Download or read book Why Needs to Predict Consumer Behavior written by Johnny Ch Lok and published by Independently Published. This book was released on 2018-10-17 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: I also suggest a two stage procedure to detect whether the act of measurement alters the strength of the relationship between a latent construct that is measured through surveys, experiments or observations and its consequence ( e.g. intentions-behavior, attitudes-intentions, attitudes-behavior, satisfaction behavior) and to determine the time relationship in the absence of the difference between non-survey and survey consumers behavior measurement for Disney. For example, prediction of Disney visitor's entertainment facilities choice behavior intention to find why the kind of entertainment facilities can attract more visitors choose to play in Disney theme park. Disney survey method can measure to any machine entertainment facilities. So, Disney can show the strength of the relationship between latent intentions and visitor entertainment facilities choice behavior is stronger for surveyed consumers than for similar non surveyed consumers in order to find the reasons why more visitors choose to play which kind of entertainment facilities.I also suggest the Disney survey questions can concern to compare with other inputs factors of entertainment facilities choice decisions. e.g. personal entertainment tastes, mood, other similar entertainment theme parks' competitive environment. In order to make subsequent visiting Disney behavior is more than one time with prior intentions for every Disney old visitors. For example, Feldman and Lynch's ( 1988) survey method predictions, Fitzsimons and Morwitz ( 1996) found that measurement of general intentions to purchase automobiles increase the likelihood that buyers will repurchase the automobile brand that they also previously consume and that first time buyers will purchase brands will large market shares. Under the assumption, if the survey's result showed the automobiles brand-specific purchase intentions. Thus, Fitzsimons and Morwitz's results suggest that the measurement of general intentions increases the association between latent, brand-specific intent and brand choice. So, brand is a factor which can influence consumers to choose to buy which automobiles. In conclusion, it seems Disney can attempt to use survey method to investigate visitor entertainment facilities choice behavior to predict what factor is the most influential to attract every Disney visitor to choose to play the entertainment as well as what factor is the most influential to every Disney ( re-visitor ) old visitor to choose to visit Disney theme park again.

Download or read book Psychology Methods Predict written by Johnny Ch Lok and published by . This book was released on 2021-04-26 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: ⦁Can predict consumer behavior with web search?In behavioral economy view point, it can be applied to predict why consumers buy products from internet. Recent work has demonstrated that web search volume can "predict the present", meaning that can be used to accurately track outcomes, such as unemployment levels, auto and home sales and disease prevalence in near real time. Consumers are searching what for online can also predict their collective future behavior days or even weeks in advance. For example, specifically businessmen can use search query volume to forecast the opening weekend box-office revenue for feature films, first month sales of video games and the rank of songs, finding in all case that search counts are highly predictive of future outcomes from online google research. Finally, businessmen can reexamine previous work on tracking trends and show that, perhaps surprisingly, the utility of search data relative to a simple auto regressive model is modest.Nowadays, people increasingly use the internet for news, information and research purposes. From this perspective, it is a short step to conclude that what people are researching for today is predictive of what who will do in the near future. For example, consumers may search to prepare to buy a new camera, moviegoers may search to determine the opening date of a new film, or to locate cinemas showing it and individuals planning a vacation may search from a places of interest, to find airline tickets, or to price hotel rooms. So online can aggregately count of search queries related to retail activity. Movie going or travel might be able to predict collective behavior of economic, cultural, or political interest. Determining the nature of behavior that can be predicted using search, the accuracy of such predictions and the time scale over which predictions can be usefully made are therefore all questions of interest. Researchers have focused on the observation that search " predicts the present". For example, Ettredge et al (2005) found that counts of the top 300 search terms during 2001 to 2003 year were correlated with US Bureau Of Labor statistics Unemployment Figures; Cooper (2005) et al found that search activity for specific cameras during 2001 to 2003 year correlated with their estimated incidence and Eysenbach (2006) found a high correlation between clicks on sponsored search results of flu-related keywords and epidemiolopical data from the 2004 to 2005 year Canadian flu season.Thus, motivated, I indicate one example how investigates whether search activity is a systematic leading indicator of consumer activity by forecasting. For first example, supposing to opening weekend Box-office revenue for 119 feature films released in the united States between Oct. 2008 year and Sept. 2009. For second example, supposing to first month sales of video games across all gaming platforms, e.g. Xbox, Play station etc.) for 106 games released between Sept. 2008 and Sept. 2009 year. These search data can be collected from yahoo using research rank from the current and previous weeks. Can online search also predict the near future? A finding that may apply usually to a wide range of consumer behaviors, e.g. airline travel, hotel vacancy rates and auto sales and economic indicators, e.g. real-estate prices, credit card and confidence indicators. It seems all research based predictions simply models to build on publicly available information. For movies, baseline predictions can be used a linear model that includes production budgets, the number of screens on which each movie opened and box office projections from the Hollywood Stock Exchange (HSX) ( hsx.com) on online, play money prediction market that is known to generate information prediction. For video games, many of the key indicators of revenue, including production budgets and initial available.

