Within this chapter, industry case studies are provided as illustrative examples of con-
sumer and retailer behaviour in the online trading environment. Additionally, academic
articles are introduced to support underlying theoretical issues and concepts.
Levels of consumer demand for online shopping and services might ultimately deter-
mine the size of e-retail markets and when or if a market saturation point will be
reached. Currently, influences such as, whether the consumer has access to the Internet,
levels of competency in use of the technology and the perceived benefits of Internet
shopping are key factors likely to impact on the success and development of e-retailing
(Ballantine, 2005). Internet retailing, or e-retailing as it will be referred to for the rest of
this chapter, offers the consumer an experience that is very different from shopping in
the high street, for example comparison shopping is much easier and quicker online than
in the physical world (Cude and Morganosky, 2000). An example of a business that facil-
itates comparison of product and prices is Kelkoo.co.uk. Indeed, in the USA, consumers
use the Internet to find information about a product in the early part of the buying deci-
sion-making process as well as buying directly on the web. They are purchasing through
the fixed-location store or ordering by telephone or fax less than they used to (see Mini
Case Study 10.5, The offline impact of online marketing). Other notable differences
between on- and offline shopping are: dynamic pricing, which is often linked directly to
demand, interactive promotions and web-stores, which are always open.
As a result of the characteristics of the virtual shopping environment, the online con-
sumer experience can become an elective and very goal-orientated activity whereby
online consumers go to the Internet to seek particular information about the products
and services they wish to buy. Perea et al. (2004) highlight that whilst increasingly con-
sumers are shopping online it is not clear what drives them to shop in this way. They
suggest there are various factors including ease of use, enjoyment and consumer traits,
that will determine whether an individual will be an avid Internet shopper. So who are
the customers who shop online?
Who are the online customers?
Many researchers have written about which sectors of society use the Internet. Hoffman
and Novak (1998) focused on the impact of demographics, and highlight inequities of
Internet access based on race and gender. Sorce et al. (2005) looked at age and found
that ‘while older shoppers search for significantly fewer products than their younger
counterparts they actually purchase as much as the younger consumer’. More specifi-
cally, The National Statistics Office (UK) (2005) identified that people aged 25–44 were
most likely to buy online (63%), while people aged 65 and over were least likely to buy
online (41%). Mori (2005), the market research agency specialising in reporting on
public opinion has maintained a consistent interest in the technology sector. Mori
(2005) have been watching technology usage in general and, in particular, who is using
the Internet. This data highlights important trends that can help a retailer to develop a
deeper understanding of which technologies consumers might use to access the
e-retailer’s online offer (see Chapter 2 for further discussion).
Another variable to consider when identifying the online consumers is where do indi-
viduals access the Internet both in terms of the nature of the point of access and
Prices can be updated
in real time according
to the type of customer
or current market
Point of access – the nature of the location can be fixed or mobile and, say, be at home
or work. According to the National Statistics Office (2005), the most common place to
access the Internet was at home (88%), although 48% have accessed it at work, 29%
at another person’s home, 13% at a place of education and 10% at a public library.
The main means of access was via a desktop computer (85%) followed by a laptop
(28%) and mobile phone (22%). In Britain, in July 2005, over half of households
(approximately 12.9 million) could access the Internet from home, a trend which has
been increasing year on year.
Geographical location – there are varying levels of Internet penetration around the
globe (see Table 10.1 and Table 10.2 for various statistics). Asia now has the largest
number of Internet users, followed by the European Union (EU). Interestingly the
USA no longer has the highest density of users per head of population (see Table 10.2)
as in Sweden over 75% of the population are connected to the Internet. The size and
density of user populations vary considerably from country to country and a key
reason for this is the Internet infrastructure, which has not developed to the same
extent on a worldwide scale. In general, northern European countries have a higher
level of Internet penetration per head of population than southern European and
former Eastern bloc countries. Underdeveloped, highly populated nations tend to
have a comparatively low level of Internet penetration but more rapid growth rates
than compared with highly developed nations.
From an e-retailers perspective, digital technologies and the Internet create an opportu-
nity to cross barriers created by time and geography. However, it should also be
remembered that where people live has potential strategic and operational implications.
(This issue is discussed at the end of this chapter.)
