Product Code Database
Personalization (broadly known as customization) consists of tailoring a service or product to accommodate specific individuals. It is sometimes tied to groups or segments of individuals. Personalization involves collecting data on individuals, including web browsing history, HTTP cookie, and location. Various organizations use personalization (along with the opposite mechanism of Popularity) to improve customer satisfaction, Online shopping conversion, marketing results, branding, and improved website metrics as well as for advertising. Personalization acts as a key element in social media and recommender systems. Personalization influences every sector of society — be it work, leisure, or citizenship.
In the recent times, there has been a significant increase in the number of mass media outlets that use advertising as a primary revenue stream. These companies gain knowledge about the specific demographic and Psychographics characteristics of readers and viewers. After that, this information is used to personalize an audience’s experience and therefore draw customers in through the use of entertainment and information that interests them.
Data available from a user's social graph may be accessed by third-party application software so that it fits the personalized web page or information appliance.
Current open data standards on the Internet are:
Technically, web personalization can be accomplished by associating a visitor segment with a predefined action. Customizing the user experience based on behavioral, contextual, and technical data is proven to have a positive impact on conversion rate optimization efforts. Associated actions can be anything from changing the content of a webpage, presenting a modal display, presenting interstitials, triggering a personalized email, or even automating a phone call to the user.
According to a study conducted in 2014 at the research firm Econsultancy, less than 30% of e-commerce websites have invested in the field of web personalization. However, many companies now offer services for web personalization as well as web and email recommendation systems that are based on personalization or anonymously collected user behaviors.
There are many categories of web personalization which includes:
There are several camps in defining and executing web personalization. A few broad methods for web personalization include:
With implicit personalization, personalization is performed based on data learned from indirect observations of the user. This data can be, for example, items purchased on other sites or pages viewed. With explicit personalization, the web page (or information system) is changed by the user using the features provided by the system. Hybrid personalization combines the above two approaches to leverage both explicit user actions on the system and implicit data.
Web personalization can be linked to the notion of adaptive hypermedia (AH). The main difference is that the former would usually work on what is considered "open corpus hypermedia", while the latter would traditionally work on "closed corpus hypermedia." However, recent research directions in the AH domain take both closed and open corpus into account, making the two fields very inter-related.
Personalization is also being considered for use in less open commercial applications to improve the user experience in the online world. Internet activist Eli Pariser has documented personalized search, where Google and Yahoo! News give different results to different people (even when logged out). He also points out social media site Facebook changes user's friend feeds based on what it thinks they want to see. This creates a clear filter bubble.
Websites use a visitor's location data to adjust content, design, and the entire functionality. (2015). 9781450338486, Association for Computing Machinery. ISBN 9781450338486 On an intranet or B2E Enterprise Web portals, personalization is often based on user attributes such as department, functional area, or the specified role. The term "customization" in this context refers to the ability of users to modify the page layout or specify what content should be displayed.
The term "personalization" should not be confused with variable data, which is a much more detailed method of marketing that leverages both images and text with the medium, not just fields within a database. Personalized children's books are created by companies who are using and leveraging all the strengths of variable data printing (VDP). This allows for full image and text variability within a printed book. With the rise of online 3D printing services including Shapeways and Ponoko, personalization is becoming present in the world of product design.
/ref>Kundisch, D., et al. (2017). An introduction to personalization and mass customization. Journal of Intelligent Information Systems
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Research distinguishes enabling layers that support mass personalization across digital and physical domains. On the digital side, platforms aggregate and process user, product, and context data to deliver real-time decisions and content. This commonly uses cloud service models such as platform-as-a-service (PaaS)—a managed environment for developing and deploying applications—together with “personalization-as-a-service” architectures that expose personalization functions through APIs.Mell, P. & Grance, T. (2011). The NIST Definition of Cloud Computing
Within manufacturing, mass personalization is linked to Industry 4.0 concepts, including digital twins, additive manufacturing, industrial IoT, and advanced planning/scheduling. Digital-twin frameworks are studied as a means to synchronize product, process, and usage data in support of individualized designs and operations.Aheleroff, S., Zhong, R.Y., & Xu, X. (2020). A Digital Twin Reference for Mass Personalization in Industry 4.0. Procedia CIRP
Service-based production models have been proposed to make personalization economically viable at scale. In mass personalization as a service (MPaaS), personalization capabilities are delivered via modular, service-oriented architectures across the value chain.Aheleroff, S., Mostashiri, N., Xu, X., & Zhong, R.Y. (2021). Mass Personalisation as a Service in Industry 4.0: A Resilient Response Case Study. Advanced Engineering Informatics
Related business-model research links mass personalization to servitization and product-service systems (PSS), including product-as-a-service offerings that provide access to a product’s function rather than ownership; these models are studied for their implications on circularity, lifecycle management, and revenue mechanisms.Tukker, A. (2015). Product services for a resource-efficient and circular economy—A review. Journal of Cleaner Production
/ref>Chen, Y., et al. (2009). Personalization as a Service: The Architecture and a Case Study. In: IEEE International Conference on e-Business Engineering
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/ref>Zhang, X., Ming, X., & Bao, Y. (2025). Mass personalization product service system (MP-PSS) driven by industrial intelligence: transformation, implementation, and application. The International Journal of Advanced Manufacturing Technology
/ref> Operational studies address order promising, task splitting, and scheduling for flexible systems that must simultaneously meet individualized requirements and capacity constraints.Wang, Y., et al. (2021). Mass personalization-oriented integrated optimization of production task splitting and scheduling. Computers & Industrial Engineering
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/ref> In parallel, manufacturing-as-a-service (MaaS) and production-as-a-service conceptualize manufacturing resources (machines, skills, and processes) as cloud-like services discoverable and orchestrated through digital platforms, enabling on-demand, highly individualized production (including “batch size one”).Li, B.H., et al. (2018). Cloud manufacturing: a service-oriented manufacturing paradigm—A review. Engineering Management in Production and Services
/ref>Romero, D., et al. (2023). World Manufacturing Report 2023: New Business Models for the Manufacturing of the Future. World Manufacturing Foundation.Tedaldi, G., & Miragliotta, G. (2023). Early adopters of Manufacturing-as-a-Service (MaaS): state-of-the-art and deployment models. Journal of Manufacturing Technology Management
/ref>ASME (2016). Production as a Service: Optimizing Utilization in Manufacturing (DSCC2016-9908). ASME DSCC
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/ref>Koers, L., et al. (2024). Product-as-a-Service from B2C retailers’ perspective: a framework of challenges and mitigations. International Journal of Retail & Distribution Management
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Predictive personalization
Predictive personalization is defined as the ability to predict customer behavior, needs or wants—and tailor offers and communications very precisely. Social data is one source of providing this predictive analysis, particularly social data that is structured. Predictive personalization is a much more recent means of personalization and can be used to augment current personalization offerings. Predictive personalization has grown to play an especially important role in , where users, especially recurring clients, have come to expect "smart shopping lists" - mechanisms that predict what products they need based on customers similar to them and their past shopping behaviors.
Personalization and power
The Volume-Control Model offers an analytical framework to understand how personalization helps to gain power. It links between information personalization and the opposite mechanism, information Popularity. This model explains how both personalization and popularization are employed together (by tech companies, organizations, governments or even individuals) as complementing mechanisms to gain economic, political, and social power. Among the social implications of information personalization is the emergence of .
See also
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