A Model Of Consumer Behavior Online

Published Date: 23 Mar 2015 Last Modified: 18 May 2017

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.

<H1>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.

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.

<H2>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.

<H1>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.

</INTRO></FM><BM>

<H1>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.

<H2>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 <OLINK>Chapter 5</OLINK> (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. <LINK>Exhibit 9.1</LINK> 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]

<BL> 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. <LINK>Exhibit 9.1</LINK> illustrates the major variables in each influential dimension. A more detailed description is provided in <OLINK>Online File W9.1</OLINK>.

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.</BL>

The Major Influential Factors

These factors fall into the following categories:

<H4>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., <URL>emarketer.com</URL>, <URL>clickz.com</URL>, and <URL>comscore.com</URL>). 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).

<H4>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.

<H4>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.

<H4>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).

<H5>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).

<H5>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).

<H4>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:

<H5>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.

<H5>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.

<H5>Other environmental variables. These include aspects such as available information, government regulations, legal constraints, and situational factors.

[Comp: please shade the bullet list]

<H6>Section 9.1 Ÿ Review Questions

<GENQ>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.</GENQ>

<H1>9.2 The Consumer Purchasing Decision-Making Process

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

repurchase.

<H2>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 (<KT>product brokering</KT>) and from whom to buy it (<KT>merchant brokering</KT>). 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 <URL>shopping.com<URL>, <URL>buyersindex.com</URL>, and <URL>mysimon.com</URL>, 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:

<NL>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.</NL>

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

<NL>5. S-Satisfaction. Customer satisfaction will generate higher loyalty and lead to repurchase after using a product/service.</NL> (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.

<H2>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 <OLINK>Online File W9.3</OLINK> 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)..

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.

<H2>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:

<NL>

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.</NL>

[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.

<H6>Section 9.2 Ÿ Review Questions

<GENQ>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.</GENQ>

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 (<URL>octopuscards.com</URL>), 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 at<URL>fancl.com</URL>, 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 is a key to increase consumer trust in the website.

Affiliate with an Objective Third Party. This approach aims at building consumer trust by affiliating the customer with trusted third parties. Internet stores can put hypertext links on their websites to trusted targets, including reputable companies or well-known portals. These reputable companies are able to transfer brand equity to the Internet stores because companies with brand names facilitate trust. Internet stores can also use third-party seals of approval such as TRUSTe (truste.com) and BBBOnline (bbbonline.org), the online version of the Better Business Bureau. Escrow providers and reputation finders (e.g., cyberalert.com and cymfony.com) also are useful. These agencies provide business-critical intelligence on how brands are being used on the Internet as well as research about spying on businesses.

Working against EC trust are stories about fraud on the Internet, especially when unknown parties are involved. Reputation systems that were described in Chapter 7 can impact trust either positively or negatively.

Establish Trustworthiness. Trustworthiness can be achieved through three key elements: integrity, competence, and security. Integrity conveys an overall sense of the ability of the Internet store to build an image of strong justice and fulfill all the promises that have been made to the customers (i.e., offering a money-back guarantee with the products and clearly stating the guarantee policy on the website). Another indicator of trustworthiness is an Internet store's competence. Stores can promote the perception of competence by delivering a professional website. Finally, EC security mechanisms can help solidify trust. Dell was the first PC manufacturer to launch an online secure shopping guarantee to online shoppers making purchases at its website.

Other Methods for Facilitating Trust

Several other methods are used to facilitate trust on the Web. For example, tying cognitive style to communication with customers (Urban, et al. 2009, discussed later in the chapter) is designed to build trust. Another method is that of reputation.

Reputation-Based Systems. Reputation is the opinion of the public toward a person, a group of people, or an organization. It is an important factor in many fields, such as business, online communities, and social status. Reputation-based systems are used to establish trust among members of online communities where parties with no prior knowledge of each other use the feedback from their peers to assess the trustworthiness of the peers in the community. For details, see 'Reputation' at Wikipedia. For a comprehensive overview and how to design a reputation system, see Dellarocas (2010).

A major player in this area is Yelp.com, which aggregates reviews that contain highly subjective judgments. Its system enables similarly minded users to spot each other.

Online Word of Mouth. Due to the increased social activities on the Internet, online word of mouth is also influencing trust level.