Download or read book Can Predict When How Why Consumer Behavioral Changing written by Johnny Ch LOK and published by . This book was released on 2018-06-19 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction This book has these two research questions need to be answered?(1) Can apply (AI) learning machine as well as micro and macro economic methods predict consumer behavioral changing?(2) Can (AI) learning machine replace human marketing research method, e.g. survey or human psychological and micro and macro economic methods to predict consumer behaviors more accurate? This book has two parts. The first part indicates whether micro and macro economic methods can be attempted to apply to predict when, how and why consumer behavioral changing for every kind of different business. The second part indicates whether artificial intelligence can be attempted to apply to predict when, how and why consumer behavioral chaning for every kind of different business. Nowadays, many businessmen or marketing research professional hope to apply different methods to predict consumer behaviors in order to know what will be future market activities and market changes to help them to choose to implement what kinds of marketing strategies more accurately. The methods include economic environmental change prediction method, consumer individual psychological change prediction method, micro or macro behavioral economic environmental change prediction method, marketing environmental change prediction method etc. different kinds of methods which can be applied to predict how consumer behavioral changes to influence whose behavioral consumption to the manufacturer products sale within one to two years short term or three to five years middle term, even above five years long term business plans. Hence, if the product manufacturers can apply the most suitable consumer behavioral prediction method to predict how consumers' choice will be changed to influence their products sale easily. It will have more beneficial intangible and tangible advantages to achieve the their product easier sale aim to ensure their businesses' future market share to be increased more easier to their countries' choice target sale markets. Otherwise, if they applied the inaccurate consumer behavioral prediction methods to predict how their consumers' behavioral changes wrongly. Then, it will influence their market shares to be same level, even it will decrease their market shares, when their consumer behavioral prediction inaccurately. Whether can businessmen apply micro and macro-economic methods to assist them to analyze how marketing will change, what marketing trend will develop next month or next half year, even more than one year marketing development trend in possible? In my this book first part, I shall considerate on businessmen and customers both beneficial view point to explain how to apply behavioral economic concept to predict how their specific industries marketing development trend or consumer behavioral changing trend in these micro economic (individual consumer psychological shopping change trend) and macro-economic (global every specific industry marketing changing trend) environment. This book main research this two questions: (1) Has it relationship between macro and micro economic environment change factors to influence marketing development change trend? (2) Can businessmen apply macro and micro economic methods to predict future marketing development change trend in their specific industries?

Download or read book Can Apply Artificial Intelligence Predicts Consumer Behavior In Business Environment written by Johnny C. H. Lok and published by Independently Published. This book was released on 2018-09-17 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: Prepare This book has these two research questions need to be answered? (1) Can apply (AI) learning machine predict consumer behaviors? (2) Can (AI) learning machine replace human marketing research method, e.g. survey or human psychological and micro and macro economic methods to predict consumer behaviors more accurate? Nowadays, many businessmen or marketing research professional hope to apply different methods to predict consumer behaviors in order to know what will be future market activities and market changes to help them to choose to implement what kinds of marketing strategies more accurately. The methods include economic environmental change prediction method, consumer individual psychological change prediction method, micro or macro behavioral economic environmental change prediction method, marketing environmental change prediction method etc. different kinds of methods which can be applied to predict how consumer behavioral changes to influence whose behavioral consumption to the manufacturer products sale within one to two years short term or three to five years middle term, even above five years long term business plans. Hence, if the product manufacturers can apply the most suitable consumer behavioral prediction method to predict how consumers' choice will be changed to influence their products sale easily. It will have more beneficial intangible and tangible advantages to achieve the their product easier sale aim to ensure their businesses' future market share to be increased more easier to their countries' choice target sale markets. Otherwise, if they applied the inaccurate consumer behavioral prediction methods to predict how their consumers' behavioral changes wrongly. Then, it will influence their market shares to be same level, even it will decrease their market shares, when their consumer behavioral prediction inaccurately. In my this book first part, I concentrate on indicate whether any artificial intelligence (AI) tools will be one kind of good consumer behavioral prediction method to be choose to apply to predict consumer behaviors. I shall indicate some examples, cases to give reasonable evidences to analyze whether (AI) tools will be one kind suitable tool to be applied to predict when and how consumer behavioral changes. If (AI) can be one kind tool to attempt to be applied to predict when and how consumer behavioral changes. Will it replace other kinds of methods to predict consumer behaviors? Does it have weaknesses to be applied to predict consumer behaviors, instead of strengths? Can it be applied to predict consumer behaviors depending on any situations of only some situation? Finally, I believe that any readers can find answers to answer above these questions in this book. In my this book second part, I shall explain why and how human can possible apply (AI) tool to predict consumer individual emotion. I shall indicate case studies to explain how consumer individual better or worse emotion how to influence whose consumption behavior in different situation. Finally, I shall indicate evidences to conclude how and why (AI) tool that can be used to predict consumer individual emotion and it will have direct relationship to influence consumption behavior, as well as how (AI) tool can assist businessmen to judge whether what reasons case the customer does not choose to buy its product, it is possible because the product high price factor, poor product quality or poor staff service performance or attitude etc. different factors to influence the consumer decides to choose to buy the other product consequently, when the (AI) tool can confirm consumer has good or bad emotion to judge what factors are the causes his decision making at the moment.

