1. The document discusses the importance of context-aware recommender systems for one-to-one marketing in e-commerce. Traditionally, recommender systems use collaborative filtering or content-based recommendations without considering the context or situation of a customer's purchase.
2. It proposes that recommender systems should take into account the "embodied knowledge" or context of customers' online shopping behavior in order to improve marketing strategies and increase sales. Capturing contextual information could help create perceptions of trust, value and relevance to better satisfy customer needs.
3. Recommender systems are currently built from a "seller-centric" view rather than considering customer perspectives and contexts. Incorporating contextual factors could help elicit positive customer
This study all about Customer preference in online grocery shopping of Divino Food International Pvt Ltd. Presently multi day, Customer has changed because of consistent change in business condition. This adjustment in the earth, requests increasingly advancement of the time. Buyer purchasing conduct has changed from accommodation to comfort what's more, from purchasing in stores to purchasing on the web notwithstanding purchasing from wide screen to purchasing little screen i.e. move frame windows PC to Android/Device. The present situation is the time of retailing. There is a change in outlook of purchasers moving from commercial center to advertise space. Buyers presently want to shop items online over traditional strategies for shopping in stores. Web based shopping has turned into the third generally well known web action, quickly following email Using/texting and web perusing. Subsequently this investigation expects to know the client inclination towards web based shopping in Bangalore with test respondents of 52.
This document summarizes a research study that examined how consumer participation when using online recommendation agents (RAs) affects satisfaction, trust, and purchase intentions. The study hypothesized that greater participation when using an RA would lead to higher satisfaction and trust in the RA and its recommendations. It also proposed that financial risk associated with products would reduce satisfaction, trust and purchase intentions, and moderate the effects of participation. The findings were intended to provide insights for marketing strategy regarding how to design RAs and the role of participation and risk.
1) A field experiment was conducted at an electronics retail store to examine if giving customers a gift coupon during a sales pitch would increase the likelihood of them purchasing a computer and the amount they would spend.
2) Customers were randomly assigned to one of three conditions that varied the discount amount provided (no discount, 10% off, or 10% + 5% off).
3) The results showed that while the 10% + 5% off condition approached a significant effect on purchase likelihood, overall the reciprocity manipulation did not significantly affect purchase rates or spending amounts. However, some trends in the data suggested reciprocity may have had an effect warranting further research.
presentation on e-marketing research process , data driven strategy , SDS model , Knowledge Management, social media monitaring, electronic marketing information system , facts and figures about social media
E satisfaction e-loyalty of consumers shopping onlineAbu Bashar
With the advent of information technologies and emergence of online stores, the
online shopping has not been the same as it was in the past. Now in order to strive
in this cut throat competition it is of vital importance for the organizations to
understand the factors that matter for consumers when they shop online. As the
competition in e-commerce is intensified, it becomes more important for online
retailers to understand the antecedents of consumer acceptance of online
shopping. Such knowledge is essential to customer relationship management,
which has been recognized as an effective business strategy to achieve success
in the electronic market. The current research study is an effort to understand
the satisfaction and loyalty pattern for the consumers shopping online. The objective
of this research is to study the impact of emotional state and perceived risk of
remote purchase on e-satisfaction during the Internet shopping. As well, it aims
to study the influence of e-satisfaction on e-loyalty. The data gathering was carried
out by a questionnaire. The results show that three dimensions of the emotional
state during Internet shopping (the pleasure, stimulation and dominance) have a
significant positive impact on e-satisfaction. Dimensions of the perceived risk of
remote purchase, (the total risk, the financial risk, the social risk, the
psychological risk, the functional risk, and the physical risk) don't have a significant
impact on e-satisfaction, except the risk of loss of time has a negative impact.
Finally satisfaction influences positively and significantly the e-loyalty of the cyber
consumers.
This document summarizes a research paper on online shopping behavior in Turkey. The paper studied over 900 online shoppers in Eskisehir, Turkey to understand their demographic traits and online shopping behaviors. It tested several hypotheses, including that frequent online shoppers are more price sensitive, auctions can lead to impulse purchases, and website loyalists prefer online shopping. The analyses found support for some hypotheses but not others. Factor analysis was used to reduce 24 variables measuring attitudes and behaviors into 7 components to analyze relationships between variables.
Consumer decision making in online environment : The effect of interactive d...Giang Coffee
Despite the explosive growth of electronic commerce and the
rapidly increasing number of consumers who use interactive
media (such as the World Wide Web) for prepurchase information search and online shopping, very little is known
about how consumers make purchase decisions in such settings. A unique characteristic of online shopping environments is that they allow vendors to create retail interfaces
with highly interactive features. One desirable form of interactivity from a consumer perspective is the implementation
of sophisticated tools to assist shoppers in their purchase decisions by customizing the electronic shopping environment
to their individual preferences. The availability of such
tools, which we refer to asinteractive decision aidsfor consumers, may lead to a transformation of the way in which shoppers search for product information and make purchase decisions. The primary objective of this paper is to investigate
the nature of the effects that interactive decision aids may
have on consumer decision making in online shopping
environments
This study all about Customer preference in online grocery shopping of Divino Food International Pvt Ltd. Presently multi day, Customer has changed because of consistent change in business condition. This adjustment in the earth, requests increasingly advancement of the time. Buyer purchasing conduct has changed from accommodation to comfort what's more, from purchasing in stores to purchasing on the web notwithstanding purchasing from wide screen to purchasing little screen i.e. move frame windows PC to Android/Device. The present situation is the time of retailing. There is a change in outlook of purchasers moving from commercial center to advertise space. Buyers presently want to shop items online over traditional strategies for shopping in stores. Web based shopping has turned into the third generally well known web action, quickly following email Using/texting and web perusing. Subsequently this investigation expects to know the client inclination towards web based shopping in Bangalore with test respondents of 52.
This document summarizes a research study that examined how consumer participation when using online recommendation agents (RAs) affects satisfaction, trust, and purchase intentions. The study hypothesized that greater participation when using an RA would lead to higher satisfaction and trust in the RA and its recommendations. It also proposed that financial risk associated with products would reduce satisfaction, trust and purchase intentions, and moderate the effects of participation. The findings were intended to provide insights for marketing strategy regarding how to design RAs and the role of participation and risk.
1) A field experiment was conducted at an electronics retail store to examine if giving customers a gift coupon during a sales pitch would increase the likelihood of them purchasing a computer and the amount they would spend.
2) Customers were randomly assigned to one of three conditions that varied the discount amount provided (no discount, 10% off, or 10% + 5% off).
3) The results showed that while the 10% + 5% off condition approached a significant effect on purchase likelihood, overall the reciprocity manipulation did not significantly affect purchase rates or spending amounts. However, some trends in the data suggested reciprocity may have had an effect warranting further research.
presentation on e-marketing research process , data driven strategy , SDS model , Knowledge Management, social media monitaring, electronic marketing information system , facts and figures about social media
E satisfaction e-loyalty of consumers shopping onlineAbu Bashar
With the advent of information technologies and emergence of online stores, the
online shopping has not been the same as it was in the past. Now in order to strive
in this cut throat competition it is of vital importance for the organizations to
understand the factors that matter for consumers when they shop online. As the
competition in e-commerce is intensified, it becomes more important for online
retailers to understand the antecedents of consumer acceptance of online
shopping. Such knowledge is essential to customer relationship management,
which has been recognized as an effective business strategy to achieve success
in the electronic market. The current research study is an effort to understand
the satisfaction and loyalty pattern for the consumers shopping online. The objective
of this research is to study the impact of emotional state and perceived risk of
remote purchase on e-satisfaction during the Internet shopping. As well, it aims
to study the influence of e-satisfaction on e-loyalty. The data gathering was carried
out by a questionnaire. The results show that three dimensions of the emotional
state during Internet shopping (the pleasure, stimulation and dominance) have a
significant positive impact on e-satisfaction. Dimensions of the perceived risk of
remote purchase, (the total risk, the financial risk, the social risk, the
psychological risk, the functional risk, and the physical risk) don't have a significant
impact on e-satisfaction, except the risk of loss of time has a negative impact.