A study by Awad and Ragowsky (2008) found that online word-of-mouth quality affects online trust and its effect varies across genders. In general, males value their ability to post online, whereas females value the responsive participation of other consumers. Online word of mouth may occur in different forms, such as consumer online feedback and participation in social media forums. Hence, fostering positive word of mouth is an effective strategy to build stronger trust in a website.

SECTION 9.3· REVIEW QUESTIONS

1. Describe customer loyalty and e-loyalty.

2. Describe the use of business intelligence and analytical software for e-loyalty.

3. Describe the issue of trust in EC and how to increase it.

4. What influences consumer satisfaction online? Why do companies need to monitor it?

5. How can trust be increased in EC?

6. Define reputation-based systems and relate them to trust in EC

<H1>9.4 Mass Marketing, Market Segmentation, and Relationship Marketing

One of the greatest benefits of EC is its ability to match products (services) with individual consumers. Such a match is called one-to-one marketing, a part of the relationship marketing that treats each customer in a unique way to fit marketing and advertising with the customer's profile and needs. Let's first see how the one-to-one approach evolved from traditional marketing approaches.

<H2>From Mass Marketing to One-to-One Marketing

Three major basic approaches are used in marketing and advertising: mass marketing, market segmentation, and relationship (one-to-one) marketing.

<H3>Mass Marketing and Advertising

Marketing efforts traditionally were targeted to everyone (the "masses"). For example, using a newspaper or TV ad usually means one-way interpersonal communication to those who see it. Such an effort may be effective for brand recognition or for introducing a new product or service. It can be conducted on the Internet as well. Putting banner ads on an Internet portal to send messages to everyone who accesses the website is a typical example of mass marketing.

Example. In 2005, Ford Motor Company unveiled a roadblock approach on the Internet to promote its F-150 truck. (A "roadblock" refers to running a commercial on all major TV channels at exactly the same time, so viewers cannot switch channels to escape the commercial.) On the day of the launch, Ford placed static banner ads for 24 hours on the three leading Internet portals-AOL, MSN, and Yahoo!-introducing a 3-month campaign. Some 50 million Web surfers saw Ford's banner. Millions of them clicked on the banner, pouring onto Ford's website at a rate that reached 3,000 per second. Ford claimed that the traffic led to a 6 percent increase in sales over the first three months of the campaign.

[End of example]

<H3>Market Segmentation

<KT>Market segmentation</KT> refers to the practice of promoting a product or service to a subset of customers or prospects. For example, cosmetic product producers may put their advertisements mostly in magazines geared toward women. This implies that the market is segmented by the gender of consumers. One advantage of market segmentation is that advertising and marketing efforts can match segments better than the "mass," providing a better response rate. Also, the expense of reaching the segments may be lower, and marketing efforts can be faster (e.g., e-mails are sent to fewer people, or banner ads are placed on fewer websites). The Internet enables more effective market segmentation, but it also improves relationship marketing, or one-to-one marketing.

<H4>Criteria for Market Segmentation.</H4> For effective market segmentation, the following are common criteria that companies use:

<BL>

• Geographic. Region; size of city, county, or Standard Metropolitan Statistical Area (SMSA); population density; climate; language.

• Demographic. Age, occupation, gender, education, family size, religion, race, income, nationality, urban (or suburban or rural).

• Psychological (lifestyle). Social class, lifestyle, personality, activities, VALS typology (see 'VALS typology' at<URL>strategicbusinessinsights.com</URL>).

• Cognitive, affective, behavioral. Attitudes, benefits sought, loyalty status, readiness stage, usage rate, perceived risk, user status, innovativeness, usage situation, involvement, Internet shopping experience.

• Profitability. Valued customers are placed in a special category.

• Risk core. Low-risk customers are in a special category.</BL>

[Comp: please shade the bullet list]

Statistical and data mining methods are often used to identify valuable segments for promotion or advertising. Modern companies assign a variety of segments to their customers, often dynamically defining segments and temporarily regrouping customers for specific campaigns. By segmenting customers, companies could begin more specialized communications about their products. Much of this relies on the company's understanding its business strategies to the extent that they know their most desirable segments. For instance, if a bank has organized its website on deriving most of its profits from fee-income products offered in its investment services line of business, customers for this bank will likely have different preferences and characteristics from those banks offering only savings accounts. Segmenting customers based on their preferred line of business or desired product features can reveal interesting facts about their different preferences and behaviors.

