CROSS-REFERENCE TO RELATED APPLICATIONS

This application is related to the following co-pending and commonly-assigned patent application, which application is incorporated by reference herein:

U.S. patent application Ser. No. 15/894,335, filed on Feb. 12, 2018, entitled “HEADLESS CONTENT MANAGEMENT SYSTEM (CMS),” with inventors Adam K. Weber, Nicholas J. Wesselman, Olexandr Shyba, and Michael Seifert, which application claims the benefit of provisional application 62/457,295 filed on Feb. 10, 2017.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates generally to content management systems (CMS), and in particular, to a method, system, apparatus, and article of manufacture for customization/personalization of content based on machine learning (ML).

2. Description of the Related Art

A content management system (CMS) is an application that is often used for the creation and modification of digital content. Web CMS (WCM or WCMS) is a CMS designed to support the management of web pages. Prior art systems have attempted to personalize web content. However, such prior art systems base such personalization on content tests and merely select a single result from such tests to present to the user. Further, such prior art systems fail to engage the user in determining how such content should be personalized while also failing to discover different variants for different audiences. Accordingly, what is needed is a method and system for personalizing content based on customer data, to discover audience segments, and suggest personalized content for such segments, while utilizing machine learning techniques.

To better understand the problems of the prior art, a description of prior art personalization processing may be useful.

FIG. 1illustrates the logical flow for personalization in prior art systems. At step102, a content test is started. In this regard, a user may create a content test on a page and selects the test objective (e.g., a goal or engagement value). Further, the test may have N different variants, that are competing against each other.

At step104, the test is executed/in-progress. Any visitor to the page sees only one of the possible variants that are available. Statistics of the visits are accumulated and logged to a database in order to find the winner.

At step106, the test is finished and the winning variant is determined. In this regard, the test may only be finished when there are a significant number of visits (e.g., a threshold number of visits has been completed). The winning variant is presented/picked to/by the user.

At step108, the “winner” variant becomes the only variant that is presented on the web page delivered to the end-user/consumer.

In view of the above, in the prior art, a simple content test is used to suggest one single winner for all visitors. However, specific sub-segments within the entire audience may prefer different content (e.g., a sub-segment in a different geographic location may prefer certain content [e.g., different geographic areas may have preferences for certain products, trends, food, etc. and desire different content related to such preferences]). Accordingly, prior art personalization is limited in its ability to both discover personalization rules as well as presenting multiple variations of personalized content to consumers.

SUMMARY OF THE INVENTION

Embodiments of the invention overcome the problems of the prior art and discover user segments to personalize (e.g., discover personalization rules). In this regard, machine learning methodologies are employed, based on accumulated statistics of visits (e.g., customer's data), to discover audience segments and suggest/provide/generate personalized content for these segments. Through such personalization, embodiments of the invention attempt to maximize business goals such as visitor engagement, goal conversions, e-commerce purchases, and other types of conversions.

Competitive advantages of embodiments of the invention include maintainability and manageability, integration with existing systems, and the ability to leverage databases.

With respect to maintainability and manageability, while automated personalization products exist, such products focus on completely automated processes, which is a black box for a customer. Such an approach is a limitation to the completely automated system. In contrast, embodiments of the invention are provided with the ability to preview suggested personalization rules and if needed, personalization variants can be edited or dismissed. Accordingly, embodiments of the invention provide customers/users with more control over presentation, while at the same time supporting the decision making with machine learning.

With respect to integration with existing systems, prior art systems require the addition of custom code on a web page and calls to third party services in order to provide personalization. Such requirements result in increased latency and integration issues. In contrast, embodiments of the invention provide an integrated product suite in which personalization rules and customization are provided in a native format to the databases and services provided.

With respect to leveraging databases, embodiments of the invention may leverage an experience/customer database such as the XDB database available from the assignee of the present invention. Such a database provides behavioral profiles and engagement values thereby enabling unique customization/personalization compared to that of prior art systems. Further, the integration with such a database provides for end-to-end business optimization scenarios.

In addition to providing the personalization of content for websites, embodiments of the invention may be utilized in other channels, such as the personalization on the internet of things (IOT) channel (e.g., ATMs, smart refrigerators, etc.), mobile applications, and third-party based websites.

