Download - User experience issues -- Personalization vs. Customization

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Page 1: User experience issues -- Personalization vs. Customization

All Rights Reserved

Friday, April 7, 2023

CONFIDENTIAL

Vinay Mohanty & Devesh Jagatram

Personalization vs. Customization

User experience issues- A case study

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Contents

» Personalization - An Overview

» Personalization vs Customization

» Ideal Personalization Scenario

» Best Practice Case Studies

» Customization (My Yahoo!)

» Personalization (Amazon & Gmail)

» ANNEXURE - I

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Personalization - An overview

» What is Personalization?

Personalization is the process of tailoring content to individual users' characteristics or preferences.  It is a means of meeting the customer's needs more effectively and efficiently, making interactions faster and easier and, consequently, increasing customer satisfaction and retention.

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Personalization - An overview

» Web personalization is delivering different and unique content to each individual customer based on the customer's interests. It's your own version of the web site, a site just for you.

» The real benefit of personalization occurs when an individual has an "aha!" experience that occurs when the content adapts itself based on the person's profile, and provides something new, different, and possibly unexpected.

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Personalization vs Customization

Customization Personalization

You explicitly specify what you want. It gives explicit user control (you are what you say you are)

E.g. choosing which information elements might be presented on a home page, choosing display colors, etc.

Customization is at a generic "feature" level, where you see/hide etc what you want

My Yahoo is an example of customization where you tell the site what you want

Personalization uses implicit interests and learns what you like from your actions (you are what you click on and what you buy)

E.g. getting the information related to one’s preferences and regular activities

Personalization is at the data/ content served level

Amazon.com is an example of personalization where the latter learns your interests and adapts to your needs

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Personalization vs Customization

www.amazon.com

Personalization

my.yahoo.comCustomization

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» A sample scenario depicting the ultimate goal of personalization.

The holy grail of e-commerce is always to achieve a real world experience , online. Something like …

»Sales Person: "Hi, how may I help you?“

»Customer: "I'm looking for a new digital camera.“

»Sales Person: "Great, did you have a model in mind?“

»Customer: "Uh, no, I'm not sure which model I need. I was hoping you could help me.“

»Sales Person: "Great! Well, let me ask you a few questions ...“

Personalization aims at creating such (like the above conversation) a compelling and strong user experience in on the web by anticipating the user’s needs i.e. the questions the customer is most likely to ask.

Ideal Personalization Scenario

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Best Practice Case Study for Customization

» My Yahoo!» http://my.yahoo.com

» Need for Customization» Prioritize content

» User Controlled content

» Customized Look & Feel for each user

» Promote regular usage of My Yahoo!

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Customization features in My Yahoo!

Name

Single point access with latest activities

related to each service

Single point access with latest activities

related to each service

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Customization features in My Yahoo!

Choice of services to be listed (users can

show / hide sections)

Choice of services to be listed (users can

show / hide sections)

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Customization features in My Yahoo!

Choice of colors / layout and other settings

pertaining to UI

Choice of colors / layout and other settings

pertaining to UI

Prioritizing services by specifying their

placement on screen

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Allowing users to add non-Yahoo! sections – providing access to all

frequently used services / sites from one point

Customization features in My Yahoo!

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Best Practice Case Study 1 :for Personalization

» Amazon» http://www.amazon.com

» Need for Personalization» Promoting sales of various products

» Build a relationship that encourages the customer to return

» Provide customized experience for online shopping to make it as real as in-person shopping

» Target each individual customer differently by providing one-to-one marketing

» Predict customer needs and purchase patterns

» Identify customer characteristics by initiating 2 way communication

» Make the interaction efficient and satisfying for both parties

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Personalization features in Amazon

Recording customer preferences by asking her to rate/tag products

( 2 way communication)

Recording customer preferences by asking her to rate/tag products

( 2 way communication)

Recording customer preferences by asking her to rate/tag products

( 2 way communication)

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Personalization features in Amazon

Advertisements related to what’s on wishlists

Advertisements related to what’s on cart

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Personalization features in Amazon

NameName

Recommendations based on preferences of people

with similar profile

Recommendations based on preferences of people

with similar profile

Recommendations based on browsing history

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Personalization features in Amazon

Recently Viewed Items

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Best Practice Case Study - 2 for Personalization

» GMail» http://www.gmail.com

» Need for Personalization» Promote sponsor sites

» Predicting sites users might be interested into

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Personalization features in GMail

Informing users about sites they may be

interested into based on their email communication

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ANNEXURE - I

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Why personalize the web ?

