A Model Of Consumer Behavior Online

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18/05/17 Marketing Reference this

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Del Monte operates in a very competitive global food industry. In addition to manufacturing canned fruits and vegetables for human consumption, Del Monte produces pet food such as Gravy Train, 9 Lives, and Meow Mix. Therefore, using market research the company constantly looks for innovative ways to increase its competitive edge. The company also decided to implement social media. Once Del Monte made the decision to deploy social media projects, the company had to decide how best to use social media research to support its diverse product line-in this case dog food.

The Solution

The basic idea was first to connect and collaborate with dog lovers via social networks. Since the corporate IT department was not equipped to deal with social network research, Del Monte hired Market Tools Inc., a market research firm.

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With the help of Market Tools Inc., Del Monte began offering an online platform for customers to chat and comment on blog entries about different Del Monte products. Using their propriety software, Market Tools monitors millions of relevant blogs in the blogsphere as well as forums in social networks, in order to identify key ideas and issues that consumers are interested in, analyze them, and then predict consumer behavior trends. To analyze the collected data, Del Monte teamed up with Umbria (a division of J. D. Power and Associates), a pioneer in drawing market intelligence from the online community. Umbria assisted in further analysis of and in profiling the collected information. Such analysis is usually done by using computerized tools such as monitoring consumer interactions, analyzing consumers’ sentiments, and using social analytics methods (e.g., see Hedin, et al. 2011 and Jayanti 2010). By utilizing social media, Del Monte can conduct market research much more efficiently. The conventional approach was to use questionnaires or focus groups that were expensive and difficult to fill with qualified participants. Using social media, Del Monte can gather much of the same or more qualitative data faster and at a lower price. All that is required now is to monitor customer conversations, collect the data, and analyze the vast amount of information. The software also facilitates subgroup creation, idea generation, and panel creation. The results of the analysis help Del Monte understand its customers and consequently plan its marketing activities, communication strategies, and customer service applications. The results also help evaluate the success of marketing campaigns, how well the business processes accomplished the goals, and better justify proposed new activities.

The Experiment

Del Monte used the above application first to help improve its dog treat, Snausages Breakfast Bites. For guidance, Del Monte relied on its dog lover’s social community. By monitoring customer blogs and by posting questions to customers to stimulate discussions, Del Monte used text analysis methods to investigate the relationship between dogs and their owners. Del Monte concluded that owners of small dogs would be the major purchasers of Snausages Breakfast Bites. The company also found differences due to the age of owners, and discovered other people-dogs relationships. Next, a small sample of the improved dog food was produced and tested in the physical market. As a result of both social media and physical research, the product design decisions were revised. Also, marketing promotions were modified. The product sells better because the dogs love it. Finally, the new approach solidified the community of dog lovers who are happy that their opinions are considered.

The Results

Product cycle time was reduced by more than 50 percent to only 6 months, and Del Monte was able to develop a better marketing communication strategy. Furthermore, the analysis helped the company better understand customers and their purchasing activities as well as predicting market trends and identifying and anticipating opportunities.

Note: Similar research on cat food was conducted in 2012 in an online survey, by Kelton Research, using e-mail invitation and an online survey. For details see Meow Mix (2012).

Sources: Compiled from Steel (2008), Greengard (2008), Hedin et al. (2011), Jayanti (2010), Meow Mix (2012), Wikivest (2012), and Market Tools (2008).

What we can learn…

The opening case illustrates that market research can be useful in a competitive market by providing insights for better product development and marketing strategy. In this case, the company collected data online from its socially-oriented customers. Market Tools Inc. monitored conversations (over 50 millions of them) on blogs and discussion rooms to find the “voice of the customers.” The collected data were then analyzed. The results of the analysis helped Del Monte improve its dog food and devise new marketing strategies. Market research, as seen in the case, is related to consumer behavior, purchasing decision making, behavioral marketing, and advertising strategies; all these topics are addressed in this chapter.

