Personalization & Interactivity

Interactivity Machine Interactivity Product Interactivity Virtual product experience Navigation/Site Interactivity Hyperlinks Agents Site Map Person Interactivity Customer-Customer Customer-Company Focus groups Brand community W.O.M

E-mail contact

Pertinent machine vs. person interactivity reference

: Hoffman and Novak, 1996

Response to Interactivity Depends on Motivation for Visiting the Site Why do people visit Web sites?

To search – To find particular information while expending minimal time and energy – Purposive, task-specific behavior – Pre-purchase deliberation – Think more about products To browse – To be delighted and entertained – Recreational/ experiential behavior – Not efficiency-oriented – Think more about Web site execution

Features Likely to Increase Online Purchasing Feature

"Close-up" product images Product availability Product comparison guides Search function 1-800 Customer service number Consumer reviews/evaluations Catalog quick order Source: PricewaterhouseCoopers, 2001

% of Shoppers Indicating Feature Increases Purchase Likelihood

44% 39% 34% 30% 25% 24% 24%

Sensory Breadth Sensory Depth

“Sticky” Sites

Vividness Telepresence Feeling present in the created environment Speed Range Mapping Interactivity

Personalization Systems

Customer Preferences in Product Space Key Product Attributes Qualitative, Complex (e.g., experience goods) Quantitative, Few (e.g., search goods) Uniform Highly differentiated

Endorse

•Customer benefit: choice simplification •Firm needs satisfaction database

Rule-based

•Customer benefit interaction management •Firm needs user models and observable triggers

Collaborative filtering

•Customer benefit: educated word-of-mouth •Firm needs extensive user data and clustering

CASE

•Customer benefit: show individual’s utility function •Firm needs extensive product database and user cooperation

Rule-based system

Collaborative Filtering

• Based upon other users’ overall ratings of items in the database, as well as the target user’s own evaluation. • Identifies other people who are “nearest neighbors” (most similar) to the target user. Those nearest neighbors most similar to the target user are weighted most heavily. • Prediction of what the target user might like is based upon what the weighted nearest neighbors liked.

A Closer Look at Collaborative Filtering

Jack Phil Jean Ted Bill Pat 5 5 2

A

1

Book B C D

1 5

?

1 2 2 2 4 5 1 3 1 3 3 3 4

Criticisms of Collaborative Filtering

• •

Inefficient

for marketers since you can not control what is recommended

“Black Box”

why.

approach - if it works, we don’t know •

Does it work?

– Industry models (LikeMinds, Firefly, NetPerceptions) are proprietary algorithms and we don’t know how well they work.

– Selection of similarity index (who is closest to the target user?) and clustering algorithm (how do we identify the nearest neighbors?) is often atheoretical, adhoc, and a guess.

Product categories?

• Marketing issue is that you don’t have any say on what product the software will recommend.

• Taste is important.

• Product must exist - not concept testing or new products.

• Consumer doesn’t have sufficient first-hand experience.

• The fewer desirable items, the more effective.

Profile x Timing

Increasing Levels of Knowledge • Valid name + database • Valid name • User ID • Cookies • Log Analysis • Session online behavior • Average visitor statistics • Anonymous

Branded Response

Yesmail.com

• What solution would you favor for the recruitment of new members? The “network solution”? Build a proprietary list? Both?

• What does yesmail bring to its members? To its clients? Would you recommend that yesmail adopt a different pricing policy?

• What is the future of agents such as yesmail.com? On the basis of this, what would you recommend that yesmail do?

Onsale

• When Kaplan created the Onsale format, he called it “a new form of retailing that exploited the unique characteristics of the net.” In what ways is Onsale’s model different from traditional retail models?

• Is Onsale performing well? What are the benchmarks for performance in this market?

• Evaluate the AtCost model. What are the benefits and risks? How would you propose they overcome the risks?