Replenium Inc. (20240346537). AUTOMATED REPLENISHMENT SHOPPING HARMONIZATION simplified abstract
Contents
AUTOMATED REPLENISHMENT SHOPPING HARMONIZATION
Organization Name
Inventor(s)
Thomas W. Furphy of Sammamish WA (US)
William Justin Leigh of Seattle WA (US)
Umair Bashir of Issaquah WA (US)
Terrence Nightingale of Seattle WA (US)
AUTOMATED REPLENISHMENT SHOPPING HARMONIZATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240346537 titled 'AUTOMATED REPLENISHMENT SHOPPING HARMONIZATION
The abstract describes an auto-replenishment platform that aggregates data from retailers, manufacturers, and third-party consumers to predict consumer demand, factors influencing convenience, and group products for shipment or pickup.
- Aggregates retailer, manufacturer, and consumer data
- Mines and clusters aggregated data
- Generates consumer model for predicting demand and convenience factors
- Integrates platform into e-commerce platforms
- Groups consumer products for shipment or pickup
Potential Applications: - Streamlining inventory management - Enhancing customer experience - Improving supply chain efficiency
Problems Solved: - Predicting consumer demand accurately - Optimizing product shipment and pickup processes - Enhancing convenience for consumers
Benefits: - Increased efficiency in inventory management - Improved customer satisfaction - Cost savings for retailers, manufacturers, and third-party platforms
Commercial Applications: Title: "Enhancing Inventory Management and Customer Experience with Auto-Replenishment Platform" This technology can be used in various industries such as retail, manufacturing, and e-commerce platforms to streamline inventory management processes, improve customer satisfaction, and reduce operational costs.
Prior Art: Further research can be conducted in the fields of data aggregation, consumer behavior analysis, and supply chain optimization to explore existing technologies related to auto-replenishment platforms.
Frequently Updated Research: Stay updated on advancements in data analytics, machine learning algorithms, and e-commerce technologies to enhance the capabilities of auto-replenishment platforms.
Questions about Auto-Replenishment Platforms: 1. How does data aggregation contribute to predicting consumer demand accurately? 2. What are the key factors influencing a consumer's perception of convenience in purchasing products?
Original Abstract Submitted
an auto-replenishment platform may receive retailer, manufacturer, and 3party consumer data on a regular time interval, via their e-commerce platforms. the auto-replenishment platform, via a harmonization engine, may aggregate all data sets, mine the aggregated data, and then cluster the data. subsequently, the auto-replenishment platform may generate a consumer model for predicting the consumer demand for a product, factors that influence a consumer's perception of convenience or ease in purchasing that product, and for aggregating a consumer's purchased products for shipment or pickup. the auto-replenishment platform may send the consumer model to the retailer, manufacturer, and 3party e-commerce platforms to integrate the auto-replenishment platform into those platforms. additionally, the auto-replenishment platform may group a consumer's products for shipment which provides additional efficiencies for the customer and retailer/manufacturer/3party in the form of time savings and/or reduced shipping and handling cost and related logistical advantages.