9.1 Learning About Consumer Behavior Online

Companies are operating in an increasingly competitive environment. Therefore, they please customers and influence them to buy their goods and services. Finding and retaining customers are major critical success factors for most businesses, both offline and online. One of the key elements in building effective customer relationships is an understanding of consumer shopping behavior online.

A Model of Consumer Behavior Online

For decades, market researchers have tried to understand consumer shopping behavior, and have summarized their findings in various models. The purpose of a consumer behavior model is to help vendors understand how a consumer makes a purchasing decision. If a firm understands the decision process, it may be able to better influence the buyer’s decision, for example, through advertising or special promotions.

Before examining the consumer behavior model’s variables, let’s describe who the EC consumers are. Online consumers can be divided into two types: individual consumers (who get much of the media attention) and organizational buyers, who do most of the actual shopping in cyberspace in terms of dollar volume of sales. Organizational buyers include governments, private corporations, resellers, and nonprofit organizations. Purchases by organizational buyers are generally used to add value to materials or products. Also, organizational buyers may purchase products for resale without any further modifications. We discuss organizational purchasing in detail in Chapter 5 (e-procurement) and will focus on individual consumers in this chapter.

The purpose of a consumer behavior model (for individuals) is to show factors that affect consumer behavior. Exhibit 9.1 shows the basic elements of a consumer behavior model. The model is composed of two major parts: influential factors and the consumer decision process.

[Insert Exhibit 9.1 here]

ƒ˜ Influential factors. Five dimensions are considered to affect consumer behavior. They are consumer characteristics, environmental characteristics, merchant and intermediary characteristics (which are at the top of the exhibit and are considered uncontrollable from the seller’s point of view), product/service characteristics (which include market stimuli), and EC systems. The last two are mostly controlled by the sellers. Exhibit 9.1 illustrates the major variables in each influential dimension. A more detailed description is provided in Online File W9.1.

ƒ˜ The attitude-behavior decision process. The consumer decision process usually starts with a positive attitude and ends with the buyer’s’ decision to purchase and/or repurchase. A favorable attitude would lead to a stronger buying intention, which in turn would result in the actual buying behavior. Previous research has shown that the linkages among the previously mentioned three constructs are quite strong. For example, Ranganathan and Jha (2007) found that past online shopping experiences have the strongest associations with online purchase intention, followed by customer concerns, website quality, and computer self-efficacy. Therefore, developing a positive consumer attitude plays a central role in the final purchase decision.

The Major Influential Factors

These factors fall into the following categories:

Personal characteristics. Personal characteristics, which are shown in the top-left portion of Exhibit 9.1, refer to demographic factors, individual preferences, and behavioral characteristics. Several websites provide information on customer buying habits online (e.g., emarketer.com, clickz.com, and comscore.com). The major demographics that such sites track are gender, age, marital status, educational level, ethnicity, occupation, and household income, which can be correlated with Internet usage and EC data. Males and females have been found to perceive information differently depending on their levels of purchase confidence and internal knowledge (Barber et al. 2009). A recent survey by Crespo and Bosque (2010) shows that shopping experience has a significant effect on consumer attitude and intention to purchase online.

Psychological variables such as personality and lifestyle characteristics are also studied by marketers. These variables are briefly mentioned in several places throughout the text. The reader who is interested in the impact of lifestyle differences on online shopping may see Wang et al. (2006).

Product/service factors. The second group of factors is related to the product/service itself. Whether a consumer decides to buy is affected by the nature of the product/service in the transaction. These may include the price, quality, design, brand, and other related attributes of the product.

Merchant and intermediary factors. Online transactions may also be affected by the merchant that provides the product/service. This group of factors includes merchant reputation, size of transaction, trust in the merchant, and so on. For example, people feel more secure when they purchase from Amazon.com (due to its reputation) than from a no-name seller. Other factors such as marketing strategy and advertising can also play a major role.

EC systems. The EC platform for online transactions (e.g., security protection, payment mechanism, and so forth) offered by the merchant may also have effects. EC design factors can be divided into motivational and hygiene factors. Motivational factors were found to be more important than hygiene factors in attracting online customers (Liang and Lai 2002). Perceived usability is highly related to user preference for commercial websites (Lee and Koubek 2010).