A simple way to do segmentation online is to go to a specialized website or portal and advertise to its visitors. For example, when you go to <URL>ivillage.com</URL>, you reach mostly women. Advertising in Internet communities and social networks usually provides you with market segmentation. Increasingly, advertising is being placed on social networking sites (such as Facebook). Note that U.S. spending on social network advertising is growing rapidly (see <OLINK>Chapter 7</OLINK>). Some Weblogs that focus on specific niches (e.g.,see <URL>paidcontent.org</URL> or <URL>fark.com</URL>) are more attractive to advertisers.

<H3>Relationship (One-to-One) Marketing

<KT>Relationship marketing</KT> is different from traditional marketing in that it focuses on building long-term relationships with customers. In order to do so, the seller must have a much deeper understanding of its customers on a one-to-one basis. To do so, merchants need to know their customers' profiles. Such information can be obtained faster, easier and cheaper for online customers. When such information is analyzed it become valuable for one-to-one marketing.

Although segmentation can focus on a group of customers, it may not be good enough because most of the competitors can adopt similar strategies. It may be advisable, therefore, to shift the target for marketing from a group of consumers to each individual. Instead of selling a single product to as many customers as possible, marketers are trying to sell as many products as possible to one customer-over a long period of time. To do this, marketers need to concentrate on building unique relationships with individual customers on a one-to-one basis.

<KT>One-to-one marketing</KT>is a way for marketers to get to know their customers more intimately by understanding their preferences and then providing personalized marketing communication.

One-to-one means not only communicating with customers as individuals, but possibly providing customized products and tailored messages based on the customer's preferences. The major characteristics of one-to-one marketing as compared to mass marketing and market segmentation are illustrated in <LINK>Exhibit 9.5</LINK>.

[Insert Exhibit 9.5 here]

<H2>How One-to-One Relationships Are Practiced

Although some companies have had one-to-one marketing programs for years, it may be much more beneficial to institute a corporate-wide policy of building one-to-one relationships around the Web. This can be done in several ways. For example, <LINK>Exhibit 9.6</LINK> shows a possible one-to-one marketing cycle. The cyclical process includes four stages: identification of customer preference, differentiation of products/services, interaction with customers, and customization (personalized service). The process can start at any point in the cycle. For new customers, it usually starts with "Customer receives marketing exposure" (at the top right side of exhibit). The customer then decides on how to respond to the marketing exposure and makes the purchase decision (e.g., whether to buy the product online or offline; if online, whether to buy as an individual or to use group purchasing). When a sale is made, customer information is collected (lower left corner) and then it is placed in a database. Then, a customer's profile is developed, and the so-called four Ps of marketing (product, place, price, and promotion) are planned based on the profile, on a one-to-one basis. All of this can be done in the Web environment.

[Insert Exhibit 9.6 here]

Unfortunately, many businesses view their interactions with customers as distinct transactions. However, customers do not look at them this way; view their relationship with a business as relationship, not individual interactions. What if businesses could go beyond what is just transacted with their customers when evaluating the quality of the service they provide and look at the overall relationship with a customer across all channels? What if by doing this they could incorporate a customer's feeling, wants and needs into the equation. Such an approach is emerging now as a theory of customer dynamic (see Ziv 2010) and it is practice on the Web as a one-to-one strategy.

One of the benefits of doing business over the Internet is that it enables companies to better communicate with customers and better understand customers' needs and buying habits. These improvements, in turn, enable companies to enhance and frequently personalize their future marketing efforts. For example, Amazon.com can e-mail customers announcements of the availability of books in their areas of interest as soon as they are published; Expedia.com will ask consumers where they are likely to fly to and then e-mail them information about special discounts to their desired destination. Details on these key concepts that are part of personalization are discussed in Section 9.5.

<H6>Section 9.4 Ÿ Review Questions

<GENQ>1. Define and describe mass marketing.

2. Define market segmentation. How is segmentation done?

3. Define one-to-one marketing. What are its advantages?

4. Describe the one-to-one marketing cyclical process.

5. How is the knowledge of a customer profile used by the advertisers?</GENQ>

<H1>9.5 Personalization and Behavioral Marketing

Internet marketing facilitates the use of market segmentation and one-to-one marketing. Here we address three key issues related to one-to-one marketing: personalization, behavioral targeting, and collaborative filtering.

