Customer Purchase History Classification for Automated Ordering
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Solution Overview
Problem
Customers face inefficiencies when repeatedly ordering the same items online, as adding items to their basket can be time-consuming, and there is a need to address regular purchasers with targeted marketing messages.
Innovation Solution
A system that classifies products based on customer purchasing history, using a memory unit to store order information and generate messages based on purchase classifications and time data, allowing for efficient ordering and personalized marketing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If customers manually add items to their basket for each order, then they can customize their orders, but it takes an unneeded amount of time
Solution Approach 1:
The system performs preliminary actions by automatically analyzing customer purchase history and pre-populating frequently purchased items in the shopping basket before the customer completes their order. This eliminates the need for customers to manually add items one by one, significantly reducing the time required for ordering while maintaining the ability to customize orders by adding or removing items as needed.
2Adaptability or versatility
If the system sends marketing messages to all customers, then it can promote products, but it may not address regular purchasers appropriately
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring and analyzing customer purchase behavior patterns, then using this information to dynamically adjust and personalize marketing messages. The classification unit processes purchase history data to identify regular purchasers and tailor appropriate messages, ensuring that marketing communications are adapted to individual customer behaviors rather than using generic approaches for all customers.
Solution Approach 2:
The system applies local quality by providing different types of marketing messages to different customer segments based on their specific purchase patterns. Regular purchasers receive tailored messages that recognize their loyalty and purchasing habits, while other customers receive appropriate promotional content. This ensures that each customer receives marketing information specifically suited to their behavior rather than a one-size-fits-all approach.
Data Source
AI summary
Systems, methods, and computer-readable storage media are provided that allow orders to be made remotely by customers and classify a product or category of products based on a customer's purchasing history of that product and generate a message to the customer based on the classification.