Customer Journey Functional Mapping for Real-Time Contextual Nurturing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems fail to efficiently organize and analyze vast volumes of customer interaction data across multiple channels and timeframes, lacking a holistic approach to understand customer behavior, preferences, and intents, and struggle to provide real-time guidance for marketing efforts.
Innovation Solution
A system that collects, organizes, and curates customer engagements using a self-organizing, orientation-aware functional map data structure, employing semi-supervised learning and geometric transformations to identify micro-journeys and align them with business objectives, enabling real-time nudges and strategic guidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional data storage and analysis methods are used for customer interaction data, then data can be stored, but the system cannot efficiently organize and analyze vast volumes of data across multiple channels and timeframes to provide holistic customer understanding
Solution Approach 1:
The patent segments customer interaction data into discrete events with specific types, channels, and timestamps. Each interaction is broken down into structured components that can be independently processed and analyzed, enabling efficient organization of vast data volumes while maintaining complete customer journey information through the functional map data structure.
Solution Approach 2:
The patent introduces a functional map data structure that maps customer journeys across multiple dimensions including time, channel, interaction type, and business objective. This multi-dimensional organization allows the system to efficiently query and analyze data from any perspective while maintaining holistic customer understanding across all dimensions simultaneously.
2Measurement precision
If manual market research and user surveys are conducted to understand customer motivations, then comprehensive views can be obtained for certain user types, but the approach cannot scale to all users and provides only partial perspectives
Solution Approach 1:
The system enables self-service analysis by automatically processing and analyzing customer interaction data without requiring manual market research or surveys. The functional map data structure and event processing system autonomously extract customer motivations, preferences, and intents from observed interactions, scaling precisely to all users while maintaining comprehensive understanding.
Solution Approach 2:
The system continuously processes customer interaction feedback in real-time, updating the functional map data structure with new insights about customer motivations and behaviors. This continuous feedback loop enables the system to maintain precise understanding of customer preferences across the entire user base, not just sampled groups.
3Loss of time
If real-time data processing is implemented to provide timely marketing guidance, then marketing timing can be optimized, but the system complexity increases significantly
Solution Approach 1:
The patent implements preliminary action by pre-processing and structuring customer interaction data into the functional map data structure as interactions occur. Event types, channels, and timestamps are organized in advance, enabling rapid real-time analysis and marketing decision-making without complex processing during critical response moments.
Solution Approach 2:
The functional map data structure serves multiple functions simultaneously: it stores raw interaction data, organizes data by multiple dimensions, enables real-time querying, supports historical analysis, and provides the foundation for predictive modeling. This multi-functionality reduces overall system complexity by consolidating what would otherwise require separate systems.
4Reliability
If customer journey mapping is performed to understand end-to-end customer experiences, then customer satisfaction can be improved, but the system cannot handle the voluminous interaction data at scale
Solution Approach 1:
The patent extracts only the essential elements needed for customer journey mapping from the voluminous interaction data. The functional map data structure selectively captures event types, channels, timestamps, and business objectives that define customer journeys, filtering out redundant information while maintaining complete journey context for satisfaction analysis.
Solution Approach 2:
The system dynamically adapts the functional map data structure to handle varying data volumes and journey complexities. As customer interactions accumulate, the system automatically adjusts its processing and organization methods, maintaining efficient journey mapping capabilities regardless of data scale through dynamic resource allocation and processing optimization.
Data Source
AI summary
A system and method for collecting, organizing, and curating customer engagements across multiple interactions and touch points. The disclosed method allows for a discovery of purposes, an accretion of micro-journeys for a plurality of customers and a contextual nurturing of those customers on respective journeys towards their next milestones using numerical, graphical, statistical, and heuristics-based methods and proposed memory layouts of the same. Real-time staging and processing of inbound factual data and inferential dimensions into a multipartite multidimensional space of the factual and inferential dimensions to enable the mapping of customer interactions with a brand and the digital encoding thereof.