Personalization

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"Customization" redirects here. For other uses, see custom.

Personalization or personalisation (see spelling differences) is tailoring a consumer product, electronic or written medium to a user based on personal details or characteristics they provide. More recently, it has especially been applied in the context of the World Wide Web.

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Web pages are personalized based on the interests of an individual. Personalization implies that the changes are based on implicit data, such as items purchased or pages viewed. The term customization is used instead when the site only uses explicit data such as ratings or preferences.

On an intranet or B2E Enterprise Web portals, personalization is often based on user attributes such as department, functional area, or 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.

There are two categories of personalizations:

  1. rule-based
  2. content-based

Web personalization models include rules-based filtering, based on "if this, then that" rules processing, and collaborative filtering, which serves relevant material to customers by combining their own personal preferences with the preferences of like-minded others. Collaborative filtering works well for books, music, video, etc. However, it does not work well for a number of categories such as apparel, jewelry, cosmetics, etc. Recently, another method, Prediction Based on Benefit is proposed for products with complex attributes such as apparel[1].


Many companies like Choicestream, Loomia, Certona, Aggregate Knowledge, MyBuys, Minekey, and MyShoppingPal.com offers services for web recommendation and email recommendation that is based on personalization.


Personalisation is also being considered for use in less overtly commercial applications to improve the user experience online [2].

Google is the first of the "Big Three" search engines to introduce personalized results on a massive scale. Weighing a number of factors including but not limited to user history, bookmarks, community behaviour and site click-through rate and stickiness, Google is providing results that are specific to what they believe you are searching for.

Currently this service is only available to those who are logged into their Google account [3].

Amazon.com has been the early adopter of personalization technology to recommend products to shoppers on its site, based upon their previous purchases. Amazon makes extensive use of Collaborative Filtering in its personalization technology.

Personalization does not necessarily need to be based on individual user accounts (as is conventional); it can also be based on region or language (see localization) or browser.

Main article: Mail merge

In print media, ranging from magazines to promotional publications, personalization uses databases of individual recipients’ information. Not only does the written document address itself by name to the reader, but the advertising is targeted to the recipient’s demographics or interests using fields within the database, such as "first name", "last name", "company", etc.

The term "personalization" should not be confused with "variable data", which is a much more granular method of marketing that leverages both images and text with the medium, not just fields within a database.

Promotional items industry (mugs, T-shirts, keychains etc.) are also regularly personalized. Personalized children’s storybooks — wherein the child becomes the protagonist — have also appeared.[1] Personalized CDs for Children such as Songs Just For Me are becoming very popular, as children (and parents) enjoy hearing their names in songs. [2]

Mass personalization is defined as custom tailoring by a company in accordance with its end users tastes and preferences [3]. The main difference between mass customization and mass personalization is that customization is the ability for a company to give its customers an opportunity to create and choose product to certain specifications, but does have limits [4].

Personalization allows a company to tailor a specific product in accordance with individual standards, tastes and preferences. For example, baseball jerseys can be customized based on size, colour, team and logo, however there are a finite number of choices for these variables to choose. To personalize a jersey, a name or number can be administered to it as well as custom fitting. [4]

The emergence of e-commerce has allowed for the personalization of clothing as well as the customization of audio CD’s and downloading of music as well as graphic design for personal websites from the comfort of one’s own home. Computer companies such as Dell have been widely regarded as a market leader in made to order desktops or notebooks for high-performance and entertainment needs. Consumers are able to place orders based on product family, usage, price range, processor, and form factors. This customization ensures that each purchaser can view the merchandise available in order to make an informed decision. [5]

However, with the ability to altar images digitally and upload personalized pictures and logos, the personalization world seems limitless. In an age of increasing globalization Thomas Friedman argued in September 2005 during an MIT lecture that “companies were increasingly feeling the pressure to customize their products for each and every client.” [6] The end result is that B2C e-commerce may become so fixated on satisfying the consumer through being a low-cost competitor that maintenance, repair, and reliability of the product can decline.

Furthermore, customization for consumers has been had increasing importance as firms utilize the internet to provide products and services to the customer. This means of delivery lacks human interaction and in an effort to create a similar experience. As a result, information and consultation by experts on clothing and technology purchased online does not exist, leaving consumers the onus on being knowledgeable for all of their requirements. [7]

  1. ^ Personalization: Collaborative Filtering vs Prediction Based on Benefit Theory
  2. ^ Bowen, J.P. and Filippini-Fantoni, S., Personalization and the Web from a Museum Perspective. In David Bearman and Jennifer Trant (eds.), Museums and the Web 2004: Selected Papers from an International Conference, Arlington, Virginia, USA, 31 March – 3 April 2004. Archives & Museum Informatics, pages 63–78, 2004.
  3. ^ Sullivan, D., Google Ramps Up Personalized Search, 2 February 2007.
  4. ^ Haag et al., Management Information Systems for the Information Age, 3rd edition, 2006, page 331.
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