<H2>Personalization in E-Commerce

<KT>Personalization</KT> refers to the matching of services and advertising content to individuals based on their preferences. The matching process is based on what a company knows about the individual user. This knowledge is usually referred to as a user profile. The <KT>user profile</KT> defines customer preferences, behaviors, and demographics. It can be generated by getting information directly from the user; observing what people are doing online through the use of tools such as a <KT>cookie</KT>-a data file that is placed on a user's hard drive by a remote Web server, frequently without disclosure or the user's consent, that collects information about the user's activities at a site; building profiles from previous purchase patterns; performing marketing research (see <LINK>Section 9.6</LINK>); and making inferences from information known about similar consumers.

Once a customer profile is constructed, a company can match the profile with a database of products, services, or ads. Manual matching is time-consuming and expensive; therefore, the matching process is usually done by computerized software agents. One-to-one matching can be applied through several different methods. One well-known method is collaborative filtering (discussed later in this section).

Many vendors provide personalization tools that help in customer acquisition and retention. Examples of such vendors are Get Sidecar, see<URL>getsidecar.com</URL> and Magnify 360, see <URL>magnify360.com</URL>.

<H3>Cookies in E-Commerce

The use of cookies is a well-known method that enables the identification of customers' future visits on the same computers. See 'cookies' at Wikipedia. .

Are cookies bad or good? The answer is "both." When users revisit Amazon.com or other sites, customers are greeted by their first name. How does Amazon.com know a user's identity? Through the use of cookies! Vendors can provide consumers with considerable personalized information if they use cookies that signal a consumer's return to a site. Cookies can provide marketers with a wealth of information, which then can be used to target ads to them. Thus, marketers get higher rates of "click-through," and customers can view the most relevant information. Cookies can also prevent repetitive ads because vendors can arrange for a consumer not to see the same ad twice. Finally, advanced data mining companies (e.g., provided by SPSS and Sift), can analyze information in cookie files so companies can better meet their customers' needs.

However, some people object to cookies because they do not like the idea that "someone" is watching their activity on the Internet. Users who do not like cookies can disable them. On the other hand, some consumers may want to keep the friendly cookies. For example, many sites recognize a person as a subscriber so that they do not need to register several times.

For information on deleting cookies from you Internet browser see 'deleting cookies' at <URL>whitecanyon.com</URL>.

<H3>Using Personalized Techniques to Increase Sales

Companies try to provide personalized services to customers in order to increase customers' satisfaction and loyalty. A prime example is Amazon.com which provides many personalized services. Most common there are product recommendations. Amazon.com generates automatically such recommendations based on the buyers' purchasing and browsing histories, and upon purchasing of other customers with similar purchasing history (see Scharge (2008) for details). Another company, MotherNature.com, see at<URL>mothernature.com</URL>, is using data and text mining to analyze each site visit based on the customer's preferences and buying habits. It is able to track everything from the success rate of online promotions to trends that can be used in site personalization. Personalized services can be facilitated when the companies know more about their customers. Such information is provided, see 'personalized service' at <URL>rapleaf.com</URL>.

<H2>Behavioral Marketing and Collaborative Filtering

One of the most popular ways of matching customers with ads is by using technologies based on customer behavior on the Web. It is essentially a one-to-one approach. We discuss here the essentials of this approach, which is known as behavioral targeting, and provide brief information on one method for doing it.

<H3>Behavioral Targeting

<KT>Behavioral targeting</KT> uses information collected about an individual's Web-browsing behavior, such as the pages they have visited or the searches they have made, in order to select an advertisement to display to that individual. Many vendors believe that this can help them deliver online advertisements to users who then would be influenced by the ads. Behavioral targeting can be used on its own or in conjunction with other forms of targeting, such as using factors like location of the customers or demographics. Google is reported to test its "interest-based advertising" to make ads more relevant and useful. Representative vendors of behavioral targeting tools are Predictad.com, Adlink.com, Adaptlogic.com, Boomerang.com, Criteo.com, and Valueclick.com. For more information see at Wikipedia.. A major method of behavioral targeting is collaborative filtering.