Finally satisfaction influences positively and significantly the e-loyalty of the cyber
consumers.
This document summarizes a research paper on online shopping behavior in Turkey. The paper studied over 900 online shoppers in Eskisehir, Turkey to understand their demographic traits and online shopping behaviors. It tested several hypotheses, including that frequent online shoppers are more price sensitive, auctions can lead to impulse purchases, and website loyalists prefer online shopping. The analyses found support for some hypotheses but not others. Factor analysis was used to reduce 24 variables measuring attitudes and behaviors into 7 components to analyze relationships between variables.
Consumer decision making in online environment : The effect of interactive d...Giang Coffee
Despite the explosive growth of electronic commerce and the
rapidly increasing number of consumers who use interactive
media (such as the World Wide Web) for prepurchase information search and online shopping, very little is known
about how consumers make purchase decisions in such settings. A unique characteristic of online shopping environments is that they allow vendors to create retail interfaces
with highly interactive features. One desirable form of interactivity from a consumer perspective is the implementation
of sophisticated tools to assist shoppers in their purchase decisions by customizing the electronic shopping environment
to their individual preferences. The availability of such
tools, which we refer to asinteractive decision aidsfor consumers, may lead to a transformation of the way in which shoppers search for product information and make purchase decisions. The primary objective of this paper is to investigate
the nature of the effects that interactive decision aids may
have on consumer decision making in online shopping
environments
This document discusses online marketing and how it compares to traditional marketing. Online marketing uses the internet and digital media to reach customers, reducing costs and allowing for more interactivity and targeted campaigns. It describes common online marketing strategies like affiliate marketing, email marketing, viral marketing, search engine marketing, and referral marketing. The document also notes benefits of online marketing like cost savings, global reach, and always being available, as well as potential limitations like requiring new technology and an inability to physically see products before buying.
The document discusses segmenting the internet market in Cameroon. It defines internet market segmentation and target market. Possible traditional segments include geographic, demographic, psychographic, and behavioral factors. Local realities suggest also considering gender, price, interests, location, religion, income, and household size. The market could be segmented into students/children, adults, professionals, and corporations. Further segmentation is proposed into four target groups: Home Riders, Generational Adventurers, Transit Masters, and Hot Sellers. Each group has different needs and motivations for internet usage.
Factors Influencing the E-Shoppers Perception towards E-Shopping (A Study wit...Dr. Amarjeet Singh
Purpose: The study focuses on identifying and exploring the various factors influencing the e-shoppers perception towards e-shopping.
Design / methodology / approach: A research model is developed based on the literature. For the purpose of study data collected from 100 e-shoppers belonged to Wardha City of Maharashtra. By using in structured questionnaire, descriptive statistical measure like mean has been used for analyzing the data.
Findings: The results reveal that the seven key factors like convenience, time saving, home delivery, price advantage, more choice, reliability and security significantly influenced the e-shoppers perception on e-shopping.
Contribution of the study: The result of this study provides a valuable reference to the e-marketers to understand the factors influencing e-shoppers perception. They can further sharpen their marketing strategies to attract and retain their customers.
A Corpus Driven, Aspect-based Sentiment Analysis To Evaluate In Almost Real-t...CSCJournals
Nowadays, more than ever, customers have access to other consumers’ digital evaluations concerning the products or services that they have consumed. The use of online review websites, by the potential digital consumers, makes them aware of the choices they have. This, enables them to make comparisons between all the available products or services. However, the big volume of the opinionative data that is produced continuously, creates difficulties when being analyzed by stakeholders, mostly due to human’s physical or mental restrictions. In this research, web scraping combined with an aspect-level sentiment analysis using the corpus-based technique, approached methodologically the problem, by identifying not only the relevant information, but also the particular expressions and phrases that the reviewers use over the Internet. The purpose is to recommend a corpus-based, sentiment analysis web system for detecting and quantifying customers’ opinions which are written in Greek language and referred to the Food and Beverage (F&B) sector in almost real-time. The system consists of two modules that constructed using the aforementioned methods. As far as the web scraping module is concerned, the BeautifulSoup and the Requests libraries of Python programming language were used. For the constructing purposes of the corpus-based sentiment analysis module, 80,500 customers’ reviews are extracted (data set) from 6,795 companies which selected randomly from the most popular Greek e-ordering platform. The evaluated functions are the quality of food, the customer service and the image of the company. The extracted sentiment orientation terms and phrases from the customers’ reviews are used to form the corresponding dictionaries of the functions and the appropriate pattern of tags, in order to proceed in the sentiment classification. Finally, the system is tested in the dataset and the findings will be practical and significant, as not enough attention has been paid in sentiment analysis techniques used in combination with a non-English, like the modern Greek language.
Analytical CRM - Ecommerce analysis of customer behavior to enhance sales Shrikant Samarth
Task: You are required to choose a dataset (or related datasets) in an area of interest suitable for analyzing customer relationships.
Approach: Topic is chosen – Customer behavior Analysis in Ecommerce Industry for Enhancing Sales. Brazilian E-commerce public dataset was downloaded, cleaned and performed multiple regression in SPSS to check the relationship between the dependent variable and multiple independent variables.
Findings: Customer can be retained if the product delivered in time and if there is a delay in the product delivery, it is a duty of a seller to inform the customer for the same. The payment method has proven to be an important parameter to enhance sales over a period of time. analysis suggests on-time delivery, flexibility in payment method and good customer service would help the seller to gain customer trust which would help them to convert more sales.
Tools: IBM SPSS , Excel (pivot tables and charts), Tableau
This document discusses consumer behavior in electronic commerce. It begins by outlining learning objectives related to describing consumer behavior online, characteristics of internet users, and the consumer decision making process. It then provides details on Ritchey Bikes improving their website to better understand customer wants and needs through surveys. The document also discusses models of consumer behavior online, characteristics and demographics of internet users, the consumer purchasing process, matching products to customers through personalization, delivering customer service, and conducting market research online. Intelligent agents are also described for assisting customers with tasks like identifying needs, product comparisons, and negotiating transactions.
Mathematical Assessment of “Blogging Effect” on Consumer Buying Behaviorijbiss
The Internet has escorted in mammothalterations in the marketing strategy by coalescing many diversities of business models involving affiliate marketing, direct sales, viral marketing and marketing online. It has been evidenced that blogs play an imperative role in facilitating customers to form a buying decision. In fact, blogs have an upshot on purchase behavior far more than the social networking platforms. Blogs have unremittingly garnered a reliable audience. When the demonstrative bond between the blogger and the consumers gets very substantial, it can lead the latter to really build a buying decision. The impact of blogs is so intense that it is sometimes stated as “Blogging Effect” on buying behavior. The present study is an endeavor to derive the two important mathematical instigation of the “blogging effect”
In this presentation we will discuss the importance of internet marketing, How internet related to business, and many more interesting topic related to internet.
Moving Beyond Social CRM with the Customer Brand ScoreCognizant
Travel and hospitality organizations can boost customer loyalty by better understanding customer behaviors and attitudes and leveraging social media to create an army of brand advocates.