Motivational factors. Motivational factors are the functions available on the website to provide direct support in the transactional process (e.g., search engine, shopping carts, multiple payment methods).

Hygiene factors. Hygiene factors are functions available on the website whose main purpose is to prevent possible trouble in the process (e.g., security and product status tracking).

Environmental factors. The environment in which a transaction occurs may affect a consumer’s purchase decision. As shown in Exhibit 8.1, environmental variables can be grouped into the following categories:

Social variables. People are influenced by family members, friends, coworkers, and “what’s in fashion this year.” Therefore, social variables (such as customer endorsement, word-of-mouth) play an important role in EC. Of special importance in EC are Internet communities (see Chapter 7) and discussion groups, in which people communicate via chat rooms, electronic bulletin boards, twitting, and newsgroups. These topics are discussed in various places in the text.

Cultural/community variables. It makes a big difference in what people buy if a consumer lives near Silicon Valley in California or in the mountains in Nepal. Chinese shoppers may differ from French shoppers, and rural shoppers may differ from urban ones.

Other environmental variables. These include aspects such as available information, government regulations, legal constraints, and situational factors.

[Comp: please shade the bullet list]

Section 9.1 Ÿ Review Questions

1. Describe the major components and structure of the consumer online purchasing behavior model.

2. List some major personal characteristics that influence consumer behavior.

3. List the major environmental variables of the purchasing environment.

4. List and describe five major merchant-related variables.

5. Describe the relationships among attitude, intention, and actual behavior in the behavior process model.

9.2 The Consumer Purchasing Decision-Making Process

Consumer behavior is a major element in the process of consumers’ decisions to purchase or

repurchase.

A Generic Purchasing-Decision Model

From the consumer’s perspective, a general purchasing-decision model consists of five major phases (Hawkins and Mothersbaugh 2010). In each phase, we can distinguish several activities and, in some, one or more decisions. The five phases are (1) need identification, (2) information search, (3) evaluation of alternatives, (4) purchase and delivery, and (5) postpurchase activities. Although these phases offer a general guide to the consumer decision-making process, one should not assume that every consumer’s decision-making process will necessarily proceed in this order. In fact, some consumers may proceed to a specific phase and then revert to a previous phase, or they may skip a phase altogether. The phases are discussed in more details next.

• Need identification. The first phase occurs when a consumer is faced with an imbalance between the actual and the desired states of a need. A marketer’s goal is to get the consumer to recognize such imbalance and then convince the consumer that the product or service the seller offers will fill this gap.

• Information search. After identifying the need, the consumer searches for information on the various alternatives available to satisfy the need. Here, we differentiate between two decisions: what product to buy (product brokering) and from whom to buy it (merchant brokering). These two decisions can be separate or combined. In the consumer’s search for information, catalogs, advertising, promotions, and reference groups could influence decision making. During this phase, online product search and comparison engines, see examples at shopping.com, buyersindex.com, and mysimon.com, can be very helpful. (See decision aids in Chapter 3.)

• Evaluation of Alternatives. The consumer’s information search will eventually generate a smaller set of preferred alternatives. From this set, the would-be buyer will further evaluate the alternatives and, if possible, negotiate terms. In this phase, a consumer will use the collected information to develop a set of criteria. These criteria will help the consumer evaluate and compare alternatives. For online consumers, the activities may include evaluation of product prices and features.

• Purchase and delivery. After evaluating the alternatives, the consumer will make the purchasing decision, arrange payment and delivery, purchase warranties, and so on.

• Postpurchase activities. The final phase is a postpurchase phase, which consists of customer service and evaluation of the usefulness of the product. Customer services and consumer satisfaction will result in positive experience and word-of-mouth (e.g., “This product is really great!” or “We really received good service when we had problems.”). If the customer is satisfied with the product and services, loyalty will increase and repeat purchases will occur afterward.

