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Consumer Behavioral Segmentation and Strategic Positioning for Online Auctions

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Consumer Behavioral Segmentation and Strategic Positioning for Online Auctions.

Abstract

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E-Bay is one of the most widely used and consumer adapted means of selling a product in todays e-business market. It requires a unique marketing approach to effectively segment, target and position potential customers. Competition between sellers can be fierce and without precise understanding of buyer behavior, pinpointing what creates value can be daunting. This paper will address the basic concepts of behavioral segmentation and positioning strategies as they relate to E-Bay auctions.

It is intended to show the importance these findings for sellers to better understand their customers in order to create more efficient positioning strategies. It will evaluate and interpret existing concepts to unfold a new understanding then eventually propose a new conceptual model.

Keywords: Behavioral Segmentation, E-Bay, Target Market, Positioning, Strategies

Introduction

Today, in the 21st century, the average person has the ability to share basically anything online and have it transmitted around the globe within seconds. Businesses are making use of this technology and reaching a much larger consumer base.

If marketers have access to the right information, such as information regarding online consumer behaviors and where to reach their target market, they will be able to focus their attention on those particular areas. Online retailing has seen significant growth over time; especially in recent years this growth has become much more evident. Segmentation and positioning are not strictly “online-tools” but rather pre-existing tools, altered to a certain extent to make them applicable on the web. There are numerous aspects of positioning that all play a vital role in developing a proper positioning strategy for a company. Segmentation and Positioning are both very important but complex aspects of e-commerce. A company will not experience success without it. This being said, the focus over this paper is to uncover the consumer behavior segments in the online auction setting. Online auctions show different behaviors that can influence consumers because prices are not predicable and it is not certain that products will be purchased. Perhaps more so than any other marketplace, understanding the customer behavior of online auction is significant challenge on its own. With the opportunities available in online auctions, retailers are forced to develop more tailored strategies for their target consumer groups(Lee, Kim, Kim 2006).

This paper will also review what basic segmentation involves. Techniques used to enable a business to better target its products at the right customers identify the specific needs and wants of customer groups and then using those insights in providing products and services which meet customer needs. (Riley 2010). With a better understanding of what segmentation involves, positioning will be much easier for companies creating more efficient and effective strategies. This will help them distinguish themselves from their competitors and gain the competitive advantage to needed succeed in the market (Kotler and Armstrong. 2006). To gain understanding of segmentation in online auction markets, three proposed concepts are reviewed. The first by Min-Young Lee, Youn-Kyung Kim, and Hye-Young Kim, titled “Segmenting online auction consumers” conducts research to place online auctions customers in four distinct segments: Impulse Buyers, Variety Seekers, Risk-Averse Economists, and Auction Lovers.” The second proposed model by Chu-Chai Henry Chan titled “Online Auction Customer Segmentation Using a Neural Network Model” shows exactly what the title says. The proposed “Neural Network Model” (SOM) will segment online auction customers into homogeneous groups, impulsive deals, who want to buy products quickly, patient deals , who want to buy products for a longer period, and analytic deals , who do substantial research before making the decision. Chan states that with todays technology and auction websites such as eBay, it makes it much harder to actually “get to know” your customers.

That last model analyzed is a thesis paper by Sua Jeon “The Effect of Consumer Shopping Motivations and Attitudes on Online Auction Behaviors: An Investigation of Searching, Bidding, Purchasing, and Selling.” he breaks consumers into characteristics of “shopping motives that will lead to online purchasing behavior.” Jeon found that shopping motivations and shopping attitudes were significantly related to online auction behaviors. Understanding the relationships is beneficial for companies that seek to retain customers and increase their sales through online auction. Seeing the relations that all three researchers found when conducting similar studies proves that online auctions have unique consumer characteristics. Online auction consumers need to be segmented, targeted and positioned using new techniques that differ from traditional methods. This paper proposes a new conceptual model using the researched segments to address which positioning strategies will be most effective.

Literature Review:

Fundamentals of Segmentation

Market segmentation can be defined as the technique used to enable a business to better target its products at the right customers. It is about identifying the specific needs and wants of customer groups and then using those insights in providing products and services which meet customer needs. (Riley 2010) Segmentation is a very important, yet complicated aspect of e-commerce. The main root of the difficulties arises from the needs of customers. Customer’s needs are far too varying and diverse for a single marketing mix to satisfy everyone’s needs (Zhang, Jiao, and Ma 2007).

Segmentation simplifies strategic planning and thus plays a vital role in all industry sectors. As Beane and Ennis (1987) state, “The underlying logic is that segmentation can enhance marketing effectiveness and improve an organization’s ability to capitalize on market opportunities”. When segmentation is put in place, the segments being targeted are (hopefully) the segments that your product/service applies to most. This will, in turn, attract more traffic and generate more sales.

