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Benefits and Challenges of Segmentation - Research Proposal Example

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This research proposal "Benefits and Challenges of Segmentation" explores the challenges of developing marketing targeted to different consumer segments in Qatar. It was found that around the world, the concept of multidirectional segmentation has emerged…
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Extract of sample "Benefits and Challenges of Segmentation"

Table of Contents Introduction 2 Literature Review 3 Ecommerce Customer Segmentation 5 Benefits and Challenges of Segmentation 5 Segmentation Strategies 5 Conclusions 6 References 7 Introduction Internet has permeated world boundaries across demographics and geographical areas. It has proved out to be a game changer in the business arena and presents a new way to manage commerce. Buyers and sellers that are otherwise geographically dispersed are able to connect with each other through ecommerce. With development of ecommerce platforms in huge numbers, a large number of people have started to use ecommerce for business transactions. In 2014, the global E-commerce sales contributed $1.5 Trillion in the B2C space. With increase in Smartphone usage and ability to make purchases through the use of mobile phones, the growth of commerce has increased to 18% annually in mature markets like Europe and America and to 20% in developing markets like Asia, Middle East, and Africa. These facts suggest that there is significant opportunity for retail organizations to make their mark in the online space[Cor10]. Online retail sales in US are expected to reach $370 billion by the end of the year 2017. In Europe, it is expected to reach $240 billion in the same time. In India, ecommerce sales are increasing at a 50% CAGR rate and it is expected to reach $45 billion by the year 2020. More than 80% of the consumers globally try online shopping at least once which presents great opportunities for ecommerce organizations to build portable and long -lasting relationships between consumers and ecommerce organizations. If a relationship has to be made strong, the organizations need to understand the shopping behaviour of consumers. In the event of continuous growth of online consumers, the objective of ecommerce organizations is not to gain more visitors but to retain coming visitors on the website such that they do not leave the website and go to competitors. Consumers also use ecommerce for comparing benefits of different products and services in the online space. Some consumers also use ecommerce platform for fun, emotional gratification, gratification or hedonic benefits. Business organizations are using ecommerce for reducing their operational and marketing expenses as well as to connect with consumers directly to receive feedbacks from them about the products and services that are sold through ecommerce platforms. Consumers in the ecommerce space are commonly understood as looking for a good user experience and attractive atmosphere but researcher have shown that online consumers are more inclined towards the brand image of a website and the value proposition provided by the website. Online consumer segments show some unique characteristics that make them different. Organizations need to understand the differentiating needs of various consumer segments and cater to them with different strategies through formation of a multi-dimensional strategic framework. In this paper, ecommerce consumer segments in Qatar would be studied in order to understand them such that the strategic framework can be created for managing online consumers of the ecommerce space in the region. The study would involve exploration of different segmentations of online consumers. Literature Review As per Wigand (1997), any commercial activity that is performed using an electronic connection can be called as ecommerce. As per Varadarajan and Yadav (2002), it is an information system that enables an infrastructure that can be used by buyers an sellers for exchanging information or making transactions. According to Liu and Arnett, ecommerce is a method of doing business between organizations and consumers by using computer networks. For examination of the behaviour of online consumers, online shopping attributes, website selection models, and behavioural intensions of consumers have been explored by various researchers. Some theories can be used for understanding online consumer’s adoption of innovative technologies and their shopping behaviour such as technology acceptance model (TAM), Theory of Reasoned Action (TRA), and the theory of planned behaviour (TPB). These theories can be used for understand the consumer behaviour. TRA can be used for making predictions about the behaviour of consumers. TAM can be used to explore perceptions of consumers about the ease of use and usefulness of ecommerce. TPB anticipates consumer behaviour on the basis of their behavioural intensions and perceived behavioural control. Other theories like the transaction cost and the innovation diffusion theories can be used for understanding factors that lead consumers to shift from traditional store to ecommerce stores. Researchers have observed that traditional models present many constraints while online stores bring convenience to customers in several forms which are a primary reason why consumers are adopting ecommerce[Deb151]. As per Thomson and Laing (2003), there could be some key reasons why consumers would opt for the online shopping through ecommerce and these include reduction in the shopping time, convenience, flexibility, competitive pricing, and freedom to shop. An intension to make online purchases is determined by the value of the website as perceived by consumers. A repurchase intension can be shaped by the perceived usefulness of an ecommerce store for consumers and the perceived ease-of-use of the same website for them[Jun12]. However, there are counter arguments made by other researchers including Kim and Stoel (2004) who observed that ease of use did not make any significant contribution to customer satisfaction. They found that the transaction features and quality of content on the website were more important for achieving