found that 53% of Japan shoppers leave the store without purchasing due to checkout lines being too long.

Innovature focused on the pain-points in store and endeavoured to mitigate a frictionless shopping experience. This in turn, helps the shopper navigate from intent to completed checkout with ease.

Project Background:

The client wanted an easier shopping experience where you can get potential benefits of frictionless technology. They are in need of a contactless payment to fully automated checkout which help to streamline and improving the customer experience. They also have added appeal of more hygienic shopping as well.

Challenges:

  • Inventory optimization

Technology:

Development language: Java

Database Server: MySQL

File Storage: AWS S3 Hibernate

Content Delivery: AWS CloudFront

Solution:

Innovature built a solution helped in offering a smart shopping experience to customers, greatly reducing the shopping cycle time. Additionally, the solution also reduced the manpower required in the store, thereby bringing about a considerable increase in business returns.

Here shopping sessions start with customers initiate a transaction at an entry gate using a personal QR code from an app. Upon entering the store, strategically placed cameras capture the scene. Deep learning models running on local servers is used to detect humans in these video feeds. When a shopping session is started, customers are assigned a random ID. A central server uses this to track each shopper throughout the store as they pass through from camera to camera. Using deep learning models trained on product and positioning data from our Product Mapper software, the system determines when customers interact with products & whether to add or subtract that item from their cart. Upon leaving the store (Frictionless area) customers are charged via their digital wallet, receiving a receipt via email or text, allowing use of conventional payment methods such as cash, credit, etc.

Achievements:

  • Convenience
  • More control
  • No crowds
  • No pressure

Return on Investment:

The Fast-tracking shopping experience helped to increase operational efficiency by 50%.

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