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Self Adjusting Layout for Optimal Conversion

IP.com Disclosure Number: IPCOM000237325D
Publication Date: 2014-Jun-13
Document File: 5 page(s) / 131K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed are a method and system to automate and test content positioning on a page. The engine automatically attempts various combinations of content by repositioning, hiding, and shifting content, and analyzing statistics to understand the optimal combination.

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Self Adjusting Layout for Optimal Conversion

Within online e-commerce, page layout arrangement can lead to high and low conversion. E-commerce customers purchase e-commerce engines to run a website and purchase analytic engines to gain business insight. Business users are taxed with manually rearranging page content to spur increased conversion. Business users are also taxed with manually running A/B tests and analyzing copious data to determine the success of the page arrangements. The situation is further complicated because different layouts might optimize conversion at different times of the year; for example the optimal page layout for a seasonal holiday sale might not be the optimal for the different months . The process for selecting the optimal layout for conversion is manual and leads to a conversion rate that may or may not be optimal due to the high levels of effort needed to execute the layout .

Current known solutions lack integration and automation. E-commerce engines and analytics engines both exist with loosely coupled integration. No closed loop solution exists in which an analytics engine can automatically drive full-page e-commerce content. A/B multi-variant software exists as well; however, it typically involves manual intervention.

The novel contribution is a method and system to automate and test content positioning on a page . The engine automatically attempts various combinations of content by repositioning, hiding, and shifting content, and analyzing statistics to understand the optimal combination. A number of tests can be run with several results, where insignificant resulting combinations can be immediately disqualified.

The automated optimization of the page layout is based on customer behavior . The system automatically sets up page A/B tests and analyzes the results of the test to determine maximum conversion rates. The system continually optimizes page layouts and depths based on different characteristics including:

Customer behaviors and personas
External search findability (i.e. more people finding this page through search engines means the page has a higher rate of

findability)

Conversion ratio including number of views to clicks to conversion
Removal of poor page arrangements and poor performing pages

Figure 1: Closed loop arrangement and experimental engine

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From a series of view, click-to-view, and click-to-order actions, an analytics engine can identify the popular content on a page; however, without positioning content in different ways, the engine can never know the most popular arrangement. The analytics engine needs to control and test variations of a page.

Figure 2: Base layout

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Fig...