lecture10_e-commerce-3x - The University of Aberdeen

wallbroadSecurity

Dec 3, 2013 (3 years and 10 months ago)

120 views

Computing
Science, University of Aberdeen

1

E
-
Commerce


customer focus


Transactions, money, trust


Attracting and keeping customers

»
Key issue
:

trust, security


Legal issues


Personalization


Adverts





Computing
Science, University of Aberdeen

2

Transactions … in the
beginning


Barter


exchange one good for another


Strictly a two way thing.


Exchange happens simultaneously
(mostly).


Little, or no, trust needed




Computing
Science, University of Aberdeen

3

Transactions


commodity
money

-
Exchange
standard items with known
(supposedly intrinsic) value.

-
These
standard items are more liquid,
easier to exhange, move faster.

-
Can store for later use.

-

e.g. Weights of metal, peppercorns,
sheepskin, pigs, cattle

-

Limited trust in retained
intrinsic value




Computing
Science, University of Aberdeen

4

Transactions


representative
money

Token money

-

Early on, might be linked to a commodity

-
probably not now

-
`just a way of keeping score’

-
Even more liquid, easier to store, exchange

-
Need to trust that money will keep being
tradeable in future, and of not much less
value


Computing
Science, University of Aberdeen

5

Transactions


money

Fiat money


money that gets value,
because the government and the law
says it has (and because we believe it).


Paper money


only used widely in
Europe for last 200
-
ish years, initial trust
problems, bank runs.

http://en.wikipedia.org/wiki/John_Law_(economist)

Computing
Science, University of Aberdeen

6

Money


modern


Cash


Money held in physical capital


Money in bank


Money invested in bonds, equities


Credit


Credit and debit cards


Electronic transfers of money




Computing
Science, University of Aberdeen

7

Money


modern


Electronic transfer of money central to
e
-
commerce.


Ability to accept credit (or debit) cards
central to success at scale of B2C and
C2C.


Standards, e.g.

https://www.pcisecuritystandards.org/




Computing
Science, University of Aberdeen

8

Transactions


Evolution of money and social mechanisms has
enabled us to develop
two
-
part transactions:
money
and goods (or services) exchanged at different times.


Also
credit


Rely on

»
interpersonal trust,

»
social reputation,

»
law.




Computing
Science, University of Aberdeen

9

Money:

trust, reliability, security


Need to be sure that it will continue being acceptable


Need to be sure that it won’t lose too much value


Need to trust that our electronically stored `score’ is kept safely
by bank.


Need to be sure that electronic transfers out (and in) work
properly and are secure. [Banks and systems connecting them]


Need to be sure that credit and debit system work correctly and
are secure.


Need to trust that traders will deliver upon payment.


Traders need to be sure that they will be paid if they deliver.



Computing
Science, University of Aberdeen

10

PayPal


http://www.
paypal
.com


Users set up an account, linked to a bank account or credit card.


Enables small businesses and consumers to accept credit card
payments via paypal.

»
A lot less overhead than accepting and processing credit card details
directly.

»
Reduction in overheads enables many more participants, more trade.


Various competitors available, but economic
network effects
in
play (
natural

monopolies

and
oligopolies

emerge)


In the early days, eBay tried to set
-
up own alternative, but users
insisted on Paypal.

»
eBay gave up and bought Paypal instead.



Computing
Science, University of Aberdeen

11

Internet Escrow


Escrow
: money held by a third
-
party on behalf of transacting
parties (roughy).


Used where transacting parties have limited trust in each other


Internet escrow
:

»
Transaction between buyer and seller

»
Buyer places money in control of trusted, independent third party

»
If both verify delivery had taken place and is complete, then money is
released

»
If not, then some dispute resolution process kicks in.


E.g.
http://www.escrow.com



Computing
Science, University of Aberdeen

12

BitCoin


Emerged in last couple of years.


Open source, peer
-
to
-
peer network to track and verify
transactions.


Cut
-
out middlemen (financial institutions) in electronic
transactions using clever cryptograpic prototcols.


http://www.bitcoin.org/bitcoin.pdf


Teething problems

»
No fiat from any government (relies on designer/community?)