Download or read book Predict Consumer Behavior Psychology Methods written by Johnny Ch LOK and published by . This book was released on 2018-03-29 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: In part three, I shall explain how to apply behavioral economy method to attempt to predict how any consumer individual consumption of decision. How to predict why the consumer chooses to do whose consumption behavior in psychological view point. I shall introduce the different kinds of behavioral consumption of prediction methods include: the standard economic model of behavioral consumption of prediction method, online psychological advertising of prediction method, brand image attention of behavioral consumption of prediction method, store atmosphere environment influence prediction method, knowledge of the factors prediction method, constructive consumer choice processes influence prediction method, survey research prediction method ,consumer neuroscientific research prediction method etc. different psychological research of consumption methods. I shall indicate that how to predict customer behavior in marketing view point, analyzing and predicting consumer behavior can include demographics, personality, personal values and lifestyles. First, demographics is the size, structure and distribution of a population. How marketers use demographic analysis as market segment, descriptors and in trend analysis to predict customer behavior as well as how consumer analysts use demographic trends to predict changes in demand for and consumption of specific products and services. To explain how demographic analysis provides information for social policy and demographics used in analyzing policy questions related to the aggregate performance of marketing in society ( macro marketing) to predict how industrial demand is ultimately derived from consumer demand. I shall explain why analysis of demographic trends is only important for industrial and business-to-business marketing and why it can't concentrate on consumer individual consumption marketing both as well as to explain why in an individual firm, which must understand not only the customer's minds, but also the minds of the customers'and to explain how to apply demographic analysis to predict consumer behavior factors include: changing structure of markets , geographic factors, economic resources and global markets. I shall explain why market analysis requires information about consumers with needs, ability to buy, willingness to pay and authority to pay, changing structure of consumer markets, such as how many consumers will there be? e.g. birthrate, national increase, fertility rate, total fertility rate, population momentum etc. information. In part four, I shall give insurance and travel both industries to explain how to apply behavioral economy theories to solve consumer behavior prediction as well as I shall indicate some methods to explain how manufacturers or service providers can attempt to solve some challenges encountering when who attempt to predict consumer behaviors. Finally, I shall indicate what the methods are the most effective to attempt to predict consumer behaviors. In my this book, the main important aim, I give examples to explain how to apply psychological and behavioral economic both view point related methods to predict consumer individual behavior to let businessmen learn how to choose the reasonable or right methods to attract consumers to choose to buy whose products or consume whose services to win competitors more easily.

Download or read book The Difference Between Artificial Intelligence and Psychological Method Predicts Consumer Behavior written by Johnny Ch Lok and published by Independently Published. This book was released on 2018-09-08 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has these two research questions need to be answered? (1) Can apply (AI) learning machine predict consumer behaviors? (2) Can (AI) learning machine replace human marketing research method, e.g. survey or human psychological and micro and macro economic methods to predict consumer behaviors more accurate? Nowadays, many businessmen or marketing research professional hope to apply different methods to predict consumer behaviors in order to know what will be future market activities and market changes to help them to choose to implement what kinds of marketing strategies more accurately. The methods include economic environmental change prediction method, consumer individual psychological change prediction method, micro or macro behavioral economic environmental change prediction method, marketing environmental change prediction method etc. different kinds of methods which can be applied to predict how consumer behavioral changes to influence whose behavioral consumption to the manufacturer products sale within one to two years short term or three to five years middle term, even above five years long term business plans. Hence, if the product manufacturers can apply the most suitable consumer behavioral prediction method to predict how consumers' choice will be changed to influence their products sale easily. It will have more beneficial intangible and tangible advantages to achieve the their product easier sale aim to ensure their businesses' future market share to be increased more easier to their countries' choice target sale markets. Otherwise, if they applied the inaccurate consumer behavioral prediction methods to predict how their consumers' behavioral changes wrongly. Then, it will influence their market shares to be same level, even it will decrease their market shares, when their consumer behavioral prediction inaccurately. In my this book first part, I concentrate on indicate whether any artificial intelligence (AI) tools will be one kind of good consumer behavioral prediction method to be choose to apply to predict consumer behaviors. I shall indicate some examples, cases to give reasonable evidences to analyze whether (AI) tools will be one kind suitable tool to be applied to predict when and how consumer behavioral changes. If (AI) can be one kind tool to attempt to be applied to predict when and how consumer behavioral changes. Will it replace other kinds of methods to predict consumer behaviors? Does it have weaknesses to be applied to predict consumer behaviors, instead of strengths? Can it be applied to predict consumer behaviors depending on any situations of only some situation? Finally, I believe that any readers can find answers to answer above these questions in this book. In my this book second part, I shall explain why and how human can possible apply (AI) tool to predict consumer individual emotion. I shall indicate case studies to explain how consumer individual better or worse emotion how to influence whose consumption behavior in different suitations. Finally, I shall indicate evidences to conclude how and why (AI) tool that can be used to predict consumer individual emotion and it will have direct relationship to influence consumption behavior, as well as how (AI) tool can assist businessmen to judge whether what reasons case the customer does not choose to buy its product, it is possible because the product high price factor, poor product quality or poor staff service performance or attitude etc. different factors to influence the consumer decides to choose to buy the other product consequently, when the (AI) tool can confirm consumer has good or bad emotion to judge what factors are the causes his decision making at the moment.

