RFM Cohort Mapping Database for Custom Profile Filtering

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Solution Overview

Problem

There is no standardized method for computing customizable RFM cohorts and performing automated electronic message automations based on user-defined query logic for filtering entity data.

Innovation Solution

A computer-implemented method and system for computing and storing RFM cohorts as profile properties, allowing users to define and adjust transformation models, preview cohort assignments, and send targeted electronic messages based on cohort transitions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If RFM analysis is used to group customers into cohorts, then customer segmentation and communication strategy improvement is achieved, but there is no standardized method and automated tool for computing customizable cohorts and performing automations

Engineering Contradiction:

Improvecustomizability of RFM cohortsVSAvoidcomplexity of cohort computation system

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system segments the customer base into distinct RFM cohorts (e.g., Champions, Loyalists, Recent, Needs Attention, At Risk, Inactive) based on recency, frequency, and monetary value metrics. This segmentation enables customized communication strategies for each cohort while maintaining a standardized computation framework through the transformation model and mapping database.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces a transformation model as an intermediary component that converts raw RFM data into standardized vector representations. This mediator layer simplifies the complexity by providing a uniform transformation process that can be applied to different datasets, while the mapping database serves as another intermediary that translates vectors into cohort assignments without requiring complex custom logic.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Extent of automation

If automated tools are implemented for computing RFM cohorts and performing electronic message automations, then productivity and automation extent are improved, but security risks such as SQL injection attacks may increase

Engineering Contradiction:

Improveautomation of electronic message sendingVSAvoidSQL injection attack risk

Core Design Contradiction:

Extent of automationVSObject-affected harmful factors

Solution Approach 1:

The patent replaces traditional SQL query-based filtering mechanisms with a vector transformation and mapping approach. Instead of using SQL queries that are vulnerable to injection attacks, the system transforms RFM data into vectors and uses a pre-defined mapping database to determine cohort assignments, thereby eliminating the mechanical SQL query step that creates security vulnerabilities.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The mapping database is pre-populated with transformation models and cohort definitions before the system is deployed. This preliminary action ensures that all data processing operations use safe, pre-validated logic, preventing SQL injection attacks while maintaining automated cohort computation and electronic message sending capabilities.

Inventive Principle:

Principle #10Preliminary action

3Adaptability or versatility

If user-defined query logic is stored in a database for filtering entity data, then adaptability and customization are improved, but the complexity of data processing and query management increases

Engineering Contradiction:

Improveuser-defined query logic customizationVSAvoidcomplexity of query logic storage and processing

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

Instead of storing complex user-defined query logic directly in the database, the system creates simplified vector representations of the query criteria and stores these as mapping keys. The actual complex filtering logic is copied into the transformation model and mapping database structures, which then handle the query execution efficiently without requiring storage of the original complex query definitions.

Inventive Principle:

Principle #26Copying

Data Source

PatentUS20260056921A1Transformation Logic and Mapping Database for Computing Profile Properties and Filtering Entity Data

Publication Date: 2026.02.26 KLAVIYO INC

AI summary

A system for computing and storing a profile property to an entity profile database for multiple entities comprises a recency frequency monetary value (RFM) server platform. The RFM server platform comprises a raw score module for computing a raw score for each of recency, frequency, and monetary value for each of the entities based on the profile data; a transformation engine transforms the computed recency, frequency and monetary raw scores to a multi-dimensional vector for each entity; a mapping database maps the vector to an RFM cohort; and a main module receives the entity data from the entity profile database, communicates with the transformation engine and mapping database, and stores the RFM cohort as a property for each of the entities to the entity profile database. Filtered entity groups and automating content and delivery of electronic messaging can be performed based on the assigned cohorts. Related methods are also described.