»
If protocols breached, value could disappear

»
Value of currency is not yet
sticky

(no irrational, but helpful, faith in it)

»
Economic problems related to design (limited monetary expansion)

http://krugman.blogs.nytimes.com/2011/09/07/golden
-
cyberfetters/


Computing
Science, University of Aberdeen

13

Customer Focus

Computing
Science, University of Aberdeen

14

Customers are

not

all the same!


Consumer types

»
Individual consumers

»
Organizational buyers


Computing
Science, University of Aberdeen

15

Customers are

not

all the same!


Consumer types

»
Individual consumers

»
Organizational buyers


Goal of shopping

»
Pragmatic: buy something useful, cheaply

»
Hedonistic
: have fun


Computing
Science, University of Aberdeen

16

Customers are

not

all the same!


Consumer types

»
Individual consumers

»
Organizational buyers


Goal of shopping

»
Pragmatic: buy something useful, cheaply

»
Hedonistic
: have fun


Personality

»
Impulsive
buyers


purchase
quickly

»
Patient
buyers


make
some comparisons first

»
Analytical
buyers


do
substantial research before buying


Computing
Science, University of Aberdeen

17

Consumer
Behaviour

Prentice Hall, 2002

Computing
Science, University of Aberdeen

18

Consumer Satisfaction

Prentice Hall, 2002

Computing
Science, University of Aberdeen

19

Trust/Security


Trust/Security

»
Will the company actually deliver the correct
product/service
in reasonable shape, in a
reasonable time, at correct price

»
Will the customer pay up (is the credit card stolen,
will it be repudiated)


Technical aspects


Human aspects: Focus here

on
trust

and, to some
extent,
policies


Computing
Science, University of Aberdeen

20

Trust in physical shops


Experience: shoppers trust shops
they’ve used before


Appearance: shoppers trust store that
look reputable


Complaints: easy to complain, shop
can’t hide


Transactions are simple

Computing
Science, University of Aberdeen

21

On
-
line trust


What makes you trust an e
-
commerce
shop?

Computing
Science, University of Aberdeen

22

On
-
line Trust


Experience: I trust Amazon because I’ve used them
before

»
Reputation: because my friends use them


Very important with
e
-
shops

»
Specific technicalities; for example,
accounts/cards compromised or not?


Appearance:

Do
I trust Amazon because they have a
nice
website?

»
Less important than with physical shops

»
Marketing helps

Computing
Science, University of Aberdeen

23

On
-
line trust


Complaints: Harder to complain since
don’t know where shop is


Transactions are complex because of
delivery

»
Where many
e
-
shops mess up


Third
-
party: do I trust Amazon more if
another web site says good things
about
Amazon?

Computing
Science, University of Aberdeen

24

Does Amazon Trust Me?


Amazon trusts me because

»
Experience: I’ve always paid Amazon before

»
Reputation: I’ve used other companies and always
paid up

»
Marketing: vendors generally signal that nasty
things happen to customers who don’t pay up


credit record affected


legal consequences

Computing
Science, University of Aberdeen

25

Trust


We know quite a bit about how trust is
established in physical shops.


We are developing mechanisms for
establishing trust in e
-
shops

»
Partially technology, but human factors
(psychology, sociology, economics, law) probably
matter as much

»
Lack of trust mechanisms is barrier to new e
-
shops

Computing
Science, University of Aberdeen

26

Legal Issues: Tax


In USA, one driving force behind early
e
-
store success was lower tax

»
Because of a tax loophole, sales tax (VAT)
was not charged on e
-
commerce sales

»
Automatically gave price advantage to e
-
commerce sites!

Computing
Science, University of Aberdeen

27

Legal Issues: Intl E
-
Commerce


In theory, e
-
commerce means sites can
sell globally


In practice, difficult because of different
tax rules, regulations, customs, etc

»
More common to set up subsidiaries in
different countries, as Amazon has done


Lack of global legal/regulatory
framework hinders ecommerce

Computing
Science, University of Aberdeen

28

Personalization


E
-
Commerce sites can treat customers differently

»
Offer recommendations, special deals

»
Personalise web site

»
Adjust prices


In theory, “personalised shop” one of the great
benefits of e
-
commerce


Can also take advantage of more of
long tail

»
Don’t need to keep stock in same way as traditional shop

»
Can do things like Print On Demand


One
-
to
-
One Marketing

Build a long term association

Meeting customers cognitive needs


Customer may have novice, intermediate or expert skill

E
-
loyalty

customer’s loyalty to an e
-
tailer


costs Amazon $15 to acquire a new customer


costs Amazon $2 to $4 to keep an existing customer

Trust in EC


Deterrence
-
based

threat of punishment


Knowledge
-
based

reputation


Identification
-
based

empathy and common values


Referrals


Viral Marketing

Personalisation…

Personalisation
-

Marketing Model

“Treat different customers differently”