Analyzing the opportunities of digital marketing in bangladesh to provide an ...IJMIT JOURNAL
The idea of marketing recently converging to Digital marketing and digital marketing is becoming the most effective means for building business-customer relationships with long-term loyalty. It is a matter of concern that how this convergence is taking place in developing countries like Bangladesh. In this paper, the impact of digital marketing on the customer engagement with products and brands is investigated using descriptive research method and is based on survey. This study attempts to find the most effective form of digital marketing in Bangladesh by taking responses using questionnaires from sample, which has been used as the primary data. This study aims to discover the factors that work background to make the customers loyal to the brand and to have a positive attitude toward brand. It also illustrates about the differences of traditional marketing and digital marketing and the changes brought by digital marketing in brands relationship marketing. Analysis of survey output shows that there is an overall positive influence of internet advertising on consumer purchase decision. It is recommended that companies should conduct a market research on different markets in various countries to identify more specific market related and regional factors.
The document summarizes a case study on online shopping in Malaysia. It discusses the significance of understanding consumer attitudes and behaviors towards online shopping. It describes the methodology used, which was a questionnaire, and outlines the findings regarding consumer demographics, internet usage, attitudes towards online shopping, vendor characteristics, and website quality. Statistical analysis was conducted to analyze the data and test hypotheses.
The internet is being developed rapidly since last two decades, and with relevant digital economy that is driven by information technology also being developed worldwide. After a long term development of internet, which rapidly increased web users and highly speed internet connection, and some new technology also have been developed and used for web developing, those lead to firms can promote and enhance images of product and services through web site. Therefore, detailed product information and improved service attracts more and more people changed their consumer behaviour from the traditional mode to more rely on the internet shopping. On the other hand, more companies have realized that the consumer behaviour transformation is unavoidable trend, and thus change their marketing strategy. As the recent researches have indicated that, the internet shopping particularly in business to consumer (B2C) has risen and online shopping become more popular to many people. According to the report, The Emerging Digital Economy II, published by the US Department of Commerce, in some companies, the weight of e-commerce in total sales is quite high. For instance, the Dell computer company have reached 18 million dollars sales through the internet during the first quarter of 1999. As a result, about 30% of its 5.5 billion dollars total sales were achieved through the internet (Moon, 2004). Therefore, to understand internet shopping and its impact on consumer behaviour could help companies making use of it as a form of doing e-business.
There are many reasons for such a rapid developing of internet shopping, which mainly due to the benefits that internet provides. First of all, the internet offers different kind of convenience to consumers. Obviously, consumers do not need go out looking for product information as the internet can help them to search from online sites, and it also helps evaluate between each sites to get the cheapest price for purchase. Furthermore, the internet can enhance consumer use product more efficiently and effectively than other channels to satisfy their needs. Through the different search engines, consumers save time to access to the consumption related information, and which information with mixture of images, sound, and very detailed text description to help consumer learning and choosing the most suitable product (Moon, 2004). However, internet shopping has potential risks for the customers, such as payment safety, and after service. Due to the internet technology developed, internet payment recently becomes prevalent way for purchasing goods from the internet. Internet payment increase consumptive efficiency, at the same time, as its virtual property reduced internet security. After service is another way to stop customer shopping online. It is not like traditional retail, customer has risk that some after service should face to face serve, and especially in some complicated goods.
IOSR Journal of Business and Management (IOSR-JBM) is an open access international journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
This paper uses the rich features of two data sets obtained from the Alibaba’s Taobao online
shopping site taobao.com. The page view log data file contains the information about the advertisements
displayed after the customer’s search using keyword(s).
This document summarizes a study on the importance of e-brand trust towards customer engagement in digital transformation. The study found that while organizations spend billions on digital transformation to improve customer experiences, trust is critical for digital relationships and driving revenue. Digital connections are still human relationships, so trust forms the foundation for any digital exchange, as it does for personal transactions. The study reviewed literature showing that customers expect customized experiences and will switch providers if not met, breaking trust. It also found that creating trust in the digital world is difficult as organizations must consistently deliver trust across many digital touchpoints. The purpose of the study was to provide insights on the impact of e-brand trust on digital platforms and propose avenues for future research. It followed
This document summarizes a thesis presentation on investigating the impact of advertising appeals on brand attitude, purchase intention, and claim recall in financial institutions. The presentation studied how emotional versus informative appeals influence memory performance and the effects on attitude, intention, and recall. Focus group and survey data were analyzed from 384 participants aged 25-35. Results found that informative appeals were more memorable and preferred over emotional appeals. Memory performance positively impacted brand attitude but negatively influenced purchase intention. The study provided recommendations for financial institution marketers on improving advertising effectiveness and areas for further research.
This document describes a system for cross-site cold-start product recommendation using information from microblogging sites. It proposes using recurrent neural networks to learn correlated feature representations of users and products from e-commerce site data. It also uses modified gradient boosting trees to transform users' microblogging attributes into latent feature representations that can be incorporated into product recommendations. Finally, it applies feature-based matrix factorization to incorporate user and product features for cold-start product recommendations across social and e-commerce sites.
Accenture, comScore and dunnhumbyUSA collaborated on a study to help CPG executives better understand the link between consumers’ usage of brand websites and their brand purchases in retail stores.
This document discusses a study analyzing the relationships between four areas of technology-enabled retail services (content management, customer management, multi-channel management, and visitor traffic management) and the online sales performance of web retailers. The study uses data on the profiles, operations, and sales of the top 500 US web retailers to examine how their implementation of features in these four areas impacts online sales. The results show that content, customer, and multi-channel management features have a significant positive impact on sales, while the impact of visitor traffic management features is inconclusive.
This document summarizes research on factors that influence online shopping decisions. It finds that the marketing communication process differs between offline and online consumer decision making. The key factors that motivate online shopping are convenience, access to information, availability of products and services, and cost/time efficiency. However, some consumers are deterred by issues like security concerns, the inability to see products physically, and lack of social interaction. The document provides implications for online retailers to build trust, offer secure websites, provide attractive and useful information, add customer service features, and give additional purchasing options to appeal to more customers.
The document details data preprocessing and feature engineering steps for a machine learning model to predict West Nile virus presence. It reads in training, test, weather and spraying data, cleans variables, derives new features like distance to locations and week numbers, and splits weather data by station. New weather features like accumulated degree days are created. Moving averages and sums are also calculated for temperature, precipitation, and degree days over 1 and 2 week periods.
This document summarizes a study that analyzed multivariate models to predict the presence or absence of the West Nile virus. Four classification models - logistic regression, linear discriminant analysis, random forests, and support vector machines - were developed using weather, temporal, and spatial factors. An ensemble model that combined the generalized additive model and support vector machine with weights of 0.6 and 0.4, respectively, achieved the best results with an AUC of 0.8361962. The models took into account the developmental stages of mosquitoes to better predict the transmission pattern of the West Nile virus.
This document discusses online marketing and how it compares to traditional marketing. Online marketing uses the internet and digital media to reach customers, reducing costs and allowing for more interactivity and targeted campaigns. It describes common online marketing strategies like affiliate marketing, email marketing, viral marketing, search engine marketing, and referral marketing. The document also notes benefits of online marketing like cost savings, global reach, and always being available, as well as potential limitations like requiring new technology and an inability to physically see products before buying.
The document discusses segmenting the internet market in Cameroon. It defines internet market segmentation and target market. Possible traditional segments include geographic, demographic, psychographic, and behavioral factors. Local realities suggest also considering gender, price, interests, location, religion, income, and household size. The market could be segmented into students/children, adults, professionals, and corporations. Further segmentation is proposed into four target groups: Home Riders, Generational Adventurers, Transit Masters, and Hot Sellers. Each group has different needs and motivations for internet usage.
Factors Influencing the E-Shoppers Perception towards E-Shopping (A Study wit...Dr. Amarjeet Singh
Purpose: The study focuses on identifying and exploring the various factors influencing the e-shoppers perception towards e-shopping.
Design / methodology / approach: A research model is developed based on the literature. For the purpose of study data collected from 100 e-shoppers belonged to Wardha City of Maharashtra. By using in structured questionnaire, descriptive statistical measure like mean has been used for analyzing the data.