What is Positioning?

Market positioning can be defined as “an effort to influence consumer perception of a brand or product relative to the perception of competing brands or products. Its objective is to occupy a clear, unique, and advantageous position in the consumer’s mind (Business Dictionary). It is very important to position your company correctly in the target market that will benefit the company the most. Finding the right target market is one of the biggest tasks when trying to establish yourself in the market.

Market positioning, put simply, is how you want to be perceived by your potential customers in relation to your competitors. It must clearly distinguish you from competitors and make it obvious you are the best available choice (Core Marketing). When compared to your competitors you want your company to be the one that sticks out in consumer’s minds. You want to have your firm to have a place in consumers minds that set you above all else and choose you as their “go-to” option. Creating a competitive market position is vital to long-term success (Chen, Uysal 2002).

Insightful Positioning Strategy Concepts

There are many different positioning strategies and many tools that companies use when positioning themselves. “There is more to positioning than clever slogans and slick ad campaigns” (DiMingo 1988). Greg Digneo offers some insight on positioning. He says, “One of the most important aspects of marketing your company or product is its position in the market. The position of the product needs to be designed and engineered into the product itself, ad not be seen as an afterthought” (Digneo 2012). There are many ways to position your company including:

1)Target a Specific Group of People
Build product or service so that it is perfectly suited for a niche that the competition is ignoring 2)Do One or Two Things Very Well
Make sure your product or service focuses on doing one or two things very well instead of trying to do many things at a mediocre level 3)Tell a Unique Story
If competitors are all telling the same “story”, such as lower price or the
most innovative, you need to go a different route. Such as best service or easiest to use. 4)Be More User Friendly
Focus of making the life of your customers easier and don’t try to drain them for every last dine. (Digneo 2012)

According to Kotler and Armstrong (2006), a positioning strategy consists of three major components: 1.To reveal possible competitive advantages that will create a positioning 2.To choose the right competitive advantages and to choose a comprehensive positioning strategy that will align with the organization’s structure and consistent with the positioning objective 3.Company should adopt effective communication and distribution system to market the selected position In order for a company to be successful in positioning, they must distinguish themselves from their competitors. They need to gain the upper hand, or competitive advantage to succeed in the market.

Akpoyomare, Adeosun, and Ganiyu quote Whan et al., (1986) in saying that there are six stages companies must examine in order to determine the right positioning strategy. These are: 1.Identify the competitors

2.Determine how the competitors are perceived and evaluated 3.Determine the competitor’s positions
4.Analyze the customers
5.Select the position
6.Monitor the position.

Developing a positioning strategy is a very complex task. A company, through market analysis and planning, must identify the properties and the images of each of its major competitors. They must fully understand what it is that their customers are looking as well as what their competitors are offering (Oliver 1997)

Conceptual Model: E-Bay Buyer Segments Based on User Traits

Research done by Min-Young Lee, Youn-Kyung Kim, and Hye-Young Kim, titled “Segmenting online auction consumers”, published in the Journal of Consumer Behavior Proves that further research needed to be conducted to accurately segment online auction customers. They preformed studies by surveying a sample of the population and analyzed it “using multi-step cluster analysis, this study categorized respondents (N = 906) into four distinct segments: Impulse Buyers, Variety Seekers, Risk-Averse Economists, and Auction Lovers.” Their reasoning behind this was the growth of online auctions. This is motivating sellers to develop more specific strategies for their target consumer groups. Growth of online auctions is increasing income generating opportunities available and also competition to sellers. This is forcing sellers to stay a step above the competition by creating customized strategies to target their online consumer groups. A closer look is taken at the segment groups found and focused in on shopping values in online auctions, preferences, intentions and expenditure in online auctions. Table 4. Displays results that suggest “that the Auction Lovers enjoyed shopping the most in an online auction, rating high on both utilitarian and hedonic values. In contrast, the Risk-Averse Economists assigned a very low rating to the hedonic value of online auctions. The expenditure in online auctions of this segment is low. Variety Seekers exhibited similar findings, rating low on the hedonic value and high on the utilitarian value of online auctions; however, Variety Seekers were more likely to shop at online auctions than Risk-Averse Economists were.This group also showed a high level of intention to shop in online auctions. Impulse Buyers valued the hedonic benefits and the utilitarian benefits least.” ( Lee, Kim, Kim 2008)

Conceptual Model: Neutral Network Model for Segmenting E-Bay Buyers

Chu-Chai Henry Chan of the Department of Industrial Engineering and Management at Chaoyang University of Technology, in Wufong, Taiwan performed an empirical study consisting of 1470 records retrieved from Taiwan eBay. The proposed “Neural Network Model” (SOM) will segment online auction customers into homogeneous groups (Chan 2005). With todays technology and auction websites such as eBay, it makes it much harder to actually “get to know” your customers”. On sites such as eBay and basically everything else
online, users are recognized only by their screen name, user name, user ID, etc. This issue has built a substantial wall between buyers and sellers; thus, the need for the “Neural Network Model”.