» In an age of information explosion, personalization offers a way to focus on customers / users

» Personalization doesn't waste time showing you what everyone else sees and then asking you to search or display / hide things

» Better serve the customer by anticipating needs

» Make the interaction efficient and satisfying for both parties

» Build a relationship that encourages the customer to return for purchases

Customer Database

Business Applications

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Types of Personalization

There are three types of Personalization:

» Simple filtering A site displays content based on predefined groups of site visitors.

» Rules engines In a rules based system, the site owner defines a set of business rules which determine what category of content is shown when a certain profile type visits the site.

» Collaborative filteringThe preferences of the community of people with similar characteristics are used to predict appropriate content.

Decision

Content 1

Content 2

Content 3

Content 1

Content 2

Content 3

User

Users with similar preferences

Recommended Content

Similar preferences

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» Fill-in Profile/ forms: The user has to do lot of work filling complex questionnaires, which repels them.

» Click-stream Analysis/ Web Usage Mining: It does group profiling, but privacy issues remain.

» Cookies: ‘Tag’ / identify the user and his browser, but security issues remain with cookies.

» Measure directly by asking the user to rate products.

» Collaborative Filtering: It is fast emerging as best practice for personalization as it doesn’t have the above drawbacks.

Approaches to gather user data & Best practices

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Collaborative Filtering – A Best Practice

» In Collaborative Filtering, choice of content is based on the assumption that this particular user will value that which the like-minded people also enjoyed. The preferences of the community of like-minded people are used to predict appropriate content.

» The user’s tastes are either inferred from their previous actions (for example buying a book, or viewing a product is assumed to show an interest (or taste) for that product).

» This method has an advantage of speed and efficiency in computation, thus delivering rapid feedback. The reliance on a ‘critical mass’ of users can be a problem for collaborative filtering.

» Recommendation systems use collaborative algorithms (they are the programs which attempt to predict items like movies, music, books, news and web pages that a user may be interested in, given some information about the user's profile).

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How personalization software can help ?

» Personalization software contain a dynamic recommendation system based on collaborative filtering. E.g. IBM Like Minds is software that could be used with any e-commerce application. It analyze user interactions that occur on websites and generate real time predictions and recommendations for users.

» For example, the following types of transactions may be recorded:

» Products a user has purchased

» Items added or removed from a shopping basket

» A history of the user's navigation throughout the application

» Products that go best with a product that the user has already selected

» Any action or series of actions that are meaningful for a site

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Domains where we can use personalization software

The personalization software could be used in a variety of situations:

» e-Retailer promotion and personalization web sites

» Financial portal content recommendation and personalization web sites

» Help desk or on-line technical support content recommendation web sites

» Gift recommendations for e-Retailer

» Music, movie, book, or other product rating and recommendations

» Travel - trip planners

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Personalization software products

» Red Dot. Live server

» Plum Tree (Enterprise web Develop Kit, EDK)

» IBM Like minds

» Autonomy's Agentware 1.1

» Response Logic

» Broadvision Personalization tools

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» Computer , Don’t 2nd guess me !

» “Don't stereotype me - just give me the options because I prefer choosing for myself rather than having the computer tell me what's good for me”

» What users want on one visit may be very different from what they want on the next.

» Don’t ignore basic design & User Experience

» Web personalization is much over-rated and mainly used as a poor excuse for not designing a navigable website.

» There is no substitute for good design, usability engineering and proper information structure.

Is Personalization needed? Where will it not work?

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» Privacy / ethical issues?

» Consumers are clearly expressing an interest in a personalized experience. But at the same time, they are expressing significant fear about security of their personal information.

» “Should I share my likes & dislikes with anyone for a more personalized online experience?”

» Paradox of the active user

» Users never want to waste time teaching/training the system about themselves by filling complex forms, questionnaires. They want to do, explore and want results, right away.

» Good personalization requires the system to know a lot about the user. This is in direct conflict with the paradox of the active user.

Is Personalization needed? Where will it not work?

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Thank You