Findings: The results reveal that the seven key factors like convenience, time saving, home delivery, price advantage, more choice, reliability and security significantly influenced the e-shoppers perception on e-shopping.
Contribution of the study: The result of this study provides a valuable reference to the e-marketers to understand the factors influencing e-shoppers perception. They can further sharpen their marketing strategies to attract and retain their customers.
A Corpus Driven, Aspect-based Sentiment Analysis To Evaluate In Almost Real-t...CSCJournals
Nowadays, more than ever, customers have access to other consumers’ digital evaluations concerning the products or services that they have consumed. The use of online review websites, by the potential digital consumers, makes them aware of the choices they have. This, enables them to make comparisons between all the available products or services. However, the big volume of the opinionative data that is produced continuously, creates difficulties when being analyzed by stakeholders, mostly due to human’s physical or mental restrictions. In this research, web scraping combined with an aspect-level sentiment analysis using the corpus-based technique, approached methodologically the problem, by identifying not only the relevant information, but also the particular expressions and phrases that the reviewers use over the Internet. The purpose is to recommend a corpus-based, sentiment analysis web system for detecting and quantifying customers’ opinions which are written in Greek language and referred to the Food and Beverage (F&B) sector in almost real-time. The system consists of two modules that constructed using the aforementioned methods. As far as the web scraping module is concerned, the BeautifulSoup and the Requests libraries of Python programming language were used. For the constructing purposes of the corpus-based sentiment analysis module, 80,500 customers’ reviews are extracted (data set) from 6,795 companies which selected randomly from the most popular Greek e-ordering platform. The evaluated functions are the quality of food, the customer service and the image of the company. The extracted sentiment orientation terms and phrases from the customers’ reviews are used to form the corresponding dictionaries of the functions and the appropriate pattern of tags, in order to proceed in the sentiment classification. Finally, the system is tested in the dataset and the findings will be practical and significant, as not enough attention has been paid in sentiment analysis techniques used in combination with a non-English, like the modern Greek language.
Analytical CRM - Ecommerce analysis of customer behavior to enhance sales Shrikant Samarth
Task: You are required to choose a dataset (or related datasets) in an area of interest suitable for analyzing customer relationships.
Approach: Topic is chosen – Customer behavior Analysis in Ecommerce Industry for Enhancing Sales. Brazilian E-commerce public dataset was downloaded, cleaned and performed multiple regression in SPSS to check the relationship between the dependent variable and multiple independent variables.
Findings: Customer can be retained if the product delivered in time and if there is a delay in the product delivery, it is a duty of a seller to inform the customer for the same. The payment method has proven to be an important parameter to enhance sales over a period of time. analysis suggests on-time delivery, flexibility in payment method and good customer service would help the seller to gain customer trust which would help them to convert more sales.
Tools: IBM SPSS , Excel (pivot tables and charts), Tableau
This document discusses consumer behavior in electronic commerce. It begins by outlining learning objectives related to describing consumer behavior online, characteristics of internet users, and the consumer decision making process. It then provides details on Ritchey Bikes improving their website to better understand customer wants and needs through surveys. The document also discusses models of consumer behavior online, characteristics and demographics of internet users, the consumer purchasing process, matching products to customers through personalization, delivering customer service, and conducting market research online. Intelligent agents are also described for assisting customers with tasks like identifying needs, product comparisons, and negotiating transactions.
Mathematical Assessment of “Blogging Effect” on Consumer Buying Behaviorijbiss
The Internet has escorted in mammothalterations in the marketing strategy by coalescing many diversities of business models involving affiliate marketing, direct sales, viral marketing and marketing online. It has been evidenced that blogs play an imperative role in facilitating customers to form a buying decision. In fact, blogs have an upshot on purchase behavior far more than the social networking platforms. Blogs have unremittingly garnered a reliable audience. When the demonstrative bond between the blogger and the consumers gets very substantial, it can lead the latter to really build a buying decision. The impact of blogs is so intense that it is sometimes stated as “Blogging Effect” on buying behavior. The present study is an endeavor to derive the two important mathematical instigation of the “blogging effect”
In this presentation we will discuss the importance of internet marketing, How internet related to business, and many more interesting topic related to internet.
Moving Beyond Social CRM with the Customer Brand ScoreCognizant
Travel and hospitality organizations can boost customer loyalty by better understanding customer behaviors and attitudes and leveraging social media to create an army of brand advocates.
Analyzing the opportunities of digital marketing in bangladesh to provide an ...IJMIT JOURNAL
The idea of marketing recently converging to Digital marketing and digital marketing is becoming the most effective means for building business-customer relationships with long-term loyalty. It is a matter of concern that how this convergence is taking place in developing countries like Bangladesh. In this paper, the impact of digital marketing on the customer engagement with products and brands is investigated using descriptive research method and is based on survey. This study attempts to find the most effective form of digital marketing in Bangladesh by taking responses using questionnaires from sample, which has been used as the primary data. This study aims to discover the factors that work background to make the customers loyal to the brand and to have a positive attitude toward brand. It also illustrates about the differences of traditional marketing and digital marketing and the changes brought by digital marketing in brands relationship marketing. Analysis of survey output shows that there is an overall positive influence of internet advertising on consumer purchase decision. It is recommended that companies should conduct a market research on different markets in various countries to identify more specific market related and regional factors.
The document summarizes a case study on online shopping in Malaysia. It discusses the significance of understanding consumer attitudes and behaviors towards online shopping. It describes the methodology used, which was a questionnaire, and outlines the findings regarding consumer demographics, internet usage, attitudes towards online shopping, vendor characteristics, and website quality. Statistical analysis was conducted to analyze the data and test hypotheses.
The internet is being developed rapidly since last two decades, and with relevant digital economy that is driven by information technology also being developed worldwide. After a long term development of internet, which rapidly increased web users and highly speed internet connection, and some new technology also have been developed and used for web developing, those lead to firms can promote and enhance images of product and services through web site. Therefore, detailed product information and improved service attracts more and more people changed their consumer behaviour from the traditional mode to more rely on the internet shopping. On the other hand, more companies have realized that the consumer behaviour transformation is unavoidable trend, and thus change their marketing strategy. As the recent researches have indicated that, the internet shopping particularly in business to consumer (B2C) has risen and online shopping become more popular to many people. According to the report, The Emerging Digital Economy II, published by the US Department of Commerce, in some companies, the weight of e-commerce in total sales is quite high. For instance, the Dell computer company have reached 18 million dollars sales through the internet during the first quarter of 1999. As a result, about 30% of its 5.5 billion dollars total sales were achieved through the internet (Moon, 2004). Therefore, to understand internet shopping and its impact on consumer behaviour could help companies making use of it as a form of doing e-business.
There are many reasons for such a rapid developing of internet shopping, which mainly due to the benefits that internet provides. First of all, the internet offers different kind of convenience to consumers. Obviously, consumers do not need go out looking for product information as the internet can help them to search from online sites, and it also helps evaluate between each sites to get the cheapest price for purchase. Furthermore, the internet can enhance consumer use product more efficiently and effectively than other channels to satisfy their needs. Through the different search engines, consumers save time to access to the consumption related information, and which information with mixture of images, sound, and very detailed text description to help consumer learning and choosing the most suitable product (Moon, 2004). However, internet shopping has potential risks for the customers, such as payment safety, and after service. Due to the internet technology developed, internet payment recently becomes prevalent way for purchasing goods from the internet. Internet payment increase consumptive efficiency, at the same time, as its virtual property reduced internet security. After service is another way to stop customer shopping online. It is not like traditional retail, customer has risk that some after service should face to face serve, and especially in some complicated goods.
IOSR Journal of Business and Management (IOSR-JBM) is an open access international journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
This paper uses the rich features of two data sets obtained from the Alibaba’s Taobao online
shopping site taobao.com. The page view log data file contains the information about the advertisements
displayed after the customer’s search using keyword(s).
