Cross-Site Product Promotion via Behavioral Data Analysis
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Solution Overview
Problem
Existing electronic commerce websites struggle to effectively cross-promote products and services across multiple network sites, leading to suboptimal sales and customer engagement, as they lack the ability to identify and leverage relationships between products and sites based on user behavior.
Innovation Solution
A data communications network that utilizes a network site relationship engine to analyze customer data from multiple sites, identifying site relationships through purchase and browse history, and generates network pages that include references to complementary or related sites, enhancing product visibility and sales opportunities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single network site is used to sell products, then the website design can be optimized for specific products, but the ability to cross-promote products and services across multiple sites is limited
Solution Approach 1:
The patent combines multiple network sites into a unified system where product data, customer behavior data, and promotional content are shared across sites. The network page generation system merges information from multiple sources to create coordinated promotional content that appears across different network sites, enabling cross-promotion while maintaining individual site identities.
Solution Approach 2:
The network page generation system performs multiple functions: it analyzes customer behavior data, identifies complementary products, generates promotional network pages, and distributes them across multiple network sites. This multi-functional system enables a single platform to handle various aspects of cross-promotion, reducing the need for separate systems at each site.
2Productivity
If network pages include references to multiple network sites, then product visibility and sales opportunities increase, but the complexity of analyzing and managing relationships between sites increases
Solution Approach 1:
The system automatically analyzes customer behavior data from multiple network sites, identifies complementary products and services, and generates appropriate network pages with references to relevant sites. This self-service approach eliminates the need for manual analysis and management of inter-site relationships, reducing operational complexity while improving sales conversion through targeted cross-promotions.
3Measurement precision
If customer data from multiple sites is analyzed to identify relationships, then targeted product recommendations improve conversion rates, but the amount of data to be processed and stored increases
Solution Approach 1:
The system extracts only the relevant features and patterns from customer behavior data that are necessary for identifying complementary products and generating effective cross-promotions. Rather than processing and storing all raw data, the system extracts key behavioral indicators and relationships, reducing data volume while maintaining the precision needed for accurate product recommendations.
Data Source
AI summary
Disclosed are various embodiments for collaborative electronic commerce. For example, a first network site is implemented in at least one server that sells a first plurality of items via a network. A relationship is identified in the at least one server between a second network site and an aspect of the first network site, where the second network site is configured to sell a second plurality of items via the network. A reference to the second network site is presented to the user in association with a transaction that involves the aspect of the first network site.