Automation of Costco Receipt Analysis Using Azure AI Platform

Challenge

As a major retail chain, Costco regularly runs marketing campaigns and requires efficient analysis of purchase data to evaluate their effectiveness. Automating receipt analysis will enable the company to:

• Optimize data processing workflows.
• Enhance analytical capabilities to create personalized offers and promotions.
• Develop loyalty programs by providing customers with discounts and rewards based on their purchase history.
• Simplify handling large data volumes, which is particularly critical for a network serving millions of customers.
• This automation will streamline operations, improve customer engagement, and support data-driven decision-making.

Solution

The solution consists of several stages:

1. Data Upload and Storage

Receipts are uploaded to Azure Blob Storage, where they undergo hash verification to ensure data integrity.

Receipts can be uploaded in formats such as PDF, HEIC, JPEG, and PNG.

2. Receipt Classification

A custom Azure Document Intelligence model identifies the type of receipt (e.g., whether it was obtained in-store or online, and in which language).

3. Data Extraction

Azure Document Intelligence extracts key data fields, such as membership number, item list, prices, and total amounts.

4. Data Transformation

The extracted data is saved in structured formats like JSON or CSV.

5. Data Storage and Retrieval

The processed data is stored in Azure Blob Storage along with metadata, such as confidence scores and receipt type.

The system returns information about the processed receipts, including a summary of the extracted data and the file paths to the saved files.

This end-to-end solution ensures efficient, accurate, and scalable processing of receipt data for Costco.

Results

The system is capable of processing receipts in various formats with high accuracy—over 95%. This significantly reduces the time and effort previously spent on manual data entry and processing.

With the new system, the extracted data is stored in analysis-friendly formats (JSON, CSV), making it easier to use for further insights and decision-making. The solution is designed to handle large volumes of data and can be scaled to accommodate other types of receipts in the future.

The customer now has the ability to analyze purchase data more effectively, enabling the creation of personalized offers and enhancing loyalty programs for their clients. This improvement not only boosts customer satisfaction but also drives business growth through data-driven strategies.