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Grading Guide
Content
60 Percent
Points Earned
X/3
· Presents a clear definition of the selected disorder
· Discusses the causes and symptoms
· Addresses the biological and social ramifications
· Discusses prevalence, age of onset and gender differences
· Evaluate treatments
Comments:
Organization and Development
20 Percent
Points Earned
X/1
· The paper is 700 to 1,050 words.
· The paper is clear and organized; major points are supported by details, examples, or analysis.
· The paper uses visual and auditory aids appropriately and effectively.
· The paper effectively incorporates design elements, such as font, color, headings, and spacing.
· The paper is logical, flows, and reviews the major points.
Comments:
Mechanics and Format
20 Percent
Points Earned
X/1
· The assignment file is presentable and functional; for example, the audio clips are audible, visual components are viewable, and links work appropriately.
· Rules of grammar, usage, and punctuation are followed; spelling is correct throughout the presentation.
· The presentation is consistent with APA guidelines.
Comments:
Additional Comments:
Total Earned
X/5
database marketing
John A. McCarty
INTRODUCTION
Database marketing involves the analysis of cust-
omer transaction data, along with other customer
information (e.g., demographics), to segment
customers (see MARKET SEGMENTATION AND
TARGETING), and to develop marketing strate-
gies (see MARKETING STRATEGY) to some or all
of those segments. A key aspect of this descrip-
tion is that database marketing almost always
involves the analysis of transaction data, either
alone or with other kinds of customer data.
Transaction data include information about the
actual purchases made by consumers, such as
when a purchase was made, the assortment of
items that were purchased, and the total amount
that was spent during a particular purchase.
Thus, database marketing is generally employed
by marketers having access to such information
about individual customers, including catalog
marketers, retailers, credit card companies, and
others that engage in direct contact of one sort or
another with customers. Nonprofits (e.g., char-
ities, associations) have also utilized database
marketing. A charity, for example, has infor-
mation about donors, including how much they
have donated over the years, the amount of their
largest donation, and the number of times they
have donated.
Among marketing firms, direct marketers
(e.g., L.L. Bean) were the first to employ
database marketing techniques. Their earliest
efforts were largely informal in that direct
marketers tended to note the patterns and
preferences of their customers and to utilize
knowledge of these in their marketing to repeat
customers (Baier, Ruf, and Chakraborty, 2002).
As the number of customers for these firms
grew to a level that would make such informal
methods impractical, computers and analytical
procedures were developing that could automate
the tracking of custom ...
The document discusses online versus traditional marketing and its impact on consumer behavior. It begins by outlining the customer buying cycle and how online marketing compares to traditional marketing across the four Ps - product, price, place, and promotion. While online marketing provides greater product selection and faster communication, traditional marketing allows customers to see and feel products in person. The document then examines the research aim and objectives, which are to investigate the impact of different marketing approaches on consumer behavior, especially for men's clothing at Marks & Spencer. Finally, the methodology and data collection process are described.
The document discusses online shopping and consumer behavior related to online purchases. It begins by defining online shopping as purchasing goods and services directly from sellers over the internet without an intermediary. It notes that online shopping allows consumers to shop from home and purchase a variety of items. However, it also discusses issues with fraudulent activities and fears among consumers. The objectives of the study are to understand consumer satisfaction levels with online purchases and the reasons for purchasing online. It will use a descriptive research methodology with a sample size of 50 respondents selected through convenient sampling to understand consumer behaviors related to online shopping.
To Understand the Eco-System in Digital Media Marketing.Saurabh Giratkar
Title of the Dissertation Report is “To Understand the ecosystem of digital media marketing” and Objectives of the Dissertation are to understand the change in consumer buying behavior in digital era. Methodology used for achieving these objectives is a exploratory research. For achieving the objective, I have done one research using an online questionnaire. The title for the research is “Understand the consumer buying behaviour of Indian in digital era”.
Main findings of this Dissertation are given here. Indian customers are highly information seekers. They collect more information about a product before buying it. Internet penetration in India is key player for this phenomenon. Most of Indians are getting stimulus through advertisements, but they are not reaching to end phase of customers purchase journey, mainly in high involvement purchases. Brands are getting more touch point to reach their target group in this digital era. More details about findings are given this report.
The successful completion of this Dissertation indicates that the future of marketing is in the hands of digital. I conclude my research by quoting again that “Brands can’t sustain without digital presence”
Advertising in business is a form of marketing communication used to encourage, persuade, or manipulate an audience to take or continue to take some action. Most commonly, the desired result is to drive consumer behaviour with respect to a commercial offering. Advertising is defined by Richard F. Taflinger as “Advertising is the non-personal communication of information usually paid for and usually persuasive in nature about products, services or ideas by identified sponsors through the various media."
IRJET- Internet Shopping Value and Customer Repurchase IntentionIRJET Journal
This document discusses factors that influence customers' repurchase intentions for online shopping. It examines convenience, customization, and overall satisfaction and attitudes as key drivers of customer loyalty and repeat purchases. The document presents research showing that overall satisfaction has an even stronger impact on repurchase intentions than attitudes. It also discusses how customization and convenience enhance the online shopping experience and make customers more likely to return to the site.
1. The document discusses how the classic economic model of consumer behavior as rational actors seeking to maximize benefits is an oversimplification and does not account for variability and irrationality in consumer decision making.
2. It then outlines the traditional linear consumer purchase process model involving problem recognition, information search, evaluation of alternatives, purchase, and post-purchase evaluation.
3. However, it notes that the modern consumer decision journey is non-linear with multiple touchpoints of influence from various sources, requiring marketers to engage consumers throughout the process through two-way conversations to build loyalty.
Social media in advertising & marketingbrandoj
This document discusses how social media is used in advertising and marketing. It begins by outlining theories of branding and awareness, including top of mind, frame of mind, and friend of mind awareness. It then discusses how consumers engage with brands on social media, and how companies can build their brand and strengthen public perceptions. The rest of the document details strategies for social media marketing, including promotions, market research, branding, integrated marketing communications, strategic planning, engagement, search engine optimization, and the mobile path to purchase.
Social media in advertising & marketingwidemand
Social media provides opportunities for brands to connect with consumers in real-time and build relationships. Companies use social platforms to raise awareness, engage customers, and strengthen their brands. Effective social strategies focus on creating valuable conversations rather than just promoting products. While social media allows greater consumer reach, brands must balance this with authentic engagement and avoid appearing too promotional to build trust over time.
The growing use of Internet in India provides varied opportunities for online shopping from both customer and seller perspective. If Electronic marketers (E-Marketers) know the factors affecting online Indian behavior, the relationships between these factors and the type of online buyers, they can further develop their marketing strategies to convert potential buyers into active buyerswhile retainingits original customer base. This study focuses on the factors which online buyers takes into consideration while shopping online. This research will help in finding the impact of e-market on customers’ purchasing patterns and how their security and privacy concerns about online marketinginfluences their online buying behavior. The study will further encompass the various important inputs which will equip the marketers for creating online marketing more lucrative and assured by adding value to the existing services.
Similar to ECT 584_Research Paper_JoyceRose_08182015 (20)
consumer perception towards online marketing in india
ECT 584_Research Paper_JoyceRose_08182015
1. 1
The relevance of context aware recommender system for one to one marketing in E-
commerce
Name: Joyce Rose
ID: 1433345
Email: jr25depaul@gmail.com
Class: ECT 584
Abstract: The movement of the physical store to the virtual space, that is the world of e-
commerce has not only resulted in the explosion of information but has also created the
possibility of converting standardized products into personalized products for customers. The
importance of having a robust recommender system in an environment laden with information,
for a virtual store, from a marketing perspective is to convert browsers into sellers, increase cross
sell between products and build loyalty by creating a positive interaction between the site and
customer which in turn increases profitability for the company. Traditionally the adopted method
for implementing one to one marketing through recommendation systems is by the use of
collaborative filtering or content-based recommendation. Though both methods rely on user
profiles and items. The crux of the recommendation system fails to capture the impact of
contexts or situations - the context in which a customer purchases a product - as an important
factor in understanding customer shopping behavior. Therefore, the purpose of this paper is to
explore the relevance of context in improving the quality of a recommender system and its
importance to a one to one e – commerce marketing strategy.
