This project’s goal is to understand, why the consumers abandon the shopping carts, which results in the sale of $10 Million i.e., an increase in Lotte.com. The Lotte.com is the main web based shopping center in Korea. This web based shopping center has in excess of 13 million clients and it has built up an incorporated web movement investigation system by utilizing the SAS. The SAS system is utilized for client encounter investigation. Along these lines, this internet shopping center can enhance the online experience for their clients and create the great comes back from their showcasing efforts. So, lotte.com decided to implement the SAS for customer experience analytics solutions to improve the sales and satisfy the customer needs. This system is used for executives, this can confirm the results anytime, anywhere and make the immediate changes. Each day, more than one million web site visitors are view the Lotte.com. Along these lines, it has to realize the Lottie is have to recognize what number of guests are making the buys and which channel is bringing the most significant movement. Once, surveying the numerous different the methodologies and solutions, the lottie.com presented the incorporated web movement examination system by utilizing the SAS investigation solution.
The Lotte.com is the main web based shopping center in Korea. This web based shopping center has in excess of 13 million clients and it has built up an incorporated web movement investigation system by utilizing the SAS. The SAS system is utilized for client encounter investigation. Along these lines, this internet shopping center can enhance the online experience for their clients and create the great comes back from their showcasing efforts. So, lotte.com decided to implement the SAS for customer experience analytics solutions to improve the sales and satisfy the customer needs. This system is used for executives can confirm the results anytime, anywhere and make the immediate changes. Each day, more than one million web site visitors are view the Lotte.com. So, it needs to know the Lottie is need to identify the number of visitors are purchasing, then which channel brings the extremely valuable traffic. Once, various diverse approaches and solutions are reviewed, the lottie.com has introduced an integrated web traffic analysis system, with the help of SAS analytics solution (Balaraman & Chandrasekar, 2016).
In Korea, such a system is the first online conducting investigation system connected with web based shopping center. This system effectively measure and break down the site guest numbers, buys and site visit status of the site guests. It likewise break down the fame of each item and its class and that’s only the tip of the iceberg. This investigate data are utilized to empowers the better comprehend the client and its conduct on the web and direct the modern, savvy focused on advertising. The SAS system is utilized to enhance the online encounters for their clients and produce the better comes back from its showcasing efforts (Fjermestad, Kudyba & Lawrence, 2018).
The lotte.com website is requires to build the customer behaviour analysis database to measures every visitor, improve the site efficiency, what pages are visited, what are the activities that are undertaken for enabling diverse analysis, and how visitors are navigate the website. And, the database also captures the number of orders, number of attempts, shopping cart conversion rate and size and customer demographic information. Examining the request preparing stage deflects the most clients and settling those stages change rates can be expanded in light of the fact that, at the point where breakaway happens, client conduct can be figure and advanced promoting exercises can be attempted. Along these lines, plays out the example examination of guests to affect the buys can be all the more successfully and mirrored the client request continuously to guarantee the earlier reactions.
The lotte.com website is requires to build the customer behaviour analysis database to measures every visitor, improve the site efficiency, what pages are visited, what are the activities that are undertaken for enabling diverse analysis, and how visitors are navigate the website because the current system does not provide the effective information about the customer details and it does not provide web side efficiency. And, the website database does not captures the number of orders, number of attempts, shopping cart conversion rate and size and customer demographic information. This problem is leads to decrease the sales. So, lotte.com needs to build the customer behaviour analysis to improve the sales and customer satisfaction (K & Venkatapathy, 2014).
The distinguished issues are requirements to lessen by actualized the proposed SAS system for Lotte.com. The SAS system is utilized to advance the advertising productivity examination. The current system is simply investigating the guest numbers just be that as it may, the SAS system is fit for dissecting the change rate like list of things to get, buy consummation, prompt buy, shopping basket contrasted with real guests for each battle type. This system likewise affirm that most mainstream look words utilized by the site guests for each acquired things, crusade type, and area. This system additionally decide the overlay capacity to gauge the quantity of snaps and number of guests for every item present in the page for deciding the incentive of each area of the page. This benefits are used to enables the lotte.com to renew and replace the low traffic products (Kirby-Hawkins, Birkin & Clarke, 2018).
