CS5038 The Electronic Society
2. A Quick Overview of Electronic Retailing
• B2C Retailing: types and ways to succeed
• Consumer Categories
• Consumer Decision Criteria
• Online Purchasing Aids
•
•
•
•
E-Tailing Business Models
Click and Mortar Strategy
E-tailing Problems
The middleman problem: e.g. travel industry
1
Business-to-Consumer (B2C) Retailing
• Ability to create direct relationships with consumer without
intermediaries like distributors, wholesalers, or dealers
• “Brick-and-mortar” = Traditional offline retailer
• “Click-and-mortar” = offline + online presence
• B2C Market success is derived from:
 Offering quality merchandise at good prices
 Excellent customer service
 Convenience
• Goods that sell well online
 Brand recognition and guarantees
 Digitized products – music, video, software
 Frequently purchased, inexpensive items
 Well-known items with standard specifications

no need to inspect
2
Dell
3
Portals, trust sites (2 slides ago)
Prentice Hall, 2002
Click and Mortar Strategy
Channel: route to customer (through delares/vendors/resellers/dealers and distributors, or directly (own shop or
web-site))
Channel Conflict:
 Any situation where channel members are antagonistic due
to real or perceived differences in incentives, rewards,
policies or support
 Levi’s stopped online direct sales, because
distributors complained
 Selling off old stock directly to make room for fresh
models may undercut dealers.
 Have to coordinate parallel channels of distribution, and
coordinate marketing strategies
 e.g., car dealer network + online direct sales
4
Click and Mortar Strategy (B)
Successful Strategies:
 Empower the customer – 24/7 service and information
 Store locators; Product information; Inventory
levels
 Speak with one voice – integrate back-end systems
 Customer gets the same information through
telephone or webpage
 Leverage the channels – use best channel for each part
of business process
 E.g. order electronically; physical sales return.
5
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
6
Consumer Categories
19% Social Shoppers:
enjoy shopping
20% Habit die-hards:
stuck in their ways
14% Ethical:
will purchase
provided
it is honest and ‘pc’
14% Experimenters:
ready to try new things
47% want to
shop
electronically
16% Value shoppers:
will purchase where
they see value
Michael De
Kare-Silver
Warning: these statistics are probably out of date!
17% Convenience:
responsive to things
which save time
or make life easier
Shopping avoider
Hunter gatherers
 enjoy comparison/ search
New technologists
 because it's cool
7
Diffusion of Innovation
A widely-accepted picture of technology adoption
Rogers, Everett M. (1962). Diffusion of Innovations, Glencoe: Free Press.
8
Demand, in
units
The Long (Fat) Tail
1000000+
Trad. channel
cut-off for
viable stock
E-commerce.
cut-off for
viable stock
13
J.K. Rowling
J.R. Hartley
A few big hits (green). A lot of stuff that sells poorly
(yellow). But a lot of the potential sales (in the area
under the curve) are yellow.
Titles, ordered by
sales, decreasing
9
Consumer
Behaviour
Prentice Hall, 2002
Purchasing decision-making model
6 major phases
 Need identification
 Develop Consideration Set
 Information search and evaluation of alternatives
 Choice Decision
 Configuration/Personalization
 Upgrade/Replacement
Need to help the Consumer at each stage of this process
• Return to this later from market-research viewpoint
11
Consumers’ Decision Criteria
1. Value proposition
 customer service, better prices, higher quality
2. Personal service
 treat the customer as a unique individual
3. Convenience
 self-contained site that serves all customer needs
4. Other criteria
 service after the sale, online help, return policy.
Advertisers try to Influence consumer decision
 Products—portfolio of items available
 Price of the products
 Promotion of products (ads & giveaways)
 Packaging and delivery.
12
Online Purchasing Aids
Shopping portals
 Comprehensive portals - many different sellers & comparisons
 Shop.lycos.com
 Niche oriented - specialised line of products (dogtoys.com)
Shopbots and agents
 Tools scout the Web for specific search criteria - Mysimon.com
Business ratings sites
 Sites that rate e-tailers - Bizrate.com, Gomez.com
Trust verification sites
 Evaluate and verify trustworthiness of e-tailers - TRUSTe
Escrow services
 3rd party to assure quality and proper exchange
Communities of consumers
 Epinions.com—searchable recommendations on products
13
 PriceGrabber.com—comparison shopping
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…
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
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
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
searching for valuable information in extremely large databases
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
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?