2. 2
1. Introduction and Motivation
In the world of e-commerce where the Internet serves as the primary medium to “facilitate,
execute and process business transactions” (DeLone & McLean, 2004, p. 31), the birth of the
‘virtual store,’ an alternate reality to physical stores, is a paradigm shift from ‘tradition.’ A shift
in that e-commerce not only experienced a decrease in operational costs (Vafopoulos &
Oikonomou, 2011), but also encountered the possibility of converting standardized products into
personalized products for customers. A most noted move away from marketing to the masses to
one to one marketing. With the advent of personalization Schaefr, Konstan and Riedi write, “At a
minimum, companies need to be able to develop multiple products that meet the multiple needs
of multiple consumers. While E-commerce hasn’t necessarily allowed businesses to produce
more products, it has allowed them to provide consumers with more choices. Instead of tens of
thousands of books in a superstore, consumers may choose among millions of books in an online
store. Increasing choice, however, has also increased the amount of information that consumers
must process before they are able to select which items meet their needs” (para. 1).
The virtual store, therefore, is an ocean of information one in which consumers can feel
overwhelmed and lost. In order to combat the negative repercussions of information overload -
which is less foot traffic and poor sales performance - recommender systems (RS) have been
used as a “virtual salesperson” to “propose products for purchase,” (Vafopoulos & Oikonomou,
2011, p.5) each personalized to the needs of the customer. The goal of recommender systems is
to create a positive discourse between the recommender and the recommendee by exploiting
“user’s characteristics (e.g. demographics) and preferences (e.g. views and purchase) to form
recommendations” (Vafopoulos & Oikonomou, 2011, p.6). Hence, the robustness of RS for a
virtual store, from a marketing perspective, has been defined based upon the systems’ ability to
convert browsers into buyers, to increase cross sell between products and to build loyalty by
creating a positive interaction between the site and customer. This in turn increases profitability
for the company.
Traditionally, the adopted method for implementing one to one marketing through
recommendation systems is by the use of collaborative filtering or content-based
recommendation. Both methods rely on user profiles and past transactions/items to make
recommendations. The crux of such a recommendation system is limited in that it fails to capture
the impact of contexts or situations - the context in which a customer purchases a product - as an
important factor in increasing sales. The failure of recommendation systems to capture
contextual information is not a poor reflection on the algorithm itself. However, it is a reflection
of marketers’ inability to understand the importance of context in consumers’ online shopping
behavior.
The primary goal of a marketer is to identify, anticipate and satisfy customer requirements
profitably. “In particular, one to one marketing is defined by four principles, namely: (1) identify
customers, (2) differentiate each customer, (3) interact with each customer and (4) customize
products for each customer” (Vafopoulos & Oikonomou, 2011, p.10). Though there are no
arguments against the principles themselves, it is important to ask the two following questions to
systematically understand the limitations of the traditional recommender systems: “how do
customers behave in electronically enhanced buying environments? And how can marketers
3. 3
design e-services that deliver quality and value to customers?” (Bolton, 2003, para. 44). Bolton
argues that marketers often fail to realize that the online shopping environment is vastly different
than shopping in store in that customers are no longer able to feel the product but instead are
offered information to decipher the quality of it. Therefore, the basis of customers’ purchasing a
product or not is primarily rested on perception – perception of value [be it need or relevance] in
the product being recommended and perception of the website. And based on perception trust
and customer loyalty is built.
The marketing challenges that Bolton has pointed out calls attention to the fact that
recommendation systems are built from a ‘seller centric’ point of view irrespective of the
‘personalized’ item recommendations offered to consumers. The personalization remains seller
centric because considerations such as customer perception on trust, lack of interpersonal
interaction or customer psychographics in general is not accounted for by the algorithms.
Therefore, the purpose of this paper is to explore and emphasize the importance of “embodied
knowledge” or contexts when building a recommendation system and the impact of such a
context aware recommender to a one to one e-commerce marketing strategy. The premise of the
paper is that a positive customer behavior is elicited by a recommender system only when the
product being recommended is placed within a context without which even a quality
recommender system with robust filtering mechanisms that match items and users will fail to
reap profits. As DeLone and McLean (2004) write, “the law of economics has not been rewritten.
The long terms success or failure of companies is determined by their ability to generate positive
net revenues” (p. 31).
Much research on recommender systems has been conducted with detailed descriptions of the
algorithms themselves. The goal of this paper is not dwell in technicalities but to understand and
achieve a balance between recommender applications and business relevance/importance. In this
regard, the rest of the paper will be divided as follows: Section 2: an overview of recommender
systems and its use in e-commerce, Section 3: the notion of embodied knowledge/context in
terms of customer online shopping behavior and its implications for one to one marketing
strategy in e-commerce, Section 4: finally concludes the paper with suggestions for future
research.
2. An overview of Recommender Systems and its Use in E-Commerce
The purpose of a recommender system is two fold in nature. One, to collect information on user
preference and two to filter information in a manner that provides accurate recommendations
based on the needs of the customer. Information on consumer preference is collected explicitly
[example: user’s ratings, questionnaire] or implicitly [example: by “monitoring user’s behavior,
such as songs heard, applications downloaded, websites visited and books read”, past
transactions and items in the shopping cart] (Bobadilla, Ortega, hernando, Gutierrez, 2013, 109).
It is important to note that the information collected by recommender systems is not limited to
ratings and web usage. In fact, demographic information such as age, gender and nationality
combined with social information such as tweets, tags and GPS locations might be collected
depending on the type and purpose of the recommender system. The collection of varied
information about a particular user is crucial to the quality of the recommender system in that the
more a recommender system learns about a particular user the better the recommendation.
4. 4
The methodology adopted to filter the data of a particular user is situational. So the question at
hand is: how do we filter data and what is the purpose [cross-sell, up-sell, etc.]? One must keep
in mind the process by which the data is filtered is indeed the method in which a
recommendation is made. In other words, there are three ways of making recommendations: (1)
content based filtering, (2) collaborative filtering and (3) hybrid. Content-based recommenders
use key words that describe items that were liked by a particular user to recommend similar
items. “For example, if a user likes a web page with the words “car”, “engine” and “gasoline”,
the CBF [content based filtering] will recommend pages related to the automotive world”
(Bobadilla, Ortega, hernando, Gutierrez, 2013, 119).
Collaborative based filtering makes recommendations based on the similarity between the user
and other users with similar items. Bobadilla, Ortega, hernando, Gutierrez, 2013, write “CF is
based on the way in which humans have made decisions throughout history: besides on our own
experience, we also base our decisions on the experiences and knowledge that reach each of us
from a relatively large group of acquaintances” Hybrid recommendation systems are used in
conjunction. For example, Netflix might recommend movies sharing similar characteristics to
that which user A has rated highly in the past (content based filtering) or might recommend
movies that other users similar to user A have watched (collaborative filtering). Research on
recommender systems generally indicate that the hybrid algorithm is the better method to use as
hybrids can handle issues such as cold start and sparsity adequately. Also, hybrid algorithms can
offset the disadvantage of one algorithm over another. For instance, the disadvantage of a content
based recommender is the problem of ‘overspecialization’ in that the algorithm recommends
only similar items in light of the items he/she has preferred in the past but fails to recommend
items that they might like but are not known (Bobadilla, Ortega, hernando, Gutierrez, 2013). The
use of content based along with collaborative filtering will mitigate this issue.