Download or read book Why Is Big Data Gathering the Best Method to Predict Consumer Behavior written by Johnny Ch LOK and published by Independently Published. This book was released on 2018-10-28 with total page 567 pages. Available in PDF, EPUB and Kindle. Book excerpt: Why can (AI) be applied to predict consumer behaviors?Artificial intelligence refers to complex in vehicle market, machine learning that posses the same characteristics of human intelligence and that have all our sense, all our reason and think just like human do. Besides, machine learning is the practice of using algorithms to collect and examine data, learn from it, and then make a determination or prediction about something in the world.The machine is " trained" using large amounts of data and algorithms that give it the ability to learn how to automatically perform a task with increasing accuracy. Otherwise, deep learning is primarily based on artificial neural networks inspired by our understanding of the biology of human's brains.Deep learning breaks down tasks in ways that enables machines to assist us with increasingly complex tasks, driverless cars, better preventive healthcare and more accurate product recommendation ( including vehicle recommendations). So, such as why (AI) technology can be applied to predict how vehicle consumer behavior changes to bring to judge whether vehicle consumer will like what kinds of vehicle styles next year. Then, vehicle manufacturers can gather overall vehicle consumer data to analyze and conclude the more accurate vehicle design direction for next year any new design vehicle manufacturing products.Thus, (AI) machine learning can help vehicle manufacturers to solve how to design any new vehicle products challenge. A vehicle is both one of the most important and carefully considered purchases the majority of people will ever make in their lifetime. It is also a purchase that tends to be fundamentally tied to a person's identify and view of themselves. As the same time, vehicle consumers changing lifestyles result in changing vehicle needs, e.g. the young sport car enthusiast matures into the family driver. Automotive dealers need to remember that vehicle customers and prospects are individual human beings with risk, complex and ever-changing lives factors, these factors will influence every vehicle consumer why who feels has vehicle purchase need, and how who choose to buy the first vehicle if who decided to buy the first vehicle.The (AI) technological customer behavioral prediction tool seems to be the best vehicle salespeople in the world are those that know every one of their vehicle customers. Their likes and dislikes which style of vehicle design, preferences and changing tastes to vehicle choices. The capacity of the human brain, however, limits us from achieving this type of vehicle sales and frequent turnover at vehicle dealerships often results in the further loss of vehicle salespeople along with their vehicle customer relationships and knowledge. In this competitive vehicle environment, machine learning enables platforms to assist the vehicle sales team by tracking the vehicle consumer behaviors of each vehicle customer, learning and memorizing their preferences and predicting their future vehicle purchase needs.Finally, I recommend that for a vehicle dealerships marketing platform to make their customer engagement efficient and fully-functional, I should be able to: applying (AI) tools to track every vehicle customer behavior across the web, connecting to a society of data sources, CRM, DMS, third-party, web vehicle brands, social email, click etc., aggregating and accurately cross-reference data from a variety of sources, leveraging this data to drive insights on a mass scale, as well as on an individualized basis, driving actions and automatically direct customer engagement via multiple channels based on where each customer is in their individual lifecycle.