The proposed SAS system is used to enhance the satisfaction of customer and their experience leads to increased sales, because the lotte.com website is requires to build the customer behaviour analysis database to measures every visitor, improve the site efficiency, what pages are visited, what are the activities that are undertaken for enabling diverse analysis, and how visitors are navigate the website. And, the database also captures the number of orders, number of attempts, shopping cart conversion rate and size and customer demographic information. Examining the request preparing stage deflects the most clients and settling those stages change rates can be expanded in light of the fact that, at the point where breakaway happens, client conduct can be figure and advanced promoting exercises can be attempted. Along these lines, plays out the example examination of guests to affect the buys can be all the more successfully and mirrored the client request continuously to guarantee the earlier reactions. So, satisfaction of customer has improved as lotte website and also good insight into each customer interest, needs and behaviours (Konasani & Kadre, 2015).
Finally, Evaluating the SAS system is used for determining the customer service improvement and the subjects of target marketing. Such system also helps in the success of various campaigns. Also, this system has most popular benefits to gain insight into the individual customer and various customer groups. It also achieved the better customer experiences, targeted channel marketing and navigate throughout the web page. And, also provided the information about the customer which is leads to provide the understanding of the customers’ needs and interests. This system successfully identifying the shopping cart abandonment to increases the first year sales is 8 million euros. The SAS system for customer experience analytics was implemented to increases the sales (Schniederjans, Schniederjans & Starkey, 2015).
The lotte.com website is successfully improve the sales by use the SAS analytics. The Lotte.com is build the customer behaviour analysis database to measures every visitor, improve the site efficiency, what pages are visited, what activities are undertaken to enable the diverse analysis and how visitors are navigate the website. And, the database also captures the number of orders, number of attempts, shopping cart conversion rate and size and customer demographic information. Examining the request preparing stage deflects the most clients and settling those stages change rates can be expanded in light of the fact that, at the point where breakaway happens, client conduct can be figure and advanced promoting exercises can be attempted. Along these lines, plays out the example examination of guests to affect the buys can be all the more successfully and mirrored the client request continuously to guarantee the earlier reactions. So, satisfaction of customer has improved as lotte website and also good insight into each customer interest, needs and behaviours.
The proposed SAS system is used to enhance the satisfaction and experience of the customers which leads to increased sales. It successfully build the customer behaviour analysis database to measures every visitor, improve the site efficiency, what pages are visited, what are the activities that are undertaken for enabling diverse analysis, and how visitors are navigate the website. And, the database also captures the number of orders, number of attempts, shopping cart conversion rate and size and customer demographic information. Analysing the order processing stage deters the most customers and fixing those stages conversion rates can be increased because, at the point where breakaway occurs, customer behaviour can be forecast and sophisticated marketing activities can be undertaken. So, performs the pattern analysis of visitors to influenced the purchases can be more effectively and reflected the customer demand in real time to ensure the quicker responses. So, customer satisfaction is improvised with the lotte website and also good insight into each customer interest, needs and behaviours.
Lotte online shopping mall is capable of improving the online experience for its customers, to generate good returns from its marketing campaigns. So, lotte.com has decided to implement, SAS for providing customer experience analytics solutions, which improves the sales and satisfy the customer needs. This system mainly is used for executives, this can confirm the results anytime, anywhere and make the immediate changes. Each day, more than one million web site visitors are view the Lotte.com. Thus, it has to realize the Lottie is have to distinguish what number of guests are making the buys and which channel is bringing the most profitable movement. Once, investigating the numerous various the methodologies and solutions, the lottie.com presented the coordinated web movement examination system by utilizing the SAS examination solution. And, lotte.com website is requires to build the customer behaviour analysis database to measures every visitor, improve the site efficiency, what pages are visited, what are the activities that are undertaken for enabling the diverse analysis, and how visitors are navigate the website because the current system does not provide the effective information about the customer details and it does not provide web side efficiency. And, the website database does not captures the number of orders, number of attempts, shopping cart conversion rate and size and customer demographic information. This problem is leads to decrease the sales. So, lotte.com needs to build the customer behaviour analysis to improve the sales and customer satisfaction.