Chu-Chai Henry Chan proposes a three-step consumer behavior model. Chan states, “The first step is to develop a spider program to retrieve a data from online auction site e.g. eBay. The second step is to apply the proposed neural network to segment customers. In this stage, the retrieved auction data are differentiated as several homogenous groups. Finally, the third step is to interpret segmented data as customer types. Each segmented data would be used to describe one type of customer” (Chan 2005). After all three of these steps are carried out, the anticipated end result is the generation of a customer behavior model. Throughout this study, Chan uses several factors of consumer stimuli such as price, promotion, product, and quality as well as personal characteristics such as latest login time, total bid time and number to describe customers. Below is the customer segmentation process (Chan 2005).

There are many different factors that may possibly affect the result of an electronic auction. Normally customers are divided into three major types, impulsive deals, who want to buy products quickly, patient deals , who want to buy products for a longer period, and analytic deals , who do substantial research before making the decision (Chan 2005).

In completion of the study, Chan found that the total number for each customer type were 587 impulsive shoppers, 409 analytic shoppers, and 474 patient shoppers. Chan goes on to say that about 32.5% of analytic shoppers like to spend some time in competing the price during budding and 39.9% of impulsive consumers want to buy their products in a shorter period( Chan 2005).

Conceptual Model: How Shopping Motives Effect Online Auction Purchasing.

In the thesis paper by Sua Jeon “The Effect of Consumer Shopping Motivations and Attitudes on Online Auction Behaviors: An Investigation of Searching,
Bidding, Purchasing, and Selling.” consumers are broken down into characteristics of shopping motives that will lead to online purchasing behavior. He finds that it is essential to online auction success to “1)identify the underlying dimensions of consumer shopping motivations and attitudes toward online auction behaviors; 2)examine the relationships between shopping motivations and online auction behaviors; and 3) examine the relationships between shopping attitudes and online auction behaviors”( Jeon 2006). Jeon gave questionnaires measuring shopping motivations, attitudes, online auction behaviors, and demographic characteristics. Using multiple regression analyses to test the hypothesized relationships, he found that shopping motivations and shopping attitudes were significantly related to online auction behaviors. Understanding the relationships is beneficial for companies that seek to retain customers and increase their sales through online auction. Jeon also identified that reasons why consumers shop could be the result of a variety of hedonic shopping motivations such as “adventure shopping, social shopping, gratification shopping, idea shopping, role shopping, and value shopping” (Jeon 2006). The research went on to find that motivations could also be categorized into extrinsic and intrinsic value. Intrinsic motivations seek other benefits that evoke freedom and fun, and include enjoyment and spontaneity, consumers who have intrinsic shopping motivations seek potential entertainment from the online shopping experience. Like other shopping mediums, there may be many varied reasons consumers shop in online auctions (Jeon 2006). In Figure 4. Jeon breaks buyers shoppings motives into five categories which he believes lead to the online auction purchasing behavior .

Proposed Conceptual Model

After reviewing previous research done on the topic, a new understanding of customer motivations and behavior segments found to be important are incorporated in the new concept model. It is also important to keep in mind insightful positioning strategy concepts and segmentation basics were throughly reviewed before making the new model, research confirms this is important, it is observed that despite millions of people selling, bidding,
and buying products on online auction websites, the existing business literature provides little understanding on essential factors for sellers to implement and evaluate performance. Reviewing past theories of buyer satisfaction and proposing a new template to sellers for determining which segments they want to target and how to correctly strategically position would be of value (Rupak 2009). With this being said, this is exactly what the new proposed model attempts to address. Buyer motivations are examined in the thesis paper by Jeon along with the buyer characteristics determined by Lee, Kim, and Kim, and placed at the top of the conceptual model and logically connected with the E-Bay buyer segments. Once the segments where determined, tailored positioning strategies were listed as a way to target each segment specifically.

After further research, it was established which of these strategies were deemed most important for E-Bay Sellers, these will be highlighted and addressed below.