Download or read book Marketing Information Prediction and Artificial Intelligence Customer Psychological Prediction written by Johnny Ch Lok and published by Independently Published. This book was released on 2019-02 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: 1.1Why can (AI) be applied to predict consumer behaviors?Artificial intelligence refers to complex in vehicle market, machine learning that posses the same characteristics of human intelligence and that have all our sense, all our reason and think just like human do. Besides, machine learning is the practice of using algorithms to collect and examine data, learn from it, and then make a determination or prediction about something in the world.The machine is " trained" using large amounts of data and algorithms that give it the ability to learn how to automatically perform a task with increasing accuracy. Otherwise, deep learning is primarily based on artificial neural networks inspired by our understanding of the biology of human's brains.Deep learning breaks down tasks in ways that enables machines to assist us with increasingly complex tasks, driverless cars, better preventive healthcare and more accurate product recommendation ( including vehicle recommendations). So, such as why (AI) technology can be applied to predict how vehicle consumer behavior changes to bring to judge whether vehicle consumer will like what kinds of vehicle styles next year. Then, vehicle manufacturers can gather overall vehicle consumer data to analyze and conclude the more accurate vehicle design direction for next year any new design vehicle manufacturing products.Thus, (AI) machine learning can help vehicle manufacturers to solve how to design any new vehicle products challenge. A vehicle is both one of the most important and carefully considered purchases the majority of people will ever make in their lifetime. It is also a purchase that tends to be fundamentally tied to a person's identify and view of themselves. As the same time, vehicle consumers changing lifestyles result in changing vehicle needs, e.g. the young sport car enthusiast matures into the family driver. Automotive dealers need to remember that vehicle customers and prospects are individual human beings with risk, complex and ever-changing lives factors, these factors will influence every vehicle consumer why who feels has vehicle purchase need, and how who choose to buy the first vehicle if who decided to buy the first vehicle.The (AI) technological customer behavioral prediction tool seems to be the best vehicle salespeople in the world are those that know every one of their vehicle customers. Their likes and dislikes which style of vehicle design, preferences and changing tastes to vehicle choices. The capacity of the human brain, however, limits us from achieving this type of vehicle sales and frequent turnover at vehicle dealerships often results in the further loss of vehicle salespeople along with their vehicle customer relationships and knowledge. In this competitive vehicle environment, machine learning enables platforms to assist the vehicle sales team by tracking the vehicle consumer behaviors of each vehicle customer, learning and memorizing their preferences and predicting their future vehicle purchase needs.Finally, I recommend that for a vehicle dealerships marketing platform to make their customer engagement efficient and fully-functional, I should be able to: applying (AI) tools to track every vehicle customer behavior across the web, connecting to a society of data sources, CRM, DMS, third-party, web vehicle brands, social email, click etc., aggregating and accurately cross-reference data from a variety of sources, leveraging this data to drive insights on a mass scale, as well as on an individualized basis, driving actions and automatically direct customer engagement via multiple channels based on where each customer is in their individual lifecycle.

Download or read book Why People Buy Things They Don t Need written by Pamela Danziger and published by Kaplan Publishing. This book was released on 2004-07-01 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Consumers shop to satisfy emotional needs and desires-if a company is selling to emotion, then it's in the business of luxury. What motivates consumers to buy? Is it pleasure? Education? Entertainment? Status? Or just an impulse? Knowing why consumers buy what they do is the secret to predicting how they will behave in the ever-changing marketplace. In most cases, much of what people buy are items they really don't need. Focusing on the ""whys"" of spending, Danziger has meticulously profiled customers in more than 30 categories of discretionary spending through research based on surveys, interviews, and focus groups from a variety of people who make discretionary purchases. She provides readers with a vision of the future, giving them the foresight to anticipate the needs and desires of their customers. This groundbreaking guide will help marketers of all products understand the underlying motivators consumers use to both make their purchases and become satisfied, loyal customers. In Why People Buy Things They Don't Need, Danziger examines: * The 14 justifiers that give consumers ""permission"" to buy. * Trends impacting why people purchase what they do. * How to sell even more to these customers. * The future of discretionary spending.