CHAPTER 10 · BUSINESS-TO-CONSUMER INTERNET MARKETING
Table 10.1 World Internet users and population statistics (2005)
Population Internet usage, % Population Usage %
% of world
Oceania / Australia
Notes: (1) Internet usage and world population statistics were updated on November 21, 2005. (2) CLICK on each world region for detailed
regional information. (3) Demographic (Population) numbers are based on data contained in the world-gazetteer
web site. (4) Internet usage
information comes from data published by Nielsen//NetRatings
, by the Inter
, by local NICs, and by other
reliable sources. (5) For definitions, disclaimer, and navigation help, see the Site Sur
. (6) Information from this site may be cited,
giving due credit and establishing an active link back to www
. ©Copyright 2005, Miniwatts International, Ltd. All rights
It is important for an e-retailer to recognise the differences between on- and offline
target markets. Additionally, it should analyse and understand the differences in con-
sumer behaviour between these two channels. Knowledge of who the customers are can
give the e-retailer the opportunity to begin to analyse their needs (in an e-retailing con-
text) and then to formulate a plan as to how the company might serve the online
customers. Table 10.3 shows the potential impact of some consumer profile variables in
online markets. As in offline markets there is a wide range of profile variables that can be
used to identify and eventually segment online consumer markets.
Table 10.2 2 Internet Usage in the EU
Notes: (1) The EU Internet statistics were updated on November 21, 2005. (2) Detailed data for individual countries can be found by clicking
on each country name. (3) The demographic (population) numbers are based on data contained in world-gazetteer
. (4) The usage num-
bers come from various sources, mainly from data published by Nielsen//NetRatings
, local NICs and private sources. (5) Data
may be cited, giving due credit and establishing an active link to Inter
. (6) For definitions, see the site sur
©Copyright 2005, Miniwatts International, Ltd. All rights reserved.
© 2005, www.InternetWorldStats.com. All rights reserved
In summary, online shoppers can differ from offline shoppers in terms of profiles. Online
shoppers tend to be younger, wealthier, better educated, have higher ‘computer literacy’ and
more disposable income. However, perhaps as the Internet becomes a more mainstream
shopping channel the differences in consumer profiles will not be so marked as wider sectors
of the world at large are able to gain access to digital channels. The next part of this section
explores the expectations and motivations of online consumers (see also Activity 10.1).
CHAPTER 10 · BUSINESS-TO-CONSUMER INTERNET MARKETING
Table 10.3 3 Profile variables and the potential digital impact on target markets
Age can affect levels of access to technology, computer literacy, and
eventually, the extent to which individuals use the Internet as part of their
shopping routines. Age can also be linked to where people live and again
affect the potential size of the online market; for instance if selling goods and
services to China, the majority of online users are under 35.
Household size has the potential to affect the number of people involved in
purchasing decisions and the direction of influence. For example, research
has shown that in Europe children and teenagers can have a strong
influence on purchasing based on their levels of computing competency.
Household type has the potential to affect product and service requirements;
major shifts towards single person households in the UK (11% increase
since 1971 to 29%) has led to a shift in purchasing patterns and times of
purchasing. Online, such households can create logistical difficulties when
delivering bulky and perishable goods (see Mini Case Study 10.1 for further
Income affects primarily purchasing power, but also lifestyles and individual
expectations of quality and levels of service will vary.
Generally, Internet populations still have a slight male bias which potentially
affects the likelihood of being online and level of computing skills.
Ethnicity affects access to technology and economic circumstances.
Employment places time constraints on online shopping behaviour, i.e. when
and work patterns
individuals can access online shopping channels.
Mobility affects channel access; less mobile targets may be encouraged to
shop online. This also applies to macro-populations, which are poorly served
by public and private transport.
Whether on- or offline, consumers are individuals who buy products or services for personal consumption.