<H3>Collaborative Filtering

It would be useful if a company could predict what products or services are of interest to a customer without asking the customer directly. <KT>Collaborative filtering</KT> is a method that attempts to do just that; it uses the preferences and activities of customers with similar characteristics to build user profiles of new customers and make product recommendations to them. Many personalization systems are based on collaborative filtering; see more information at <URL>backflip.com</URL> and <URL>choicestream.com</URL>. The statement "Those who bought this item also bought the following items:" is a typical statement generated by collaborative filtering, which intends to persuade a consumer by pointing to preferences of other consumers.

<H3>Other Methods

In addition to collaborative filtering, other methods for identifying users' profiles are:

<H4>Rule-based filtering. A company asks consumers a series of yes/no or multiple-choice questions. The questions may range from personal information to the specific information the customer is looking for on a specific website. Certain behavioral patterns are predicted using the collected information. From this information, the collaborative filtering system derives behavioral and demographic rules such as, "If customer age is greater than 35, and customer income is above $100,000, show Jeep Cherokee ad. Otherwise, show Mazda Protégé ad."

<H4>Content-based filtering. With this technique, vendors identify customer preference by the attributes of the product(s) they intend to buy. Based on user preferences, the vendor's system will recommend additional products with similar attributes to the user. For instance, the system may recommend a text-mining book to customers who have shown interests in data mining, or recommend more action movies after a consumer rented one.

<H4>Activity-based filtering. Filtering rules can also be built by watching the user's activities on the Web.

For more about personalization and filtering, see personalization and filtering at Wikipedia.

<H3>Legal and Ethical Issues in Collaborative Filtering

Information often is collected from users without their knowledge or permission. This raises several ethical and legal questions, including invasion of privacy issues. Several vendors offer permission-based personalization tools. With these, companies request the customer's permission to receive questionnaires and ads. (See Chapter 14 for more on privacy issues, and Section 8.10 for information about permission marketing.)

In November 2010, Facebook announced the possibility of rolling out a Web-based advertising network that targets ads based on the recipients' behavior and the behavior of their Facebook friends. Privacy groups are not happy and are trying to pressure Facebook to cancel project.

<H3>Social Psychology and Morphing in Behavioral Marketing

Social psychology is the branch of psychology that deals with how people think about, influence, and relate to one another. Research has found that shoppers do what is popularly known as 'thinslicing' when they are out shopping. Thinslicing is a style of thinking (psychologist call it heuristic-thinking) that involves ignoring most of the information available, and instead using (slicing off) a few salient information cues, often social in nature, along with a set of simple, but usually smart mental rules of thumb to make intuitive decisions. Psychologists have identified six universal heuristics (mental rules of thumb) that shoppers use to process thinsliced information; social shopping tools are powerful because they harness these heuristic to make purchase decisions more likely. For details see Marsden (2009).

One level the social psychology reflects in social shopping (see Chapter 7); social shopping harnesses the human capacity for social learning, learning from the knowledge and experience of others we know and/or trust. This social learning faculty is part of our social intelligence, the ability to understand and learn from each other and profit from social situations. But social shopping tools also work at a more fundamental level, by playing to cognitive biases in how people are influenced by other people when shopping.

<H4>Cognitive styles and morphing. Cognitive styles that define how people process information is becoming a subject of research by behavioral scientists with respect to Internet marketing and advertising. Specifically, an attempt is made to connect the Web with users in the cognitive style they preferred. This can make one-to-one advertising messages more effective. MIT designed an empathetic Web that is used to figure out how a user processes information and then responds to each visitor's cognitive style. For a comprehensive description see Urban et al. (2009).

<H3>Use of Customer Database Marketing

Personalized services are often based on information the merchant gets from commercial database marketing services (e.g., see Strauss and Frost 2009). A unique example of such service is Rapleaf.

<H4>Example. Rapleaf is a database marketing startup (<URL>rapleaf.com<URL>). Acting primarily as B2B firm, Rapleaf's database of consumer information helps businesses segment customers, understand consumer penetration across social media, plan online marketing campaigns, find influential customers for a customer relationship management, and investigate fraud.

The company provides businesses with information about the reputation of individual customers. It is like credit card verification. But the information provided (e.g., demographic) on each customer enables merchants to provide personalized services. Individuals can see their own level of reputation (and hopefully improve it) and they can better understand their online footstep. For how the company collects information, what they know about you, how they use the information, and what privacy concerns exist see Steel (2010).

[End of example]

<H6>Section 9.5 Ÿ Review Questions

<GENQ>1. Define personalization and list some benefits of personalization.