Download or read book Artificial Intelligence Predicts Consumer Behaviors written by Johnny Ch LOK and published by . This book was released on 2020-02-16 with total page 727 pages. Available in PDF, EPUB and Kindle. Book excerpt: Challenge to using (AI) neural networks to predict customer behavior from big data gather tool(AI) big data gather tool will encounter the challenge: How can predict customer behavior be represented as sequential data describing the interactions of the customer with a company or an (AI) data gather system through the time, e.g. these interactions are items that the customer purchase or views ? So, every customer data gather , (AI) needs to spend time to analyze how and why to cause whose consumption behavioral choice. It is too difficult matter or judgement for (AI) learning. So, (AI) needs to spend time to learn how to analyze every customer's shopping behavior or actin in order to gather all different consumers' past shopping action information in order to help business owners to predict future its potential customer shopping behavior how to change more clear and accurate prediction. (AI) big data gather tool needs to learn to know that how to judge every customer interaction likes purchases over time can be represented with sequential data. Sequential data has the main property that the order of the information is important. Many (AI) machine learning models are not suited for sequential data, as they consider each input sample independent from previous ones. Therefore, at the end of the sequence, (AI) big data gather learn machines need to keep in their internal state of every customer purchase data, kind of product or service, price , whole year consumption times form all previous inputs, making them suitable for this type of data.However, consumer behavior can be represented as sequential data describing the interactions through the time. Examples of these interactions are the items that the user purchases or views. Therefore, the history of interactions can be modeled as sequential data, which has the particular trial that an incorporate a temporal aspect. For example, if a user buys a new mobile phone, who might purchase accessories for this mobile phone in the near future or it the user buys a electronic book or paper book , he might be interested in books by the same author. Therefore, to make accurate predictions is important to model this temporal aspect correctly. To solve this predictive challenge of consumers to buy the product. One count the number of purchased products of a particular category in the last N days, or the number of days since the last purchase.So, the (AI) big data gather designers can attempt to produce a feature vector which can be fed into a machine learning algorithm such as " logistic regression" will be the main feature and function to any (AI) big data gather machine to learn how to apply this " logistic regression" function or feature to predict any customer behavioral change for any product purchase or service consumption to the (AI) predictive consumer behavioral business users. Every different kinds of product purchases or services consumption will be needed to design " different model of logistic regression" in order to follow the kind of business to predict whose consumer purchase or service consumption behavior to predict more accurate.

Download or read book Anthropological Approaches to Understanding Consumption Patterns and Consumer Behavior written by Chkoniya, Valentina and published by IGI Global. This book was released on 2020-04-03 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: Anthropology is a science specialized in the study of the past and present of societies, especially the study of humans and human behavior. The disciplines of anthropology and consumer research have long been separated; however, it is now believed that joining them will lead to a more profound knowledge and understanding of consumer behaviors and will lead to further understanding and predictions for the future. Anthropological Approaches to Understanding Consumption Patterns and Consumer Behavior is a cutting-edge research publication that examines an anthropological approach to the study of the consumer and as a key role to the development of societies. The book also provides a range of marketing possibilities that can be developed from this approach such as understanding the evolution of consumer behavior, delivering truly personalized customer experiences, and potentially creating new products, brands, and services. Featuring a wide range of topics such as artificial intelligence, food consumption, and neuromarketing, this book is ideal for marketers, advertisers, brand managers, consumer behavior analysts, managing directors, consumer psychologists, academicians, social anthropologists, entrepreneurs, researchers, and students.

Download or read book Can Apply Artificial Intelligence to Predict Consumer Behavior In Any Business Environment written by Johnny Ch Lok and published by Can Apply Artificial Intellige. This book was released on 2018-09-09 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Prepare This book has these two research questions need to be answered? (1) Can apply (AI) learning machine predict consumer behaviors? (2) Can (AI) learning machine replace human marketing research method, e.g. survey or human psychological and micro and macro economic methods to predict consumer behaviors more accurate? Nowadays, many businessmen or marketing research professional hope to apply different methods to predict consumer behaviors in order to know what will be future market activities and market changes to help them to choose to implement what kinds of marketing strategies more accurately. The methods include economic environmental change prediction method, consumer individual psychological change prediction method, micro or macro behavioral economic environmental change prediction method, marketing environmental change prediction method etc. different kinds of methods which can be applied to predict how consumer behavioral changes to influence whose behavioral consumption to the manufacturer products sale within one to two years short term or three to five years middle term, even above five years long term business plans. Hence, if the product manufacturers can apply the most suitable consumer behavioral prediction method to predict how consumers' choice will be changed to influence their products sale easily. It will have more beneficial intangible and tangible advantages to achieve the their product easier sale aim to ensure their businesses' future market share to be increased more easier to their countries' choice target sale markets. Otherwise, if they applied the inaccurate consumer behavioral prediction methods to predict how their consumers' behavioral changes wrongly. Then, it will influence their market shares to be same level, even it will decrease their market shares, when their consumer behavioral prediction inaccurately. In my this book first part, I concentrate on indicate whether any artificial intelligence (AI) tools will be one kind of good consumer behavioral prediction method to be choose to apply to predict consumer behaviors. I shall indicate some examples, cases to give reasonable evidences to analyze whether (AI) tools will be one kind suitable tool to be applied to predict when and how consumer behavioral changes. If (AI) can be one kind tool to attempt to be applied to predict when and how consumer behavioral changes. Will it replace other kinds of methods to predict consumer behaviors? Does it have weaknesses to be applied to predict consumer behaviors, instead of strengths? Can it be applied to predict consumer behaviors depending on any situations of only some situation? Finally, I believe that any readers can find answers to answer above these questions in this book. In my this book second part, I shall explain why and how human can possible apply (AI) tool to predict consumer individual emotion. I shall indicate case studies to explain how consumer individual better or worse emotion how to influence whose consumption behavior in different situation. Finally, I shall indicate evidences to conclude how and why (AI) tool that can be used to predict consumer individual emotion and it will have direct relationship to influence consumption behavior, as well as how (AI) tool can assist businessmen to judge whether what reasons case the customer does not choose to buy its product, it is possible because the product high price factor, poor product quality or poor staff service performance or attitude etc. different factors to influence the consumer decides to choose to buy the other product consequently, when the (AI) tool can confirm consumer has good or bad emotion to judge what factors are the causes his decision making at the moment. Readers can understand why and how (AI) tool can be attempt to be applied to predict customer emotion and it can influence positive or negative consumption behavior to the product clearly in this part.