It is important to remember, there is not a straightforward answer to who buys: for instance some
purchases are based on individual impulses whilst others may involve a number of individuals who can
influence the final purchase choice. Blackwell et al. (2001) suggested there are five key roles that can
influence a purchase decision:
1 Initiator – starts the purchasing process
2 Influencer – tries to influence the final purchasing choice
3 Decider – has the authority to make the final choice
4 Buyer – conducts the transaction
5 User – enjoys the benefits of the purchase decision by using the product or service.
Mini Case Study 10.1
The online purchasing process
Online customers’ expectations and motivations
In the UK, over 50% of Internet users had shopped online by the end of 2004 and this is
a trend predicted to continue to grow in terms of numbers of consumers and the
amount they spend (Allegra, 2005). However, it has been suggested that too many com-
panies are failing to realise the potential of this new digital trading environment and are
tending to adopt defensive strategies, taking the lead from their nearest competitors as
to what the organisation should be offering online rather than capitalising on the
potential provided by digital channels (Allegra, 2005). E-retailers should aim to under-
stand how customer expectations have been raised. Key areas where customers have
high expectations of online retailers are the following:
Logistics – the critical link between consumer-based Internet ordering and the delivery
of the product to the consumer is often referred to as the final or last mile. The last
mile, including product transportation, is frequently considered the most important
element of the order fulfilment process, i.e. 89% of online shoppers rate on-time
delivery high in importance and 85% of buyers who receive their order on time
would shop at the Internet merchant again. Thus, delivery-related issues have been
shown to have a high level of importance to online shoppers (Esper et al., 2003).
Security and privacy of information – customers now expect that if they are prepared to
provide detailed personal and financial information it will be stored securely.
In an online purchasing situation, the initiator, decider and user roles remain similar to those in an offline
purchasing situation but research has shown that the influencer and the buyer can be significantly changed
(e.g. the influencer/buyer is likely to be a younger member of the household; children and teenagers who
are playing an increasingly influential role in online purchasing decisions). Furthermore, they are very likely
to be those persons who actually conduct the online transaction. This is important for the digital marketing
managers as they need to consider how to tailor their web site content and search marketing strategy in
order to communicate with this relatively new type of influencer. Increasingly, younger influencers are enjoy-
ing more power in the online purchasing situation. E-tailers (see e-retailing section) are increasingly using
web sites to support the purchasing decision by providing information at the evaluation stage of the buying
process and also to avert post-purchase dissonance through sophisticated after-sales support online.
‘Going shopping online’
Select a product or service of your choice that you are about to or would like to be able to
purchase. Visit as many web sites as required until you find a product or service that could
meet your needs (see Figure 10.1, for example).
Using your online shopping experience identify:
1 The problem you were seeking to solve
2 The extent of your information searching
3 The choice criteria which informed your decision making
4 The purchase solution (your preferred product or service)
5 Evaluate the web sites you have visited in terms of how easy it was to find the information
you needed to make your purchasing decision.
CHAPTER 10 · BUSINESS-TO-CONSUMER INTERNET MARKETING
Figure 10.1 Thinking of buying a book? Examples of online book retailers
Timeliness – the speed of digital communications has raised customer expectations in
terms of response times and they expect a speedy shopping experience. It is no longer
acceptable to take three or four days to respond to an online customer enquiry; an
online customer expects the response will be instantaneous or at least within a couple
of hours. Additionally, they expect to be able to order goods and services at any time.
Availability – the Internet creates a sales environment, which is not restricted by space
constraints, therefore there is an increased expectation that not only will there be a
wider range of goods for sale online but also the goods will be readily available for
Convenience – it should be easier and quicker to compare prices online; there should
be easy access to a wide range of retailers without the inconvenience of having to
travel to a number of different locations.
Customer service – customer value is the foremost driver of competitive advantage in
the Internet shopping environment and customer service can be measured by the
consumer in terms of price savings, service excellence, time savings and experiential
values such as entertainment, visual stimulation/reward, levels of interaction. Positive
response to such factors can lead to heightened loyalty (Lee and Overby, 2004).
The increase in customer expectations can have quite wide-reaching organisational
implications. The gap between customer expectations of the online offer and the actual
performance can have a significant impact on online performance. Mini Case Study 10.2
explores the relationship between experiences and online success. Following your read-
ing of this case study, you can go on to try Activity 10.2.
There has been a great deal of academic research looking at the relationship between quality and online
success in consumer markets. Wolfinbarger and Gilly (2003) used the premise that quality is related to
customer satisfaction and retention in both product and service settings as a basis for their work. In
doing so they established the dimensions of etailing and developed a scale for the measurement of etail
quality (eTailQ). They identified four key factors, which they found to affect levels of online customer sat-
isfaction, and these in rank order are:
1 Web site design:
(a) Easy navigation
(b) Appropriate levels of information
(c) Effective information search facility
(d) Straightforward ordering
(e) Appropriate personalisation
(f) Appropriate product selection
(a) Accurate display aimed at ensuring alignment between customer expectations and realisation
(b) Delivery of the right product within promised time frame
3 Customer service:
(a) Responsiveness to enquiries
(c) Willing service
(d) Immediacy of response
(a) Secure payment facilities
(b) Secure and private personal information.
