Personalized Digital Promotion Server Using Shopper Preference Data
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Solution Overview
Problem
Existing digital promotion systems lack the ability to personalize promotions based on individual shopper preferences and historical purchase data, leading to inefficient marketing and reduced consumer engagement.
Innovation Solution
A digital promotion processing system that includes a promotion processing server capable of determining available digital promotions for a given product, prompting shoppers to select promotions, storing and updating shopper preference data, and generating personalized digital promotions based on this data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional digital promotion systems are used, then promotion distribution is simple and fast, but personalization capability is poor and marketing efficiency is reduced
Solution Approach 1:
The system segments promotion distribution by creating distinct modules: a preference data collection module that gathers shopper preferences, a promotion generation module that creates personalized promotions, and a distribution module that delivers promotions. This segmentation enables personalization while maintaining manageable system complexity through modular architecture.
Solution Approach 2:
The system performs preliminary actions by collecting and storing shopper preference data before promotion distribution. The promotion generation module pre-processes this data to create personalized promotion templates, which are then quickly distributed when needed. This preliminary preparation enables fast personalized distribution without real-time processing complexity.
2Productivity
If personalized promotions are generated using shopper preference data, then marketing efficiency improves, but data processing requirements increase
Solution Approach 1:
The system collects and stores shopper preference data in advance during shopping trips, before promotion generation is needed. This preliminary data collection and preprocessing reduces the processing load during actual promotion distribution, enabling efficient personalized promotion delivery without real-time data processing bottlenecks.
Solution Approach 2:
The system creates simplified copies of shopper preferences in structured formats that can be quickly matched with available promotions. Instead of processing raw shopping data each time, the system uses pre-formed preference profiles that can be efficiently queried and matched, reducing data processing requirements while maintaining personalization quality.
3Ease of operation
If multiple redemption terms are offered for different shoppers, then consumer engagement increases, but promotion management complexity increases
Solution Approach 1:
The system segments promotion management by separating the complex personalization logic from the simple distribution function. The promotion generation module handles the complexity of creating multiple redemption terms based on shopper preferences, while the distribution module simply delivers the generated promotions. This segmentation increases consumer engagement through personalized terms while managing complexity through modular design.
Solution Approach 2:
The system enables self-service by allowing shoppers to implicitly define their own promotion preferences through their shopping behavior and explicit feedback. The automated promotion generation module then uses these self-defined preferences to create appropriate redemption terms, reducing the need for manual promotion management while increasing consumer engagement through personalized offerings.
Data Source
AI summary
A digital promotion processing system may include a shopper device associated with a given shopper, and a promotion processing server. The promotion processing server may be configured to determine available digital promotions for a given product for purchase, each available digital promotion having different redemption terms. The promotion processing server may also be configured to cooperate with the shopper device to prompt the shopper to select one of the available digital promotions to apply toward purchase of the given product, store shopper promotion terms preference data based upon the selected digital promotion, and update the shopper promotion terms preference data based upon a plurality of new selections of available digital promotions. The promotion processing server may further be configured to generate and communicate a personalized digital promotion to the shopper device. The personalized digital promotion may have redemption terms based upon the updated shopper promotion terms preference data.