customer satisfaction. They also stated that ability of the website to respond quickly can have a strong influence on consumer satisfaction but Xia, Mengqiao, Fang and Peihong (2008) did not see any significant impact of rapid response on consumer satisfaction. As per them design aspects were not very important but as per Wolfinbarger and Gilly (2003), frequent consumers consider website design as an important criteria to judge the quality of the products listed on an ecommerce store[Hon02]. Other factors that are determined to be causing impacts on consumer satisfaction and influences on the consumer decision making on choice of web portal for making an online purchase include timely and proper deliveries of products, convenience of transaction, information given online, compatibility of terms and conditions, simplified processes, easy return and compensation policies. Selection of a website is a complex phenomenon which is influence by a range of different factors such as atmosphere, information availability, transaction convenience, brand image, and so on. Most ecommerce organizations use more than one segmentation model that includes demographics, behaviour, preferences, value, or a mix of these. Micro-segmentation is another trend that has emerged in recent past which is based on consumer journeys such that one organization uses 10 to 20 micro-segmentation models for understand motivations behind purchases decisions of their consumers. In micro-segmentation, multiple dimensions can be integrated such as device preferences, marketing campaign responsiveness and visit time for predicting behaviour of consumers. A cross-device view of consumer journey is one such example of micro-segmentation that has helped companies leverage on the mobile growth for ecommerce. More is the integration between dimensions, higher are the chances that consumers would resonate with the offers promoted by the ecommerce organization[Placeholder8]. Ecommerce Customer Segmentation Benefits and Challenges of Segmentation A major work of online conversion in to convert anonymous browsers of products into paying customers and by using segmentation for these users based on different criteria like fashion, purchase history, loyalty decisions, the rate of conversion can be improved. It also helps an organization identify consumers with high potential for purchase as different segments can be compared. Customer segmentation can also help deliver insights on the factors that can influence the purchase decisions of online consumers. Segments can be created for a group of people showing similar attributes that could be demographic, geographic, behavioural, psychographic, and so on. The key objective of segmentation is to understand consumers such that successful production can be made on their interested in relevant products and services. However, despite the benefits associated with segmentation practical, there are challenges such as higher level of investment, more time required for segmentation, labour intensive, and need to respond faster to changing environment of ecommerce and markets[For152]. Segmentation Strategies Ecommerce consumers can be segmented in different ways one of which is clustering of shoppers based on their behaviour. Cluster segmentation divides consumers into four types of segments including traditional shoppers, benefit seekers, convenience or assurance seekers and information or price seekers. Consumers in each of these segments vary in terms of their preferences for selection of websites and their orientation towards online shopping[ZNO13]. Consumer segmentation can also be done on the basis of demographics and lifestyle attributes such as location, gender, age, and interests. Most marketing efforts work on such segmentation of consumers. Certain organizations make use of integrated segmentation practices such that a balance can be created between different segmentation criteria such as behaviour, market trend, consumer history, and so on. However, this approach is rare. But it has the potential to maximize online conversion rates as it would allow companies to develop strategies based on a holistic understanding of the consumer behaviour. For instance, a baby product selling platform can use a segmentation model based on fashion deals that attracted consumers such that marketing of deals can be adjusted as per the changes in the visit schedules of customers. A customer may like to browse offers on mobiles in morning while make final purchases using their laptops in the evening their time after having consulted with friends and family. A one dimensional consumer segmentation done on the basis of specific attribute can be limiting and thus, a multi-dimensional segmentation involving multiple criteria’s 0f segmentation including geographic, demographics, purchase behaviour, and Psychographics including consumer interests, buyer’s attitude, and buyer preferences is increasingly being practiced by certain organizations in the ecommerce space[Hai15]. These segmentation approaches are common with most developed countries but not with countries like Qatar where segmentation approach practiced by most ecommerce service providers are either standard or one dimensional. Organizations face major challenges in developing segmentation models to cater to the consumers in a more targeted manner. Conclusions This report was prepared to explore the challenges of developing marketing targeted to different consumer segments in Qatar. It was found that around the world, the concept of multidirectional segmentation has emerged which has several benefits for an ecommerce organization as it helps them in understanding consumers better. However, Qatar based ecommerce organizations still lack advanced segmentation capabilities. This research would thus explore various types of segmentations used by Qatar based ecommerce companies and how these segments are specifically targeted by organizations in marketing to take the benefits. References Cor10: , (Pelău & Bena, 2010), Deb151: , (Burman & Aggrawal, 2015), Jun12: , (Watada, et al., 2012), Hon02: , (Ha, 2002), Placeholder8: , (Lee, et al., 2005), For152: , (Forte Wares , 2015), ZNO13: , (ZNODE, 2013), Hai15: , (Ma, 2015), Read More
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