Mini Case Study 10.2
In addition to consumer expectations there are several other key concepts that have
been widely cited as affecting online purchasing behaviour. These are perceived risk and
trust, and loyalty.
Perceived risk and trust
Literature suggests the online trading arena is intrinsically different from any other
channel to market and in essence is an unfamiliar environment (Rutter, 2001). Online
consumers are buying into a trading situation that is inherently laden with uncertainty,
lack of cues to reinforce trusting relationships and risk. Risk and trust are multi-dimen-
sional constructs and have been found to improve online sales effectiveness if perceived
risk is reduced and trust established.
Perceived risk conceptualised by Bauer (1960) consists of six components:
1 financial risk
2 product performance risk
3 social risk
4 psychological risk
5 physical risk
6 time/convenience loss.
CHAPTER 10 · BUSINESS-TO-CONSUMER INTERNET MARKETING
Design a web site
Design an e-retail web site for a specialist retailer serving a niche market, for example a
specialist health product retailer (see Figure 10.2). Use the four key factors identified by
Wolfinbarger and Gilly (2003) to guide your design. Remember to consider:
1 Who are the online customers?
2 What are the online customer expectations?
3 How can the web site deliver online customer satisfaction?
Figure 10.2 Simply Vital example of specialist company,
which is using the Internet as a channel to market
Willingness to purchase is considered to be inversely affected by perceived risk. Stone
and Gronhaug (1993) state that ‘risk is the subjective expectation of a loss’.
Closely associated with risk is trust as it is a potential outcome of risk reduction. Trust
needs to be increased and perceived risk decreased if e-retailers are to engender positive
belief in the organisation’s online reputation. Dimensions of trust include: service
provider expertise, product performance, firm reputations, satisfaction (with past inter-
actions) and similarity. It should be noted that some researchers have suggested that not
all online customers respond in the same manner. Newholm et al. (2004) conclude that
e-retailers should adopt a differential approach to building trust and raise the point that
types of customers and products can significantly affect how retailers should develop
approaches for handling risk and trust. Indeed ‘bargain hunters’ are inherently risk
takers and in this case it becomes the propensity to engage in risk taking, rather than
being risk averse, which drives the consumer behaviour.
The risk seeking element of online purchasing behaviour possibly begins to explain
the success of the online auction platform eBay. Online auctions have seen a massive
upsurge in the number of sales of second-hand goods, which are traded between
unknown buyers and sellers. Each party has limited knowledge of the other’s past trad-
ing performance, the levels of service quality or the condition of the goods and/or
services on offer and yet millions of buyers are willing to gamble large sums of money in
pursuit of goods. The high level of purchasing activity has not gone unnoticed by retail-
ers as many now offer goods for sale within the eBay platform.
Perhaps the key question for the e-retailer to consider is what levels of trust and per-
ceived risk are required for a selected target audience, which will actually encourage
buyers to purchase in an online trading environment. Whatever the level there is perhaps
an even more fundamental implication, which is how to incorporate the excitement of
the unknown into the online offer.
Online customer loyalty has also been well researched. Srinivasan et al. (2002) identified
several variables as being unique to online consumer markets (see Table 10.4). The vari-
Customisation – tailored content;
Contact interactivity – dynamic nature of the buyer/seller relationship;
Cultivation – relevance of online content;
Care – attention retail pays to consumer buying behaviour;
Community – online interaction amongst purchasing community;
Choice – expectation of greater choice online;
Convenience – perceived comparative advantage of online shopping;
Character – web site design.
This section has considered the online consumer by looking at some of the variables
that can be used to identify and develop an understanding of the individuals who shop
online. Moreover, it has looked at customer expectations and the key factors that are
likely to affect online purchasing behaviour: risk, trust and loyalty. The next section
focuses on e-retailing and looks at how companies are attempting to meet the needs of
the online consumer.
Suggest how each of these variables might be realised in a transactional retail web site.
Documents you may be interested
Documents you may be interested