Marketing Optimization Engine Using Quantum Segmentation
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Solution Overview
Problem
Conventional marketing approaches fail to personalize communications effectively, leading to irrelevant messages and increased customer solicitation, as they do not account for individual customer profiles, locations, interests, or habits, resulting in decreased engagement and increased ignore rates.
Innovation Solution
A system utilizing cloud, hybrid, and quantum-based computing techniques to iteratively select subgroups of prospective clients, perform marketing actions, receive feedback, score it using machine learning, and modify actions to optimize marketing strategies based on personal and environmental data, ensuring relevant content delivery through multiple communication channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional automated marketing messages are sent in a predefined and sequential way to all customers, then the messaging process is simple and automated, but the messages are not customized to target individual customers based on their specific user profile, location, weather, interests, habits, etc., leading to irrelevant content and decreased engagement
Solution Approach 1:
The patent segments the customer base into subgroups based on multiple criteria including user profile, location, weather conditions, interests, and habits. This segmentation enables personalized marketing messages to be sent to specific subgroups rather than treating all customers uniformly, thereby improving adaptability while managing complexity through systematic categorization
Solution Approach 2:
The patent applies local quality by customizing marketing messages according to local characteristics of different customer subgroups. Each subgroup receives messages tailored to their specific location, weather conditions, interests, and habits, ensuring that the content is relevant and engaging for each local segment rather than using a one-size-fits-all approach
2Productivity
If constant messaging pressure is exerted on customers to increase buying likelihood, then the frequency of communication increases, but irrelevant marketing messages create unnecessary solicitation and lead customers to ignore the communications
Solution Approach 1:
The patent implements feedback mechanisms to monitor customer responses to marketing messages. By analyzing customer behavior and engagement data, the system learns from previous communications and adjusts future messaging strategies accordingly. This feedback loop ensures that marketing pressure is applied effectively while avoiding customer irritation by adapting to their responses
Solution Approach 2:
The patent employs dynamic messaging strategies that adapt to customer responses and changing conditions. Rather than sending static predefined messages, the system dynamically adjusts message content, timing, and frequency based on real-time data about customer interests, location, weather, and engagement patterns, thereby maintaining marketing effectiveness without creating unnecessary solicitation
Data Source
AI summary
Provided are methods and systems for optimization and personalization of marketing actions using cloud, hybrid, and quantum-based computing techniques. An example method commences with iteratively selecting, from a pool of prospective clients, at least one subgroup of the prospective clients based on predetermined criteria. The method further includes performing at least one marketing action on the at least one subgroup of the prospective clients. The method then continues with receiving a feedback from a prospective client belonging to the at least one subgroup of the prospective clients in response to the at least one marketing action. The method further includes scoring, by a machine learning technique, the feedback received from the prospective client. The method further includes modifying the at least one marketing action until the at least one marketing action is optimized for the prospective client based on the scoring of the feedback.