Download or read book What Are Marketing Information and Artificial Intelligence Customer Psychological Predictive written by Johnny Ch Lok and published by Independently Published. This book was released on 2019-01-04 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: (AI) digital data gather technology predicts food consumer behavior's main barriersWhat are the main barriers to food industry? When the food manufacturer applies (AI) big data gather technology to predict food consumer behavior? The barriers include that the food manufacturer / provider needs to decide whether when the right time is applied to the right (AI) digital big data prediction tool channel to find the right food consumers to be chose to full food consumption satisfactory questionnaires, how to gather multi-class food consumption classifiers on real-world food consumers transactional data from the food sale domain consistently to show the critical numbers of different kinds of food items at which the predictive performance most accurate? So, any food manufacturer / provider's advanced in (AI) digital data gather warehousing and management technologies can provide that opportunities for food business to enhance long term relationship with the food providers' clients. However, food industry's (AI) digital data gather aims to improve food customer product targeting, increase food customer loyalty and food purchase probability to the food supplier. To effective identify, understand and satisfy the needs of their food customers, the food suppliers need to develop the right (AI) digital questionnaire questions and find the right food customers to fill every right questions from every digital questionnaire at the right time through the right channel. Above of all these, they will be the barriers when one food supplier expects its (AI) digital data gather questionnaires which can conclude the most accurate prediction concerns any kinds of consumer food product choices. So, such as (AI) digital data prediction model, it is needed to incorporate into the food market segmentation, food customer targeting, and food challenging decisions with the goal of maximizing the total food customer lifetime. For example, (AI) big data gather transaction data is reasonable and accurate for building predictive models. Transaction data can be electronically collected and readily made available for data mining in lot quantity at minimum extra costs.Suggestion to apply (AI) prototypes of food customer profiles method to predict food customer behavioral changes. Prototypes of food customer profiles mean to be extracted from the discovered bins and multi-class classifies models are built using those prototypes. The learned models can than be used to predict the class of food customer profiles ( e.g. restaurants, school canteens, supermarkets etc. food suppliers) based on their food purchases. The approach is validated on the case study of a food retail and food service company operating in food and beverages market.So, a food customer profile, it is a description (AI) data gather tool will record every of food customer using available information, which help in understanding their background and food consumption behavior. (AI) data gather tool can well develop every food customer profile, every food customer data is essential in food market analysis as they aid food suppliers in saving time and money by highlighting the real potential food consumers whose needs are to be met rather a range of individuals.So, (AI) data gather tool can record every food consumer profile and every can be factual or behavioral food consumption. A factual food customer profile consists of a set of characteristics for (AI) big data gather record, e.g. demographic information, such as food customer name, gender, birth date, when a behavioral food customer profile consists of what the food customer is actually doing and is usually derived from (AI) digital transactional data gather record.

Download or read book Can Apply Artificial Intelligence to Predict Consumer Behavior in Business Envi written by Johnny Ch lok and published by . This book was released on 2018-09-13 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: In my this book first part, I concentrate on indicate whether any artificial intelligence (AI) tools will be one kind of good consumer behavioral prediction method to be choose to apply to predict consumer behaviors. I shall indicate some examples, cases to give reasonable evidences to analyze whether (AI) tools will be one kind suitable tool to be applied to predict when and how consumer behavioral changes. If (AI) can be one kind tool to attempt to be applied to predict when and how consumer behavioral changes. Will it replace other kinds of methods to predict consumer behaviors? Does it have weaknesses to be applied to predict consumer behaviors, instead of strengths? Can it be applied to predict consumer behaviors depending on any situations of only some situation? Finally, I believe that any readers can find answers to answer above these questions in this book. In my this book second part, I shall explain why and how human can possible apply (AI) tool to predict consumer individual emotion. I shall indicate case studies to explain how consumer individual better or worse emotion how to influence whose consumption behavior in different situation. Finally, I shall indicate evidences to conclude how and why (AI) tool that can be used to predict consumer individual emotion and it will have direct relationship to influence consumption behavior, as well as how (AI) tool can assist businessmen to judge whether what reasons case the customer does not choose to buy its product, it is possible because the product high price factor, poor product quality or poor staff service performance or attitude etc. different factors to influence the consumer decides to choose to buy the other product consequently, when the (AI) tool can confirm consumer has good or bad emotion to judge what factors are the causes his decision making at the moment. Readers can understand why and how (AI) tool can be attempt to be applied to predict customer emotion and it can influence positive or negative consumption behavior to the product clearly in this part. This book third part has these two research questions need to be answered?(1) Can apply (AI) learning machine as well as micro and macro economic methods predict consumer behavioral changing?(2) Can (AI) learning machine replace human marketing research method, e.g. survey or human psychological and micro and macro economic methods to predict consumer behaviors more accurate? The part indicates whether micro and macro economic methods can be attempted to apply to predict when, how and why consumer behavioral changing for every kind of different business. The second part indicates whether artificial intelligence can be attempted to apply to predict when, how and why consumer behavioral changing for every kind of different business.