[Comp: please shade the bullet list]

Several other purchasing-decision models have been proposed. A classic (1925) model for describing consumer message processing is the Attention-Interest-Desire-Action (AIDA) model at Wikipedia (see ‘AIDA’ at Wikipedia). It argues that consumer processing of an advertising message (part of the information search phase) includes the following four stages:

1. A-Attention (Awareness). The first step is to get the customers’ attention.

2. I-Interest. By demonstrating features, advantages, and benefits, the customer becomes interested in the product.

3. D-Desire. Convice the customers that they want the product or service and that it will suit their needs.

4. A-Action. Finally, the consumer will take action toward purchasing.

Now, some researchers also add another letter to form AIDA(S), where:

5. S-Satisfaction. Customer satisfaction will generate higher loyalty and lead to repurchase after using a product/service. (Loyalty, satisfaction, and trust are discussed in Online File W9.2.)

A recent version of AIDA is the AISAS model proposed by the Dentsu Group that is tailored to online behavior. The model replaces “decision” with “search” and adds “share” to show the increased word-of-mouth effect on the Internet. It indicates that consumers go through a process of Attention-Interest-Search-Action-Share in their online decision process. This model is particularly suitable for social commerce.

Customer Decision Support in Web Purchasing

The preceding generic purchasing-decision model was widely used in research on consumer-based EC. In the Web-based environment, decision support is available in each phase. The framework that is illustrated in Online File W9.3 shows that each of the phases of the purchasing model, which were described earlier, can be supported by both a consumer decision support system (CDSS) that facilitates the process and Internet and Web-aiding facilities. The CDSS facilities support the specific decisions in the process. Generic EC technologies and analytics provide the necessary mechanisms as well as enhanced communication and collaboration tools. Specific implementation of this framework and explanations of some of the terms are provided throughout this chapter and the entire text.

The planner of B2C marketing needs to consider the Web purchasing models in order to better influence the customer’s decision-making process (e.g., by effective one-to-one advertising and marketing).

[Insert Exhibit 9.2 here]

Online File W9.1 shows a model for a website that supports buyer searching and decision making. This model revises the generic model by describing a purchasing framework. The model is divided into three parts. The first includes three stages of buyer behavior (see top of exhibit): identify and manage buying criteria, search for products and merchants, and compare alternatives. Below these activities are boxes with decision support options that support the three top boxes (such as product representation)..

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The second part of the model (on the right) has a box that includes price, financial terms, shipping and warranty negotiations. These become relevant when alternatives are compared. The third part at the bottom of the exhibit, major concerns are cited.

Players in the Consumer Decision Process

Several different people may play roles in various phases of the consumer decision process. The following are five major roles:

1. Initiator. The person who first suggests or thinks of the idea of buying a particular product or service.

2. Influencer. A person whose advice or view carries some weight in making a final purchasing decision.

3. Decider. The person who ultimately makes a buying decision or any part of it-whether to buy, what to buy, how to buy, or where to buy.

4. Buyer. The person who makes an actual purchase.

5. User. The person who consumes or uses a product or service.

[Comp: please shade the number list]

A single person may play all the roles if the product or service is for personal use. In this case, the marketer needs to understand and target such individuals. In many situations, however, different people may play different roles. For example, a newly graduated engineer proposed to buy a car for his mother, which was followed by suggestions from his father and friends. Finally, he followed his father’s suggestion to buy the car. When more than one individual comes into play, it becomes more difficult to properly target advertising and marketing. Different marketing efforts may be designed to target people who are playing different roles.

Section 9.2 Ÿ Review Questions

1. List the five phases of the generic purchasing-decision model.

2. Use an example to explain the five phases in the generic purchasing-decision model.

3. Describe the supporting functions available in Web-based purchasing.

4. Describe AIDA and AISAS models and analyze their differences in illustrating an online purchasing behavior.

5. Describe the major players in a purchasing decision.

9.3 LOYALTY, SATISFACTION, AND TRUST IN E-COMMERCE

Good online marketing activity can generate positive effects, which are generally observed as trust, customer satisfaction, and loyalty. Loyalty is the goal of marketing, while trust and customer satisfaction are factors that may affect customer loyalty.