Prentice Hall, 2002

Personalisation


“Process of matching content, services, or
products to individuals’ preferences”


Build profiles


N.B. Privacy Issues


Solicit information from users


Use cookies to observe online behavior


Use data or Web mining

Computing
Science, University of Aberdeen

32

Recommendation


Build profiles

»
What has X bought?

»
What has X looked at?

»
Demographics: age, gender, etc


Recommendation

»
Rules: If X buys Harry Potter 6, recommend HP 7

»
Data Mining: Other people who bought Harry
Potter also bought Lord of the Rings

»
Collaborative: X’s overall buying profile is similar
to Y, so recommend whatever Y bought


Data Mining

Automated prediction of trends and behaviors


Example: from data on past promotional mailings, find out
targets most likely to respond in future

Automated discovery of previously unknown patterns


Example: find seemingly unrelated products often purchased
together


Example: Find anomalous data representing data entry errors

Mining tools:


Neural computing


Intelligent agents


Association analysis
-

statistical rules

Web Mining
-

Mining meaningful patterns from Web resources



Web content mining


searching Web documents


Web usage mining


searching Web access logs

searching for valuable information in extremely large databases

Computing
Science, University of Aberdeen

34

Recommendations


If done well, perceived very positively

»
Real benefit, not just marketing spam

»
Credit
-
card companies have done this well


Have the most purchasing data?


Data privacy issues

»
Can Visa sell data about you to Amazon?

»
Spyware to track all of your web browsing?

Computing
Science, University of Aberdeen

35

Personalise Web Sites


Let customers create their own “shop
front” focusing on their interest


Adjust appearance (eg, for visually
disabled, or strict, religious consumers)


Do
-
able, not huge success

Computing
Science, University of Aberdeen

36

Personalised Pricing


Companies would love to be able to
charge people different amounts for the
same product

»
Airline seats, cars, etc

»
Full price for people who are keen, in a
rush, don’t care about money

»
Discount for choosy/finicky

Computing
Science, University of Aberdeen

37

Personalised Pricing


Amazon, etc have tried this, but
customers hated it.


So has gone “underground” for now.


Technology permits this, but society’s
expectations does not allow it

Computing
Science, University of Aberdeen

38

Advertising


E
-
Shops (and other sites) can make
money via advertising

»
Google makes billions from its “sponsored
links”

»
Amazon has adverts as well

Computing
Science, University of Aberdeen

39

Web Advertising


Conventional advertising focuses on
visual appeal


Less successful on web

»
Flashy animated banner adverts are a
nuisance and distraction

Computing
Science, University of Aberdeen

40

Targeted adverts


Web allows relevant adverts to be
associated with a web page

»
Google sponsored links based on search

»
Amazon could display different adverts for
sci
-
fi and romance novel


Very effective if done well

»
So Web sites can charge more for targeted
adverts

Computing
Science, University of Aberdeen

41

Web adverts


Initially treated like TV adverts, put huge
effort into flashy multimedia banner ads


Now focusing on simple targeted
adverts instead


Advertising models cannot be blindly
moved from TV to web

»
need new models!

Computing
Science, University of Aberdeen

42

E
-
Commerce Summary


Initially tried to make e
-
shops similar to
high street shops. But

»
Need different business model

»
Trust issues much more important

»
Need appropriate legal framework


Computing
Science, University of Aberdeen

43

Customer Focus Summary


Sometimes technology really helps

»
Recommender systems, targeted adverts


Sometimes technology works, but
society doesn’t like it

»
Differential pricing


Trust


sine qua non


Computing
Science, University of Aberdeen

44

Assessment 1


Essay due
18
th

November.


Without delay
, go to
http://www.abdn.ac.uk/~csc245/teachin
g/CS5038/assessment/

for more detailed instructions.


Please read the instructions
very
carefully



and follow them!