Important Competitive Positioning Strategies for Derived Buyer Segments

User Feedback: Research shows exceptional user feedback is one of the most essential competitive advantages for E-Bay sellers. Having an exceptional track record with previous customers will create trust and effectively position themselves in the mind of a risk adverse E-Bay buyer. This is confirmed in “Self-selection, slipping, salvaging, slacking and stoning: the impacts of negative feedback at E-Bay” by Khopkar, Li, Resnick, when he finds that “In a trade environment like eBay, buyers have limited information about product quality and seller reliability, at the time of a transaction. Thus, electronic markets like eBay are ripe with the possibility of large-scale fraud and deceit. The Feedback Forum at eBay, where buyers and sellers leave feedback about each other, reduces the information asymmetry, by telling buyers whether previous customers were satisfied with the seller”(Khopkar, Li, Resnick, 2005).

Appeal and Image of EBay Store and Website:
Every targeted group would receive value from a professional appeal and
strong E-Bay store image. Findings suggest that increasing the quality of an auction business’s e-image does increase consumers willingness to transact with the business, and increases prices received at auction(Greg, Walczak 2006). This is especially important for the risk-Averse section of the model, these people are most sensitive to a companies image for fear of fraud, faulty products etc.

Buy it Now Option: One researcher found that the“buy-it-now” feature, which allows sellers to post a buy price at which a bidder can end the auction early, can increase the seller’s expected revenue if bidders are impatient. If this is correct, having the “buy it now” option to position to “impulsive” buyers would be effective, as these buyers are only looking for immediate emotional gratification and want their products immediately (Ackerberg, Hirano, Shahriar 2011).

Conclusion:

It is clear that not enough information is available on online auction markets as far as segmenting, positioning and targeting customers goes. Customer segments are unique in online auctions, traditional methods and theories will not be efficient or effective if used by marketers. With the increase growth and opportunities expected to be available for online auction sellers, research is now being done to pinpoint the new segments and characteristics of the buyers. Although, some new segments and characteristics of E-Bay buyers have been determined, there is no proposed concepts on how to effectively target and position to E-Bay buyers that fall into these categories. The conceptual model proposed above attempts to give more insight on what E-Bay buyers actually want from sellers by analyzing their specific behaviors and characteristics. Tailored strategies for each new segments are listed, in an attempt to meet buyer needs. If the E-Bay buyers in each segment needs can be met, sellers will have a much easier time obtaining their business and loyalty. In the future, it is hopeful that more research will be done on this matter, and eventually sellers can implement performance metrics to measure the effectiveness of their newly targeted positioning strategies.

References

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Chen, Joseph, and Muzaffer Uysal. “Market Positioning Analysis A Hybrid Approach.” Annals of Tourism Research. 29.4 (2002): 987-2003. Print.

Digneo, Greg. “4 Ways To Position Your Company Among Well Entrenched Competitors.” Kissmetrics. (2012)

DiMingo, Edward, The Fine Art of Positioning, Journal of Business Strategy, 9:2 (1988:Mar./Apr.) p.34

Kennedy, Dan, and Chip Kessler. “Marketing to seniors: Online Versus Offline.” Entrepreneur. N.p., 22 Feb 2013. Web.

Kotler, P. (1991). Marketing Decision Making. Harper and Row Publishers

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Riley, Jim. “What is market segmentation?.” tutor2u, 15 January 2012. Web. 9 Apr 2013.

Unknown, . “Market Cannibalization.” Investopedia. N.p.. Web.

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Whan, C.P., Bernard, J., & Deborah, J.M. (1986). Strategic Brand Concept-Image Management. Journal of Marketing, 50 , 135-145.

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Lee, Min-Young, Kim, Youn-Kyung and Kim, Hye-Young (2008).“Segmenting online auction cConsumers”, Journal of Consumer Behavior, 7(2),135-148.

Sua Jeon “The Effect of Consumer Shopping Motivations and Attitudes on Online Auction Behaviors: An Investigation of Searching, Bidding, Purchasing, and Selling.”, Thesis, 2006. http://digital.library.unt.edu/ark:/67531/metadc5366/m1/1/

Khopkar, L., Resnick, P., 2005. “Self-Selection, Slipping, Salvaging, Slacking, and Stoning: the Impacts of Negative Feedback at eBay” In: Proceedings of ACM Conference on Electronic Commerce (EC05).

Rupak, R., G, Rawski,G., Crumbly, J. Simms, J.(2009) “C2C Online Auction Website Performance:Buyers Perspective”.Journal of Electronic Commerce Research, VOL 10, NO 2, 2009

D. Ackerberg, K. Hirano, and Q. Shahriar. “Identification of time and risk preferences in buy price auctions”. Working Paper, University of Arizona, 2011.

Cite this Consumer Behavioral Segmentation and Strategic Positioning for Online Auctions

Consumer Behavioral Segmentation and Strategic Positioning for Online Auctions. (2017, Jan 31). Retrieved from https://graduateway.com/consumer-behavioral-segmentation-and-strategic-positioning-for-online-auctions/

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