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
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
Personalised Pricing (B)
• 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
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
24
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
25
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
26
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
27
Consumer Satisfaction
Prentice Hall, 2002
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
E-Tailing Business Models (by revenue)
1. Subscription models
 Charge monthly or annual subscription fee for service
2. Transaction fee models
 Service fee based on the level of transaction offered
3. Advertising-supported models
 Charge fee to advertisers instead of customers
4. Sponsorship models
 Companies sponsor the business through donations
(usually supplemental income)
Alternative Classification (by service)
 Direct marketing – sell directly to consumers
 Pure-play e-tailers – do not maintain physical channel
 Traditional retailers with Web sites – 2 channels
 On-Demand Delivery Services (ODDS)

30
Firms that have a fleet to deliver direct to consumers
E-tailing Failures and Lessons Learned
 Profitability – Each additional sale must lead to additional profits
 “if it doesn’t make cents it doesn’t make sense”
 Some pure play e-tailers lose money on every sale to grow to profitable
size and scale
 Branding – drive to establish brand can lead to excessive spending
 Strategy based on assumption that they will get quick customer
recognition
 Performance
 Web sites need to function in a fast, user-friendly manner
 Security (we’ll return to this later)
 Static design or dynamic sites – rich databases of useful information
encourage customers to return
 Incorrect Revenue Model – many were relying on advertising.
 Lack of funding – takes time to acquire sufficient customer base,
investors were not willing to wait / take the risk
 First-mover may make mistakes, second-mover can learn
31
Middleman Problem
(a case study in the travel industry)
• Retailers are “middleman” between provider and
customer
• Traditionally make money by mark-up
 Buy product from supplier for £10, sell it to
customer for £15
 Difference (£5) is profit margin
32
Middleman problem
Competition keeps profit margin down
 If you have a £5 mark-up, customers will go to
competitor with £4 mark-up
Suppliers may sell direct to customer
 If supplier sells product to customer for £12, he
and customer benefit
 Disintermediation
Hard to make money by mark-up in e-Commerce.
33
Example: Flights
Pre-Internet, airlines sold flights to consumers via travel
agents.
 Travel agent charged £100, gave airline £80 and
kept £20 as mark-up
 If customer bought directly from airline, would be
charged £100 (same as from travel agent)
How did agents add value?
34
Example: Flights
In Internet age, airlines sell flights directly to customer
 Airline sells flight to both customer and travel
agent for £80.
 If travel agent sells flight to customer for £80, he
won’t make any money
 If travel agent charges £100, customer will buy
direct from airline for £80
How can travel agent make money in Internet age?
 Especially a small one, not Expedia
35
Business Models
Sell extras, upgrades:
 Sell flight at cost price, but extras at high markup
 E.g., insurance, delivery
 Use loss leaders and technology lock-in, e.g.
http://www.bbc.co.uk/news/technology-19907546 .
Make sales elsewhere
 Sell advertising space on website
 Sell customer data.
Address niche market
 Specialize in travel to, say, Poland
 Flights, hotel, airport transfer, tours
 Specialize in selling flights to universities
 Failures from poor understanding of niche, e.g.
``Pink it, Shrink it’’ http://www.bbc.co.uk/news/business-1988472036
In these cases, how is value added?
Business Models (B)
Branding
 Build up a good reputation, so customers trust you
to offer OK deals, good delivery
 If you’re trustworthy and “cheap enough”, it is
not worth the hassle of looking at competitors
• Satisficing
 Means trusted shop can charge a bit more
 Marketing helps branding
 Customers visiting site helps
 Even if no purchase, just looking
37
Business Must Change
Successful Internet travel agents differ from successful
pre-Internet travel agent
 Old: small shop selling generic flights to local
customers with high mark-up
 Joe’s travel agency
 Where’s the added value for the custommer?
 New: focus on product niche, high mark-up extras,
advertising revenue, brand
 Expedia, escape2poland.co.uk
 Where’s the added value for the customer?
38
Internet Business Model
Internet requires new business model(s)
Management issue (mostly), not technology
 But must be resolved in order for e-commerce to
really take off
Poor business models one cause of dot-com boom/bust
 Pouring in money before business model issue
resolved is a mistake!
39
E-Commerce Bus. Mod. 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
Organizational Change
Internet (and most new tech) cannot be fully exploited
unless society changes
Change is painful for companies
 Many bankrupt small travel agents
 Many bankrupt dot-com investors
41
Organizational Change
Change is painful for individuals
 Loss of skills: Joe has worked for 30 years
selling generic hols to Spain, does this well
 Must ditch this, learn new skills
 Dislike model: Joe dislikes “encouraging”
customers to buy overpriced insurance
 Loss of income: average income of travel agents
may go down, even if they adapt
42
Summary
• Consumer Categories – value shoppers, convenience
shoppers
• Consumer Decision Criteria – value, service, convenience
• Online Purchasing Aids – portals, shop-bots, trust sites
• E-Tailing Business Models
• Click and Mortar Strategy
• E-tailing Problems – channel conflict, wrong revenue model
• Case study from Travel Industry
• Need for organizational change
43
E-Commerce in the News
• OFT details widespread ongoing problems with
compliance with UK Distance Selling Regulations
• ``More than a third of the UK's top online retailers
could be breaking consumer laws, the Office of
Fair Trading (OFT) has said.’’
• http://www.bbc.co.uk/news/business-19910561
• http://www.oft.gov.uk/shared_oft/research/OFT145
2_Websweep_report_2012.pdf
• Facebook pays £238 000 in (corporation) tax in the
UK despite advertising revenue of £175 000 000
(estimated).
• Only reports £20 000 000 revenue in the UK.
• http://www.bbc.co.uk/newsbeat/19910456
44