CUSTOMER LOYALTY

One of the major objectives of marketing is to increase customer loyalty (recall the Netflix case). Customer loyalty refers to a deep commitment to repurchase or repatronize a preferred product/service continually in the future, thereby causing repetitive same-brand or same brand-set purchasing, despite situational influences and marketing efforts that have the potential to cause switching behavior. Customer acquisition and retention is a critical success factor in e-tailing. The expense of acquiring a new customer can be more than $100; even for Amazon.com, which has a huge reach, it is more than $15. In contrast, the cost of maintaining an existing customer at Amazon.com is $2 to $4.

Attracting and retaining loyal customers remains the most important issue for any selling company, including e-tailers. Increased customer loyalty can result in cost savings to a company in various ways: lower marketing and advertising costs, lower transaction costs, lower customer turnover expenses, lower failure costs such as warranty claims, and so on. Customer loyalty also strengthens a company’s market position because loyal customers are kept away from the competition. In addition, customer loyalty can lead to high resistance to competitors, a decrease in price sensitivity, and an increase in favorable word of mouth.

Loyalty programs were introduced more than 100 years ago and are widely used among airlines, retailers, hotel chains, banks, casinos, car rentals, restaurants, and credit card companies. But now, loyalty programs have been computerized and expanded to all kinds of businesses. For example, Octopus Hong Kong (octopuscards.com), a stored-value card operator, launched a reward program for consumers aimed at increasing card usage across Hong Kong. Reward points are gained by purchasing at a number of leading merchants across the territory, including Wellcome, Watsons, UA Cinemas, and McDonald’s. Each Octopus card can store up to 1,000 rewards points, which can be redeemed on the next purchase. FANCL, see the company atfancl.com, a Japanese cosmetics and health-care company, offers the “FANCL point program” where consumers earn FANCL points that are saved for gift redemption.

However, the introduction of Internet technologies and social networking has the potential to undermine brands and discourage customer loyalty. The customers’ ability to shop, compare, get quick advice from friends, and switch to different vendors becomes easier, faster, and less expensive, given the aid of search engines and other technologies. Furthermore, customers are less loyal to the brand because of the lower switching costs for them to take advantage of special online offers and promotions, as well as to try new things.

It is interesting to note that companies have found that loyal customers end up buying more when they have an optional website from which to shop. For example, W.W. Grainger, a large industrial-supply company, found that loyal B2B customers increased their purchases substantially when they began using Grainger’s website (grainger.com). (See Chapter 4 for more information.) Also, loyal customers may refer other customers to a site, especially with word of mouth in social networks. Therefore, it is important for EC companies to increase customer loyalty. The Web offers ample opportunities to do so.

E-Loyalty

E-loyalty refers to a customer’s loyalty to an e-tailer or a manufacturer that sells directly online, or to loyalty programs delivered online or supported electronically. Companies can foster e-loyalty by learning about their customers’ needs, interacting with customers, and providing superb customer service. Another source of information is colloquy.com, which concentrates on loyalty marketing.

In an online environment, merchant ratings can be the source of interpersonal communication and are obtained from other consumers, not just friends and family. It is interesting to note that positive customer reviews have considerable impact on repurchase intention. It is not the total number of reviews that influences customer repurchase intention, but the percentage of positive reviews. This increases e-loyalty. (For reviews and recommendations in social networks, see Chapter 7.)

Also, online ratings and word of mouth may undermine the effects of competitors’ low prices. For example, Amazon.com has higher prices than Half.com, but Amazon.com is still preferred by many customers. The difference is that Amazon.com has customer reviews and other personalization services, and Half.com does not.

