Cause-and-Effect Experimentation for Retail Content Optimization

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Solution Overview

Problem

Current methods for evaluating the effectiveness of communication content in retail environments, such as point-of-purchase advertising, fail to reliably demonstrate causation between marketing messages and business results, leading to challenges in measuring performance and optimizing content distribution effectively.

Innovation Solution

A system and method that conduct cause-and-effect experiments using experimental content and machine learning routines to assess and optimize communication content effectiveness across geographically disparate digital signage networks, ensuring non-confounded results and maximizing business objectives.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If correlational or matched control studies are used to evaluate advertising content performance, then marketing research can be conducted with existing methodologies, but causation between marketing message and business result cannot be reliably revealed

Engineering Contradiction:

Improvecausation detection reliabilityVSAvoidresearch methodology complexity

Core Design Contradiction:

ReliabilityVSEase of manufacture

Solution Approach 1:

The system segments the retail environment into multiple test locations and divides the advertising content into different variants. Each location serves as an independent experimental unit where specific content variants are tested, allowing for controlled comparison and causal inference while maintaining practical implementation through standardized test protocols

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system performs preliminary random assignment of content variants to different locations before the experiment begins. This pre-randomization ensures that any observed effects can be attributed to the content rather than pre-existing conditions, establishing causation while using straightforward randomization procedures rather than complex experimental designs

Inventive Principle:

Principle #10Preliminary action

2Adaptability or versatility

If multiple cause-and-effect experiments are conducted concurrently on geographically disparate displays, then content effectiveness can be measured across different contexts, but experimental schedules must be carefully coordinated to avoid confounding

Engineering Contradiction:

Improvemulti-location experiment capabilityVSAvoidschedule coordination complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system segments the experiment into independent time slots and location-specific test units. Each location can run its own experiment independently with its own time slots, allowing concurrent multi-location testing while avoiding confounding through spatial and temporal separation of experimental conditions

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system dynamically assigns time slots to different content variants at different locations based on real-time conditions and experimental requirements. This dynamic scheduling allows flexible coordination of multiple concurrent experiments without fixed rigid schedules, reducing complexity while maintaining experimental integrity across geographically dispersed displays

Inventive Principle:

Principle #15Dynamics

3Measurement precision

If experimental content is displayed to determine effectiveness, then causation can be established, but business objectives may be compromised during experiment periods

Engineering Contradiction:

Improvecontent effectiveness measurementVSAvoidbusiness objective achievement

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The system segments display time into dedicated experiment slots and business optimization slots. During experiment slots, content variants are tested to establish causation, while during business slots, the system displays content optimized for business objectives. This temporal segmentation allows both measurement precision and productivity to be achieved without compromising either function

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system applies experimental content only to the extent necessary for valid measurement (partial action) rather than continuously. By limiting experimental content to specific time slots and locations, the system maintains measurement precision for causation establishment while allowing business-optimized content to be displayed during other periods, thus preserving overall productivity and business objective achievement

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS9519916B2System and method for concurrently conducting cause-and-effect experiments on content effectiveness and adjusting content distribution to optimize business objectives

Publication Date: 2016.12.13 3M INNOVATIVE PROPERTIES CO

AI summary

The present invention is directed to systems, articles, and computer-implemented methods for assessing effectiveness of communication content and optimizing content distribution to enhance business objectives. Embodiments of the present invention are directed to computer-implemented methods for a computer-implemented method, comprising conducting an experiment using experimental content to determine effectiveness of communication content and executing, while conducting the experiment, a machine learning routine (MLR) using MLR content to enhance an effectiveness metric.