Relationship Rank Calculation Using Multi-Source Interaction Scores
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Solution Overview
Problem
Current CRM systems lack the ability to effectively quantify and rank the strength of relationships between individuals or organizations, which is crucial for informed customer service actions and strategic decision-making.
Innovation Solution
A computer-based system calculates a relationship rank by aggregating contact interaction scores from CRM, telephone call, and email data using weighted sums, stored in dedicated databases, to determine the strength of relationships between parties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If CRM systems track various contact interactions (meetings, calls, emails), then the quantity of relationship data is improved, but the ability to quantify and rank relationship strength remains insufficient
Solution Approach 1:
The patent transforms unquantified relationship data into measurable relationship scores by changing the parameter state from qualitative interaction records to quantitative scored values. Multiple interaction types (meetings, calls, emails) are converted into standardized score parameters that can be aggregated and ranked, enabling precise measurement of relationship strength.
Solution Approach 2:
The patent introduces an intermediary scoring mechanism that mediates between raw interaction data and relationship strength assessment. The relationship score acts as an intermediary variable that synthesizes multiple interaction types into a single quantifiable metric, bridging the gap between data quantity and measurement precision.
2Measurement precision
If relationship rank is calculated using multiple data sources (CRM, telephone, email), then the measurement precision of relationship strength is improved, but the device complexity increases
Solution Approach 1:
The patent merges multiple data sources (CRM interactions, telephone calls, emails) into a unified relationship scoring system. By combining these separate data streams into a single aggregated relationship score, the system achieves comprehensive measurement precision while managing complexity through integration rather than separate processing systems.
Solution Approach 2:
The patent creates a universal relationship scoring mechanism that handles multiple interaction types through a single framework. The same scoring algorithm processes meetings, calls, and emails uniformly, providing multi-functional capability that reduces system complexity compared to separate analysis systems for each interaction type.
3Reliability
If relationship scores are aggregated from multiple interaction types, then the reliability of relationship assessment is improved, but the loss of information from different interaction contexts increases
Solution Approach 1:
The patent segments the relationship assessment process into distinct interaction type components (meetings, calls, emails) that are processed separately before aggregation. Each interaction type maintains its contextual characteristics through dedicated scoring, then combines into the overall relationship score, preserving information while achieving reliable综合 assessment.
Solution Approach 2:
The patent adds a dimensional layer to relationship assessment by treating different interaction types as separate dimensions. Each interaction type contributes to the relationship score from its own dimensional perspective, preserving contextual information while enabling reliable multi-dimensional relationship evaluation through aggregation.
Data Source
AI summary
A method of determining and an apparatus for displaying, for an organization, a relationship rank between a first party and a second party. A customer relationship management score, a telephone call score, and an e-mail score for the first party relative to the second party may be calculated using a computer system. The customer relationship management score, the telephone call score, and the e-mail score may be calculated using data for the first party and the second party stored in databases. A relationship score for the first party relative to the second party may be calculated using the customer relationship management score, the telephone call score, and the e-mail score. A relationship rank may be calculated for the first party relative to the second party using a computer system. The relationship rank for the first party relative to the second party may be an indication of the strength of the first party's relationship to the second party. The relationship rank may be based on the relationship score.