Selecting the type of filtering method for a recommender system is not the only decision to be
made. A recommendation system can be memory based or model based. A memory based
method for a collaborative filtering approach would mean that the algorithm computes the
correlations between all the users in the dataset and the target user. Then based on the number
assigned for the k nearest neighbor selects the closest neighbors, then computes the respective
weights and finally predicts the ratings. It is easy to see that the usage of the entire dataset will
render the algorithm computationally slow and expensive though the quality of predictions might
be good. Model based algorithms on the other hand is faster and scalable in that only a subset of
the data is selected and a model is built on a portion of the data to make recommendations. The
quality of the prediction is comparatively less than the memory based algorithm. However,
model based algorithms favor real time recommendations due to its speed and scalability.
Though recommendation systems are built to accurately predict ratings there are three factors
[sparsity, cold start and scalability] that challenge the quality of the recommendations. “The data
sparseness issues arise irrespective of the type of recommendation systems. For example, the
data in MovieLens is represented as a user – item matrix.” (Abbas, Zhang & Khan, para.14).
Sparseness occurs when the number of items increases however since not all users have watched
all movies not all movies are ranked. Abbas, Zhan & Khan write that sparsity is often addressed
5. 5
by applying dimensionality reduction techniques such as SVD, matrix factorization and latent
semantic index.
Cold start is a term that refers to the problem of not having a rating for the following three
reasons: new community, new item and new user (Bobadilla, Ortega, hernando, Gutierrez, 2013).
All three cold start problems have the same issue, insufficient data to make recommendations.
The cold start problem, however, can be addressed by implementing a hybrid algorithm approach
where users can be asked to rate random movies. The recommender system can learn from
content similarities and once enough data is collected a collaborative method of recommending
products can be implemented.
Scalability is a problem that must be addressed before building a recommender system. The
pivotal question is: can the algorithm handle large volumes of data to process data and provide
recommendations as quickly as possible? A notion discussed in the context of memory and
model based algorithms.
Having an overview of how recommender systems function in general offers a better foundation
upon which the applications of recommender systems in e-commerce can be examined. Driskill
and Riedi write within the context of e-commerce recommender systems have indeed helped
customers “sort through large information spaces to find items of most value to them” (p.73). In
fact, e – commerce has been successfully applied in the following three areas: direct product
recommendations, gift centers and cross – sell recommendations. In agreement with Driskill and
Reidi’s statement, a study conducted by Dias, Locher et al (2008) on the value of personalized
recommender systems to e-businesses indicate that the introduction of a recommender system on
LeShop, the leading online grocery store in Switzerland, with the goal of (1) recommending
products from new categories to customers and (2) reminding customers of “forgotten items,”
that is, items that customers usually buy but have forgotten resulted in an increase in sales by at
least 66%.
Though the argument for the successful implementation of recommender systems is currently
lauded by the very existence of Amazon, Netflix, MovieLens and Pandora the problem of
shopping cart abandonment brings our attention to the fact that though recommendation systems
are recommending products to consumers marketers do struggle with the inability to convert
browsers to buyers. According to Simpson (2012), “U.S. consumers spent $194.3 billion online
in 2011” (para. 1). Nevertheless, looking at consumer expenditure alone can be detrimental in the
light of the number of sales lost due to shopping cart abandonment. The abandonment of
shopping cart refers to online shoppers initiating a purchase but failing to complete the check out
by abandoning the cart instead. The following table shows the rate of abandonment over specific
years.
Year Cart Abandonment Rate Source (Author of Article)
2015 68.53% Baymard Institute
2012 65% Simpson
2004 57% Moore & Mathews
2003 61% Morris
6. 6
The consistency that is found in the rates over the given years are red flags to marketers in that
the high cart abandonment rates equals the inability to capture sales that would potentially
generate profitable net income for companies. According to research conducted by Forrester,
abandoned carts result in “$18 billion of lost revenue annually” (Gordon, 2014, para. 4).
Hence, much research has been conducted to understand why customers are reluctant to
complete orders online. The common theme that runs through the current studies on the factors
that instigate abandonment is the notion of perceived risk. That is the need to avoid “buyer’s
remorse” or the “possibility of a new product introduced after purchase” (Coppola, & Sousa,
2008, p.387). According to Cho, Kang, Cheon (2006) marketers fail to realize that the online
shopping experience is quite different from a physical store in that the inability of the customer
to examine the product in person heightens consumers perceived value for the product.
Therefore, this increased perception of risk normally translates to customer’s abandoning their
carts. It must be noted that there are a number of other factors that also contribute to shopping
cart abandonment such as the cost of the product, shipping cost, security issues, lack of
information on the product etc. These issues are not a concern for this research paper as these
factors are not tied to the robustness of recommender systems but are a matter of web design,
features and functions.
However, the notion of perceived risk is a matter that pertains to recommender systems. Eddy
writes, “personalization is seen as the next big thing in online shopping, however most of the
personalization we see today is designed to trick shoppers into buying more. True useful
personalization is something that helps the web visitor have a better shopping experience, and we
just aren’t seeing many multichannel retailers do a great job of that yet” (para.5). In other words,
the current application of recommender systems in ecommerce, that is the 2D or traditional
recommender systems 𝑅: 𝑈𝑠𝑒𝑟 ∗ 𝐼𝑡𝑒𝑚 → 𝑅𝑎𝑡𝑖𝑛𝑔 𝑜𝑟 𝑅: 𝐼𝑡𝑒𝑚 ∗ 𝐼𝑡𝑒𝑚 → 𝑅𝑎𝑡𝑖𝑛𝑔, may in fact
contribute to shoppers’ online hesitation, the antithesis of a recommender’s purpose.
3. The notion of embodied knowledge/context in terms of customer online shopping
behavior and its relevance to one to one marketing
The notion of embodied knowledge or context cannot be entirely understood without examining
what factors contribute to the execution of recommender systems in an antagonist manner.
Recommender systems are tools that are often an accurate reflection of how marketers perceive
customers. Marketing research aims to understand customers not only from a demographic
perspective but also more importantly from a monetary point of view. In other words, what is the
value that a particular customer brings to the company? The abbreviations RFM (recency,
frequency, monetary) are the pillars of marketing upon which recommender systems are
executed. “RFM data is how recently the customer has purchased from the website, how often
the customer has purchased from the website and how much the web site has earned from the
customer’s purchases in the past” (Driskill and Riedi, 1999, p.74).
It’s not rocket science to see how a recommendation system built to make recommendations
based on the data collected against these measures would function. For instance, a content-based
recommender system would recommend to customers who are high spenders only those similar
items that are of high value. Likewise, a collaborative filtering algorithm would have clustered
7. 7
all the high spenders according to their similarities with other users and items. This strategy of
analyzing customers according to RFM is business savvy. However, this marketing strategy
assumes that the virtual and the physical world share similar customer shopping behavior. Such
an assumption often misleads marketers to overlook an important link between the user and the
items recommended that is the human mind.
The human mind is a simulator in that consumers in general call on a frame of reference or point
of contact, which may be knowledge of a product or past experience to make a decision. A
consumer in a physical store is offered the opportunity to ‘experience’ the product sold by both
body and mind. The quality of the product can be felt, its appeal can be seen in terms of
dimensions, height, width, texture etc. And based on the combination of prior knowledge and by
experiencing the product first hand a consumer is able to make a purchase decision. Even when
prior knowledge is unavailable the experience of handling the product has a better chance of a
buyer walking away from the store with a product. For instance, in an apparel store customers
can wear an outfit to gauge quality, fit and feel of the product that eventually leads to a decision.
