Includes bibliographical references
|Statement||edited by Clare-Marie Karat, Jan O. Blom, and John Karat|
|Series||Human-computer interaction series -- v. 5, Kluwer international series on HCI -- v. 5|
|Contributions||Karat, Clare-Marie, Blom, Jan O, Karat, John|
|LC Classifications||QA76.9.H85 D483 2004|
|The Physical Object|
|Pagination||xii, 348 p. :|
|Number of Pages||348|
|LC Control Number||2004049262|
The book covers four main areas: Theoretical, Conceptual, and Architectural Frameworks of Personalization, -Research on the Design and Evaluation of Personalized User Experiences in Different Domains, -Approaches to personalization Through Recommender Systems, -Lessons Learned and Future Research Questions. The present workshop aims to form a community of individuals interested in exploring the user implications of personalized eCommerce applications. People working in industry, academia, and government are welcomed to participate. The aim of the two-day workshop is to access the current state of theory, methods, and research in this area and to create a theoretical framework on personalization of the user experience in eCommerce . But if you’re looking for places to start, here’s a list of four ways to create more personalized ecommerce experiences. Situation-specific landing pages One of the more jarring situations for an ecommerce customer is when they click on a link for a deal or for a specific product, only to arrive at that site to find no relevant copy or Author: Jared Hecht. CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): What is IA and why it matters Information architecture has an evolving set of definitions, but I think for this workshop, the most important aspect is: Within the broad user experience team, an information architect is the one who is tasked with focusing on how the content in organized.
This 3-part guide aims to address how retailers of varying sizes can optimize their customers’ personalized shopping experience with. Personalization Starts with Data Collection. Before we get into the practical application of a personalized experience, it really is important to establish the foundation of personalization: data collection. Outstanding user experience is an invaluable asset for eCommerce growth. But because running a large online store is a strenuous task with many ins and outs, UX-oriented eCommerce design is often left out of the focus. This business niche is saturated and many new stores are entering the market. 5. Send Personalized Email Based on User Behavior. One way to drive more sales with eCommerce personalization is to continue marketing to visitors even after they leave your site. Amazon does this extremely well, sending follow up emails and personalized newsletters to alert customers to deals on items they’ve seen. A personalized shopping experience is not limited to your ecommerce site. From email to social media, you can stay in touch with and create a unique relationship with each shopper. According to Invesp’s research, email is by far the most important digital channel for online shopping personalization.
In: C.-M. Karat, J. Blom and J. Karat, eds: Designing Personalized User Experiences for eCommerce. Dordrecht, Netherlands: Kluwer Academi c Publishers, The new design-centric daily deal site brings smart design to the checkout process. What works: Fab sells design, and the big bold images and limited daily offering make browsing new products fun and easy. Fab’s “feed” is a Pinterest-like feed of all the products being bought and . Design online experiences for intent-driven moments. Principle Be iterative (continuous improvement) Never approach the online experience design process thinking it’s a “one–off”. The iterative continuous improvement discipline comes in two parts: Data mining, insight gathering and hypothesis creation. All customers are unique and their experiences are increasingly becoming unique. Subsequently, each and every customer experience needs to be captured, quantified, and qualified. Relying on data that is sampled, aggregated, or averaged obscures the variation inherent in real CX patterns when providing personalized experiences.