Yes, the companies of E-commerce are now in a better position, for leveraging the benefits of analytics. For example, in prompt intelligent shopping, the intuitive shopping goes for client reliability. Mix of an online coordination’s stage keeps up end-to-end deceivability of buys and requests, and business insight programming helps process client exchange information. It likewise empowers retailers to offer different conveyance alternatives, and can prompt clients for extra buys dependent on their purchasing behaviours. Predictable client benefit, combined with innovation, can incredibly build client firm quality. In analytics, empowers organizations to be more proactive and settle on learning driven choices by burdening robotized and planned information. It enables retailers to comprehend the requirements and interests of their clients continuously. Further, it recognizes client catchwords, which can be investigated to distinguish potential zones of venture and cost-cutting (Svolba, 2012).
Conclusion
This project successfully provided the understanding of the why the consumers abandon the shopping carts, which results in the sale of $10 Million i.e., an increase in Lotte.com. It has introduced the integrated web traffic analysis system, with the help of SAS. The SAS system is used for customer experience analytics. This system successfully improvised customers’ experience on online shopping also it has generated good returns from its marketing campaigns. This system is used for executives can confirm the results anytime, anywhere and make the immediate changes. The lottie.com is presented the incorporated web activity examination system by utilizing the SAS investigation solution. The SAS system is utilized to decide the client benefit enhancement and target advertising subjects. This system additionally supported the achievement of various battles. Likewise, this system has most prevalent advantages is picking up the knowledge into the individual client and different client gatherings. It also achieved the better customer experiences, targeted channel marketing and navigate throughout the web page. And, also provided the information about the customer which is leads to provide the understanding of the customers’ needs and interests. This system successfully identifying the shopping cart abandonment to increases the first year sales is 8 million euros. The SAS system for customer experience analytics was implemented to increases the sales.
References
Balaraman, P., & Chandrasekar, S. (2016). E-Commerce Trends and Future Analytics Tools. Indian Journal Of Science And Technology, 9(32). doi: 10.17485/ijst/2016/v9i32/98653
Fjermestad, J., Kudyba, S., & Lawrence, K. (2018). Business intelligence and analytics case studies. Journal Of Organizational Computing And Electronic Commerce, 28(2), 77-78. doi: 10.1080/10919392.2018.1444360
K, A., & Venkatapathy, S. (2014). A data-agnostic dashboard visualization system with customizable layout for e-commerce data analytics. ACM SIGSOFT Software Engineering Notes, 39(4), 1-5. doi: 10.1145/2632434.2632444
Kirby-Hawkins, E., Birkin, M., & Clarke, G. (2018). An investigation into the geography of corporate e-commerce sales in the UK grocery market. Environment And Planning B: Urban Analytics And City Science, 239980831875514. doi: 10.1177/2399808318755147
Konasani, V., & Kadre, S. (2015). Practical Business Analytics Using SAS. Berkeley, CA: Apress.
Schniederjans, M., Schniederjans, D., & Starkey, C. (2015). Business analytics principles, concepts, and applications with SAS. Upper Saddle River, NJ: Pearson Pub.
Sharma, N., & Dadhich, M. (2014). Predictive Business Analytics: The Way Ahead. Journal Of Commerce And Management Thought, 5(4), 652. doi: 10.5958/0976-478x.2014.00012.3
Svolba, G. (2012). Data quality for analytics using SAS. Cary, N.C.: SAS Institute.
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