In this Section our focus is in a customer and user. An essential part in the product development and in usability engineering is to understand, who are the customers, and hence who should be involved in the usability testing activities as test persons.
Today, everyone is a potential mobile phone customer. As the market has become increasingly segmented, the ability to master various product categories has become crucially important. In a segmented consumer market with high volumes, critical success factors include comprehensive product portfolio, a strong and appealing brand as well as efficient global logistics (Nokia 1998)
Different user categorizations are being used for different purposes. The three dominant ways to group users are:
1. Categorization based on expertise: novice, casual, and expert users.
2. Categorization based on product buying or adopting behaviour: Early and late adopters
3. Categorization based on segmentation, especially lifestyle segmentation
Anybody can be a mobile phone user, independently of the age, sex, culture, physical disabilities, economic background, consumer behaviour or any other identified factor. This is a challenge for usability engineering, because one of the main activities in the early development is to know the user (for example, Nielsen 1993). How can we know or satisfy anybody? Design- for-all seems to be more useful guideline than design for specific users. Nevertheless, Cooper (1999, 124) claims that better results can be achieved by designing for identified single persons instead of “anybody” or large audience.
When the users are selected to participate in product development as test persons, it should be considered what user characteristics potentially provide useful information in the specific situation. Most often user testing is performed with users that are novice with the new system but may have previous experience of the task. Hence, usability tests tend to test instant usability11 of the system. During the test sessions users learn and become, more or less, casual users of the system. However, expert users are rare. Along the development of innovative functions, the real challenge in human-centred design is to find expert users for product testing.
A system can be instantly usable or it may require learning. Grossman et al. (1992) propose the following categories for system learning:
- intuitive. The system is immediately usable, walk-up-and-use.
- discoverable. User can learn to use the system without need for external help, such as manuals.
- learnable. Manual or training is needed before the system can be used.
5.6.1 Novice, Casual, and Expert user
The most applied user categorization defines novice, casual and expert users (Nielsen, 1994) which predicts learning. This categorization describes user's experience with the specific user interface, knowledge of the task domain, and experiences about computers in general. A novice user has no (or only minimal) experience with the task domain and the system. A casual user is a person who is using the system intermittently rather than having the frequent use that an expert user has. The three dimensions can be organised as in Figure 5.6.
Nielsen (p. 28) shows that learning curves are different for novice and expert users. A system that focuses on the novice user is typically easy to learn but less efficient to use. A system that focuses on expert users is hard to learn but more efficient to use. The learning curve can be criticized with two arguments:
1. The learning process from novice to expert is not linear activity, but rather curvilineal activity.
2. Experience and knowledge are not synonyms. Experience and knowledge do not guarantee that a user is an expert user in a specific task.
11 Also known as “walk-up-and-use usability” in HCI.
Ignorant about domain Novice user of
system
Expert user of system Knowledgeable about
domain
Minimal computer experience
Extensive computer experience
Figure 5.6. The three experience dimensions (computer experience, system experience, task domain expertice) (Nielsen, 1994).
For mobile phone interaction, I define a novice user to be a person who hasn't used a mobile phone or has limited experience with it. For example, a novice user may not have made or received a phone call with a mobile phone. A casual mobile phone user may own a mobile phone, using occasionally some basic functions of the phone, for example the built-in Phonebook. His lifestyle is not based on the use of a mobile phone. An expert user has his mobile phone always with him and he uses different functions fluently and often. An expert user has previous experience of mobile phones.
The larger factors that are forming the novice-expert categorization are:
- knowledge about mobile communication (context) - experience about mobile communication (time) - personal use of mobile phone (use frequency)
Nielsen's experience dimensions can be applied for mobile phone use by having the mobile phone as system, and mobile communication as domain and state of knowledge (Figure 5.7).
Ignorant about mobile communication Novice user
of mobile phone
Expert user of mobile phone Knowledgeable
about mobile communication
Minimal mobile communication experience
Extensive mobile communication
experience
Figure 5.7. The three experience dimensions for mobile phone use.
5.6.2 Early adopters and late adopters
Norman (1998, 31-36) reviews market adaptation for a product through technology centred customers and consumer-centred customers, also known as early adopters and late adopters.
This categorization can be used to predict buying behaviour and technology adoption.