2. Describe cookies in EC.

3. Define behavioral targeting.

4. Define collaborative filtering.

5. Explain how one-to-one advertising is done with cookies and behavioral targeting.</GENQ>

<H1>9.6 Market Research for E-Commerce

In order to sell products well, it is important to conduct proper market research to find information and knowledge about consumers and products. The market researcher's goal is to discover marketing opportunities and issues, to establish marketing plans, to better understand the purchasing process, and to evaluate marketing performance. On the Web, its purpose is also to investigate the market and behavior of online customers. (e.g., see Strauss and Frost 2012). Market research includes gathering information about topics such as the economy, industry, firms, products, pricing, distribution, competition, promotion, and consumer purchasing behavior.

<H2>Objectives and Concepts of Market Research Online

Investigation of EC markets can be conducted through conventional methods or it can be done with the assistance of the Internet. Although telephone or shopping mall surveys will continue, interest in Internet research methods is on the rise. Market research that uses the Internet frequently is faster and more efficient and allows the researcher to access a more geographically diverse audience than those found in offline surveys. Also, on the Web, market researchers can conduct a very large study much more cheaply than with offline methods. Even telephone surveys can cost as much as $50 per respondent. This may be too expensive for a small company that needs several hundred respondents. An online survey will cost a fraction of a similarly sized telephone survey and can expedite research considerably, as shown in <LINK>Case 9.1</LINK> about P&G. The increased sample size in online surveys can theoretically increase the accuracy and the predictive capabilities of the results. McDaniel and Gates (2012) provide a comprehensive review of online market research technologies, methods, tools, issues, and ethical considerations.

<CS1><NUM>Case 9.1

<SUPTTL>EC Application

<TTL>Internet Market Research Expedites Time-to-Market at Procter & Gamble

For decades, Procter & Gamble (see P&G information at <URL>pg.com</URL>), Johnson & Johnson, and Colgate-Palmolive have been competitors in the market for personal care products. Developing a major new product from concept to market launch used to take more than 5 years. First, a concept test was conducted: The companies sent product photos and descriptions to potential customers, asking whether they might buy the product. If the feedback was negative, they tried to improve the product concept and then repeated the previous concept test. Once positive response was achieved, sample products were mailed out, and the customers were asked to fill out detailed questionnaires. When customers' responses met the companies' required goals, the companies would start with mass TV advertising.

However, thanks to the Internet, it took P&G only 31/2 years to get Whitestrips, a teeth-brightening product, onto the market and to a sales level of $200 million a year-considerably quicker than it had taken in the past with other oral care products. In September 2000, P&G replaced its traditional test model with a Web-based model for Whitestrips. The company spent several months studying who was coming to the site and buying the product and collecting responses to online questionnaires, which was much faster than the old mail ones.

The online research, which was facilitated by data mining conducted on P&G's huge historical data (stored in a data warehouse) and the new Internet data, identified the most enthusiastic groups. These included teenage girls, brides-to-be, and young Hispanic Americans. Immediately, the company started to target these segments with appropriate advertising. The Internet created a product awareness of 35 percent (a very high level), even before any shipments were made to stores. This awareness created a huge demand for the product by the time it became available in stores.

In 2006, P&G began using on-demand solutions from RightNow Technologies, see 'RightNow Technologies'at <URL>rightnow.com</URL>, including survey tools that execute opinion polls among selected segments of consumers who have opted into the company's market research programs (reported by PR Newswire 2006).

In 2008, P&G started to experiment with feedback collected at Facebook and other social networks. Such an information solicitation can be beneficial for successful promotion of products since people can spread the word around by word of mouth.

From these experiences, P&G learned important lessons about flexible and creative ways to approach product innovation and marketing. The whole process of studying the product concept, segmenting the market, and expediting product development has been revolutionized. As of 2009, all major competitors established groups on Facebook, developed islands in Second Life, and use LinkedIn and Twitter to communicate and learn from customers. They shorten the time-to-market and get better feedback from customers, as shown at Johnson & Johnson (see the closing case of this chapter) and in Ploof (2009). In 2010, P&G launched its "Future Friendly" campaign to raise awareness about greener products and greener practices as part of its "sustainability vision."

<SRC>Sources: Compiled from TMCnet.com (2006), Buckley (2002), Ploof (2009), Makower (2010), and <URL>