The draw back of the virtual store is that the new product being recommended is removed by
space and time. Herein lies the pivotal difference between physical and virtual stores. The
physical store relies much on the creation of an experience to sell products and the virtual store
relies heavily on relevance or contexts to sell new products.
Rosa and Malter write (2003), “it is significantly more challenging to market products for which
consumption involves high levels of somatic and sensorimotor inputs (e.g., touch, body
movement) through constrained two – dimensional interfaces, as can be seen from the limited
success that internet retailers have had with sensory products, and the high return rates in many
product categories” (p.63). Retail stores experience customer returns of about 8.7% of retail
sales. However, the number is higher for [18% to 35%] e-commerce retailers depending on the
product category. “In all, it is estimated that managing product returns costs U.S. companies well
over $200 billion annually” (Ofek, Katona, Sarvary, 2010, p. 2).
Therefore, marketers must spend time on understanding how the notion of embodied knowledge
and pre – existing knowledge plays an important role when recommending items to customers.
Embodied knowledge is instinctual. For example, the feel of driving a car at a auto showroom
where the mind is stimulated to think of all the possibilities of having the product in their
possession versus the details about a specific product which would be pre – knowledge. Though
the importance of embodied knowledge and pre-knowledge is an important customer behavior in
the physical and virtual space. The need to elicit a simulation using embodied knowledge and
pre-knowledge is pivotal to improving conversion rates. The key factor that creates a simulation
is the word ‘context’ which also can be referred as relevance. In the absence of a direct
experience generated within the walls of a physical store, relevance or context calls on
experience indirectly to instigate the buyer to purchase a product.
The CEO of a Santa Barbara Commission Junction, a company that provides marketing services
to merchants writes, “contextual commerce is about human nature” (Pack, 2011, p. 24). The lack
of context that is in essence inclusive of embodied and pre knowledge in recommender systems
can be attributed to certain customers abandoning their shopping carts. Many researchers
indicate that most often customers fail to complete their purchase because of the perceived risks
8. 8
of buying a product online. Perceived risks can be broken into two categories: (1) perceived need
and (2) perceived duress or the fear that consumer might have to go to great lengths to return a
product if it does not meet their expectations. The traditional recommender systems that do not
cater to creating a contextual recommendation have a high risk of running up against the
shopping cart abandonment syndrome. After all, without a point of reference or relevance
consumers waver between the ‘want’ to buy verses a ‘need’ which most often leads to not only
an abandonment of the cart but also a missed opportunity to convert a browser to a loyal
customer.
The notion of context in terms of time, season, location, and company is currently a topic of
ardent discussion among artificial intelligence specialists, computer scientists and data miners.
For instance, Stormer (2007) argues that by utilizing the context of ‘season’ recommender
systems can alleviate discomfort among consumers who are recommended untimely seasonal
items. For instance, recommending winter coats during summer. Similarly, time can be used as a
filter by recommender systems to recommend the right vacation packages given temporal
factors. For instance, a consumer from the Midwest during the month of December might look
for a warm weather winter vacation package. A mobile app will consider GPS location as a
context to provide real time recommendations.
The point to note here is that context is varied in meaning and the implications of its diverse
meaning calls the attention of marketers to move away from a seller centric point of view to that
of a buyer. Marketers must now understand the context or the stimulant that would elicit a
favorable response from the perspective of the buyer. This is important because in order to truly
understand the needs of the customer the customer’s intent to purchase becomes the center upon
which other factors such as RFM are later built. As Champiri, Shahamiri and Salim (2014) write,
“in order to build relevant, useful, and effective recommender systems, the validity of contextual
information through the eyes of users ought to be evaluated” (p. 1755). Building recommender
systems to make recommendations contextually does not necessarily change the nature of the
functionality of the content based filtering or the collaborative based filtering algorithm. Instead,
the contextual filtering process truly becomes specialized to the purchase intent or the needs of
the customer. Therefore, the traditional recommender has a re – birth by filling in the missing
link between the user and item, that is, the customer which equals context - 𝑅: 𝑈𝑠𝑒𝑟 ∗ 𝐶𝑜𝑛𝑡𝑒𝑥𝑡 ∗
𝐼𝑡𝑒𝑚 → 𝑅𝑎𝑡𝑖𝑛𝑔 𝑜𝑟 𝑅: 𝐼𝑡𝑒𝑚 ∗ 𝐶𝑜𝑛𝑡𝑒𝑥𝑡 ∗ 𝐼𝑡𝑒𝑚 → 𝑅𝑎𝑡𝑖𝑛𝑔.
Given that this paper has established a case for the importance of using context as a factor for
filtering data. And has emphasized the importance of marketers understanding context from a
behavioral perspective in order to abate perceived risks and consequently increase perceived site
value exhibited by not abandoning the cart. The next logical question to ask is how does a
contextual ‘customerization’ of products change the nature of one to one marketing or does the
execution methodology remain the same? If we look purely at recommender systems as tools
being a part of a one to one marketing strategy. Then it is clear that customers have played the
role of a passive participant taking directions from the recommender based on their past orders.
Customerization of products creates a sense of urgency in that one to one marketing is based on
customer intent. And the pivotal point about the notion of decision making and intent is that the
decision made by consumers changes according to situations based on whether the purchase is
made for family, self or as a gift. Therefore, marketers have to be more dynamic in deciphering
9. 9
when, how and where to deliver their marketing campaigns. This can only be done by generating
a rich study on what specific contexts are more applicable than others to the products sold on the
respective website. Implementing contextual factors can result in an increase in profits for
organizations but the immediate challenge is to ensure that the contexts used to filter data are not
too granular that its not relatable to all nor too broad that its usage is futile. It is not in the scope
of the paper to discuss how context(s) can be gathered and implemented in a 2D recommender
system. However, research conducted by Adomavicius & Tuzhilin on context – aware
recommender systems offer more insights on possible implementation strategies.
4. Conclusion
The main purpose of this paper was to emphasize that marketers have failed to understand the
relevance of the human mind, the context in which a customer shops as pivotal in converting
browsers into buyers. The very existence of high shopping cart abandonment rates over the years
is indicative that marketers have not truly understood both the psychological and commercial
value of including contexts in the 2D recommender systems. The paper also argued that
marketers’ myopic vision, that is a seller centric perspective, of personalization has rendered the
use of recommender systems futile in that the lack of contextual recommendations based only on
user and item similarity might lead to heightened perceived risk of the website and the
recommendation(s) made.
Much research has been conducted on the different ways to use context aware recommender
systems. However, it is surprising that very few have discussed the psychological implications of
context to a customer. Understanding the notion of context must be done in a systematic manner
in that context not only refers to situations such as location, time, season etc. To understand
context only as a situation is to undermine the fact that ‘context’ acts as trigger that creates a
point of reference, the frame within which consumers engage in a positive dialogue with the
recommender. Therefore, marketers must cognize that a customer centric recommender system
must be executed in a manner that truly captures all the relevant contexts that act as embodied
knowledge in the stimulation creation process. Doing so could potentially lead to consumers
completing their purchase orders as context mitigates perceived risks such as the need for the
product and the quality of the recommendation.
The nature of this paper is qualitative and hence the argument: 2D recommender systems
functioning without a context can have an antithesis effect on the consumer might serve as a
hypothesis for a quantitative research project. The value of a recommender system is only
ascertained by its utility. Within the world of business this would be analyzed in terms of ROI.
The argument that context aware recommender systems have the power to mitigate perceived
risk calls for the need to do an implementation project where upon implementing a context aware
recommender marketers can study its impact on customer shopping cart abandonment rates. A
semi qualitative and quantitative study can be conducted to ascertain the importance of
contextual stimulants to consumers as they make their purchase. This would offer marketers the
opportunity to understand what customers expect when a recommendation is made to them from
a contextual perspective.
10. 10
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