In the early days of technology, some people will buy a product because of the functions it offers. These customers are called early adopters. The buying decision is primarily based on the function lists and technological claims on advertisements. Early adopters are willing to suffer inconvenience and high cost to get the technology. Late adopters, more conservative customers, wait until the technology is reliable, cheaper, convenient, and provides better performance.
Rogers (1995) discussed the extended concept of early and later adopters. He presents the categorization of adopters: innovators, early adopters, early majority, late majority, and laggards, each playing a different role in the development of technology. He showed that innovation spread slowly, with early adopters being different kinds of people than late adopters.
Norman proposes that it is not enough to change the marketing for different adopters, but the entire product must change (Norman 1998, 274). In the early days of a technology or product, the innovators and technology enthusiasts drive the market. In the later days, the pragmatists and conservatives dominate with the need for convenience and solutions. The innovators and early adopters are only a small percentage of the market. The big market is with the pragmatists and the conservatives (Figure 5.8).
Early Customers technology and performance Innovators,
technology enthusiasts
Early adopters
visionaries Early majority pragmatists
Late majority conservatives
Laggards skeptics Relative
% of customers
Time Late
Customers solutions
and convenience Transition point
where technology satisfies
basic needs
Figure 5.8. The change in customers as a technology matures and the change from technology- driven products to customer-driven, human centred products.
5.6.3 User segments and lifestyle segmentation
Winograd (1995) recognized three phases of computer product development: Technology- driven, productivity-driven and appeal-driven. Many current consumer products can be seen clearly appeal-driven rather than technology- or productivity-driven. For example, digital watches are not often sold based on the technology or functions of the product, but the product marketing tries to approach different consumer segments by emphasizing, for example, quality, trends, price, brand, lifestyle, emotions or personalization. Also mobile phone industry has entered appeal-driven product development, where the products are developed and marketed to consumer segments.
Segmentation is the process of partitioning markets into groups of potential customers with similar needs and/or characteristics who are likely to exhibit similar purchase behavior (Weinstein 1994, 2).
Classification of users and potential customers can be based on buying behaviour and lifestyle.
As in many technology areas, emotions and feelings are becoming arguments for selling and buying, and as drivers for developing better user interfaces (Nokia 2000b, Keinonen 2000) because the relationship between a user and a mobile phone often contains a lot of emotion and personality, maybe even more than the relationship of the user and a PC (Kopomaa 2000).
Korhonen (2000) discusses strategic design where the design is explicitly started from a specific user group, or segment, and the product concept is developed to meet the needs of this group.
Mobile phone industry is developing products for different consumer segments. Marketing literature defines central variables for segmentation (Kotler 1997, Weinstein 1994):
- demographic: age, gender, occupation, income, education, family size - geographic: region, city/metro size, density, climate
- psychographics: lifestyle, personality
- behaviour: benefits, user status, usage rate, occasions - socio-economic: income levels, social class
- product usage: consumption levels, for example, heavy, medium, light, non-users - benefits: what factors weigh in selecting a product
It is relatively easy to collect and use segmentation knowledge (demographic, geographic and behavioural) about customers using typical market research methods. In the real life, customers follow identifiable lifestyles and trends that change along the time.
In the competition, manufacturers and vendors have found it important to gain more specific information and understanding than segmentation knowledge on user populations and trends in order to enable lifestyle segmentation. In lifestyle segmentation, detailed or deep knowledge is needed about user's real-life usage patterns. Lifestyle segmentation, through listening, understanding and satisfying market needs, is the objective of Nokia's product development and market strategy (Steinbock 2001, 268). In the beginning of 1990s, Nokia developed the first lifestyle segmentation of its target customers. The four most important segments were "posers",
"trendsetters", "social contact seekers", and "high-fliers".
People think, act, and are active makers of their physical and social reality. Interpretive researchers claim that relationships between people, organisations and technology are not fixed but constantly changing (Klein and Myers 1999). Hence, people and knowledge about people changes in the long run, in contrast to knowledge about material and data. For example, a mobile phone has potential to change a person's communication pattern, even lifestyle and communication culture of larger groups (Kasesniemi 2001, 77). Social learning theory (Bandura 1986) shows that people learn new attitudes and behaviours by observing others' actions and the consequences of their actions. Hence, the lifestyle segmentation based knowledge, especially in the fast developing area of mobile communication, expires fast and requires constant updating.