Many factors may affect customer loyalty and e-loyalty. A typical model is to check the relationship quality between retailers and their customers, which often is composed of trust, satisfaction, and commitment. Satisfaction and trust are particularly important because they will lead to commitment. For example, a recent study by Cyr (2008) found that e-loyalty is affected by trust and satisfaction across different cultures. Hence, we shall further discuss these two factors.

SATISFACTION IN EC

Satisfaction is one of the most important success measures in the B2C online environment. Customer satisfaction is associated with several key outcomes (e.g., repeat purchase, positive word of mouth, and so on) and it can lead to higher customer loyalty. A survey indicates that 80 percent of highly satisfied online consumers would shop again within two months, and 90 percent would recommend Internet retailers to others. However, 87 percent of dissatisfied consumers would permanently leave their Internet retailers without any complaints (Cheung and Lee 2005).

Satisfaction has received considerable attention in studies of consumer-based EC. For example, ForeSee Results, an online customer satisfaction measurement company, developed the American Customer Satisfaction Index (ACSI) (theasci.org) for measuring customer satisfaction with EC. The Customer Respect Group (customerrespect.com) also provides an index to measure customers’ online experiences. The Customer Respect Index (CRI) includes the following components: simplicity, responsiveness, transparency, principles, attitude, and privacy.

Researchers have proposed several models to explain the formation of satisfaction with online shopping. For example, Cheung and Lee (2005) proposed a framework for consumer satisfaction with Internet shopping by correlating the end-user satisfaction perspective with the service quality viewpoint. The framework is shown in Exhibit 9.3.

The ability to predict consumer satisfaction can be useful in designing websites as well as advertising and marketing strategies. However, website designers should also pay attention to the nature of website features including navigational, visual, and information design (Cyr 2008). Different features have different impacts on customer (dis)satisfaction. If certain website features, such as reliability of content, loading speed, and usefulness fail to perform properly, customer satisfaction will drop dramatically. In contrast, if features such as those make the usage enjoyable, entertaining, and useful, they could result in a significant jump in customer satisfaction.

[Insert Exhibit 9.3 here] Factors that Affect Consumer Satisfaction with Internet Shopping

TRUST IN EC

Trust is the psychological status of depending on another person or organization to achieve a planned goal. When people trust each other, they have confidence that their transaction partners will keep their promises. However, both parties in a transaction assume some risk. In the electronic marketplace, sellers and buyers do not meet face to face. The buyer can see a picture of the product but not the product itself. Promises of quality and delivery time can be easily made-but will they be kept? To deal with these issues, EC vendors need to establish high levels of trust with current and potential customers. Trust is particularly important in global EC transactions due to the difficulty of taking legal action in cases of a dispute or fraud and the potential for conflicts caused by differences in culture and business environments.

In addition to sellers and buyers trusting each other, both must have trust in the EC computing environment and in the EC infrastructure. For example, if people do not trust the security of the EC infrastructure, they will not feel comfortable about using credit cards to make EC purchases.

EC Trust Models

Trust in e-commerce is often called online trust. Several models have been put forth to explain the factors that may affect online trust. For example, Lee and Turban (2001) examined the various aspects of EC trust and developed the model shown in Online File W9.2. According to this model, the level of trust is determined by numerous variables (factors) shown on the left side and in the middle of the exhibit. The exhibit illustrates the complexity of trust relationships, especially in B2C EC.

[Enter Exhibit 9.4 here] EC Trust Model

A newer model expands previous ones to include internal and external factors. Internal factors are directly related to online services provided by the vendor, and external factors are those that have indirect relationships (Salo and Karjaluoto 2007).

How to Increase Trust in EC

Consumer trust is fundamental to successful online retailing; it is considered the “currency” of the Internet. The following are representative strategies for building consumer trust in EC.

Improve Your Website. The most important factor that affects online trust is the quality of the website. Cyr (2008) found that the navigational, visual, and information design of a website affect consumer trust. Gregg and Walczak (2010) reported a positive relationship between website quality and trust. Higher perceived website quality induces higher trust and price premium based on a survey of 701 eBay users. Therefore, how to design the EC website that delivers high-quality information and navigational experience

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