Understanding the Impact of Web Personalization on

User Information Processing and Decision Outcomes

By: Yousra HabibDr. Dina Rateb

Spring 2011

Web PersonalizationCompanies (Online Merchants) provide

personalized offerings and unique experiences to customers(Users)

Brand promotion Product Marketing After-sales Support

On going hype of delivering personalized services over the web

Little Knowledge of important links to vital concepts and factors

Important Correlation

User’s Information Processing &

decision making

IT artifact(personalizatio

n agent)

Effectiveness of Web

Personalization

Affect

Content Relevanc

e

Self Referenc

e Goal Specificit

y

Attention Cognitiv

e Processe

s

Decisions of Web Users

Factors involved in Web Personalization

Web Personalization Goal

“ delivering the right content to the right person at the right time to maximize immediate and future business opportunities ”

Personalization Strategy to Achieving the goalImmediate Opportunities

Control the content, presentation format and timing of personalized messages or offers to induce a favorable response to the merchant’s offerings

Future Opportunities Increase Likelihood of accepting firm’s

offerings in the future by implanting marketing messages in the user’s mind

Purpose of Article: Conceptualization of Web Personalization

Highlights factors behind personalization strategies & their impact on different stages of information processing of a user.

Human Information Processing Model

Permanent

Memory

Study 1: Lab ExperimentDesign

3x2x2 designContent Relevance(Relevant versus irrelevant)Self Reference(presence versus absence of relevant

content)Goal specificity( Product Selection versus product-

browsing versus random-browsing)Procedure

4 Phases 1) a 12- minute study phase to navigate through an online shop 2) a 5-minute distraction phase to clear the working memory 3) a memory recall test 4) Filling in a questionnaire

Phases of Study 1

1) a 12- minute study phase

• to navigate through an online shop

• Random assignment to these task:• 1) Product

Selection 2)Product-browsing

• 3) Random browsing

2) a 5-minute

distraction phase

• To clear the user’s working memory

• Provide details on their demographics

• Take a rest

Memory Recall Test

• Using a PC• YES-NO

recognition test such as in Cognitive research

Filling in a Questionnai

re

• Evaluating the entire process

• Seven-point Likert Scale

Study 2: Field StudyConduct of field study with a personalized

music download site.Online site set for a closed community of

registered users.Login before download requiredDatabase containing a large collection of

digitized songs.

Phases of Study 2: Field Study

• Logon filling questionnaire about music preferences in terms of category, artists, etc

• Collected data processed by Agent to generate rules for driving the personalization content

• Assign each user a password and logon name

1st

• Users allowed to download songs from the site over a 6-week period.

• New songs were added to the web site

• Easy Access & download to the music site

2nd

The Research Model

H1: Users attend to self-referent web content to a larger extent than they attend to non-self-referent web content.

H2a: Users recall self-referent web content faster and more accurately than they recall non-self-referent web content.

Self Referenc

e

# Click 0n

Stimulus

H1

Attention

Self Referenc

e

Content Recall

H2a

Cognitive ProcessingInformatio

n Exploratio

n

Self Reference

Result: measured by the number of clicks on the 2 different banners. # of clicks were 5.19 for self referent & 1.95 non self referent. Therefore supported

Result: The response in time between the self referent and non-self referent was insignificant. Thus not supported.

H3a: Users exposed to self-referent web content will seek less information and spend less time on decision making than when they are exposed to non-self referent web content.

H4a: Users accept offers associated with self-referent web content to a larger extent than they accept offers associated with non-self-referent web content.

Self Referenc

e

Content Recall

H3a

Cognitive ProcessingInformatio

n Exploration

Self Referenc

e

Final Choice

H4a

Decision

Self Reference Cont’d

Result: Product Searching Subjects with self referent banners spent less effort in decision making. Supported hypothesis

Result: Product Searching Subjects accepted self referent banners from the banner recommendations. Supported Hypothesis

H2b: Users recall web content relevant to their processing goal faster and more accurately than they recall irrelevant web content.

H3b: Users exposed to relevant web content will seek less information and spend less time on decision making than when they are exposed to irrelevant web content.

Content Relevance

Content Relevanc

e

Content Recall

H2b

Cognitive ProcessingInformatio

n Exploration

Content Relevanc

e

Content Recall

H3b

Cognitive ProcessingInformatio

n Exploration

Result: Relevant Content could be recalled faster thus Supporting this Hypothesis.

Result: Subjects exposed to congruent offers to personal preferences spent less effort in decision making

H4b: Users accept offers associated with relevant web content to a larger extent than they accept offers associated with irrelevant web content.

Content Relevance Cont’d

Content Relevance

Final Choice

H4b

Decision

Result: H4b was not supported as there wasn’t a significant difference in the songs chosen

H2c: There is a larger difference in recall accuracy and response time between relevant and irrelevant web content for users with more-specific processing goals than for those with less-specific processing goals.

ContentRelevance

Goal Specificity

Content Recall

Cognitive Processing Informatio

n Exploration

H2c

Result: The difference in recall between relevant and irrelevant content for product selection group was larger than that of the product browsing group.

H5a: Users evaluate self-referent web content more highly than they evaluate non-self-referent web content.

H5b: Users evaluate relevant web content more highly than they evaluate irrelevant web content.

Evaluation

Self Reference

Evaluation of

Offers

H5a

Evaluation

ContentRelevance

Evaluation of Offers

H5b

Evaluation

Result: The perceived usefulness of banner messages was evaluated higher in the self-referent group. Supported Hypothesis

Result: Receiving recommendations from personalization agents made the subjects more satisfied rather than random offers. Supported Hypothesis

LimitationsThe number of recall tests was 32.

Can cause Fatigue in subjects Impair their recall performance Randomizing their responses at the end of the test

Overestimate the Recall performance of Irrelevant Information Both Banners although different content and purpose placed in the same

location on a rotating basis

Both studies Intended to test proposed model but weren't exactly the same

Control experiment- make observations on memory recall Study 2 was over a period of 6 weeks, a recall test was not feasible.

Different products were tested upon and of complete different categories

ConclusionPersuasive Effectiveness of a self-referent message increased

initially but decreased when such messages were overused resulting in a U-shaped Effect.

Findings apply to a wide range of web-based services that target attracting user’s attention & influencing their information processing.

Based on the Findings Personalization could offer competitive advantages to online merchants.

Personalized messages are perceived to be more useful and create willingness to explore personalized content further.

Reduces Information Overload and is an aid to Decision Making

Article Authors

Kar Yan TamDepartment of Information and Systems ManagementSchool of Business and ManagementHong Kong University of Science and Technology, Clear Water Bay, HONG KONGkytam@ust.hk

Shuk Ying HoDepartment of Accounting and Business Information SystemsFaculty of Economics and CommerceThe University of Melbourne Victoria 3010 AUSTRALIAsuho@unimelb.edu

Citation:Kar Yan, Tam, and Ho Shuk Ying. "UNDERSTANDING THE IMPACT OF WEB PERSONALIZATION ON USER INFORMATION PROCESSING AND DECISION OUTCOMES." MIS Quarterly 30.4 (2006): 865-890. Computers & Applied Sciences Complete. EBSCO. Web. 22 Mar. 2011.

Any Questions?