Download or read book How Ai Predicts Consumer Behavior in Economic Environment written by Johnny Ch LOK and published by . This book was released on 2020-09-10 with total page 75 pages. Available in PDF, EPUB and Kindle. Book excerpt: It seems that in future, (AI) machine learning will allow search to evolve even further. Search engineers will deliver refined recommendations to their business users and use less human input to predict consumers' needs. For IBM computer example, it indicated 90% of the data that exists today has been created in the last two years. This huge explosion of data gives brands the opportunity to quickly spot and react to the latest trends, fashion and fads among its clients and potential clients. This will allow companies to better engage with younger consumers, who gain influence access to the latest trends, and use the brands. They associate with to help define who they are as individuals. Thus, brands have to identify and make use of them before consumers move on, but the vast quantity of data available makes. This a resource-intensive task. For next example, Lesara, a based online clothes store, uses this machine learning to inform its product decision often gathering information from internal and external sources. When its trends -spotting shoes. Lesara has a range of over 20 styles and sells hundreds of pairs a day. It focus on giving consumers, the very latest trends allow Lesara to develop on average of 50,000 new items each year. It compared to 11,000 old items each year. Thus, (AI) brain seems to human brain to own analytical ability to predict consumer behaviors. For another example, Lesara is one online clothes store, uses machine learning decisions after gathering information from internal and external sources. One of its most popular products, shoes with LED started life when its trend spotting software flagged up a blogger wearing similar shoes. Now Lesara has a range of over 20 styles and sells hundreds of pairs a day. Its focus on giving consumers the very latest trends allows Lesara to develop an average of 50,000 new items each year, compared to 11,000 for its competitor Lara. it seems (AI) machine learning can help Lesara business to predict what kinds of shoes design or style that shoe consumers will prefer choose to buy in future shoe market trend. Thus, Lesara can predict shoe consumers' taste successfully and it can manufacture many attractive style of shoes. (AI) machine learning can gather global past shoe consumer's shoe shopping experiences, then analyzes to make conclusion to give lesara recommendation successfully. This will make the experience more enjoyable for shoe consumers and allow Lesara to advert whose different new style or design of shoes to deliver them move relevant messages by understanding the context of the experience.However, (AI) machine learning will have this risk who manufacturers need to concern if they applied this technology to predict consumer behavior. It is on sample consumers' privacy issue, in order to avoid complaint chance occurrence. However, machine learning can tie this data together to identify which f the billions of devices are being used by individual consumers. This helps brands understand how consumer engagement and actions can be attributed to different messages in different contexts and at different time. So, machine learning can help brands to build confidence to promote their products by any advertisement channels. When, this new (AI) machine learning technology can conclude how to design their products to be the most attractive, due to it has more accurate to predict consumer behaviors to compare human themselves prediction judgement effort. It seems that (AI) machine judgement effort is more accurate to compare to human judgment effort.

Download or read book Predicting Consumer Behavioral Methods written by Johnny Ch Lok and published by Independently Published. This book was released on 2018-10-17 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: PrefaceThis book is concerned how to apply behavioral economy method to predict consumer behavior. Also I shall compare to explain what advantages and disadvantages between any one of my solvable suggestions and the any one of the company's choice of solvable method to these any one sample industry consumer behavioral economic challenges to aim to let any reader to judge whether how to choose the solvable method is better. This book can provide sample industries to let students to learn how to behavioral economy method to predict consumer behaviors. This book divides part one and part two. Part one explains what behavioral economy function and mean is and how applying this method to predict consumer behavior. Part two explains what psychological method mean and function and how appling this method to predict consumer behavior.In Behavioral economics part, it can provide more realistic psychological foundations. This book is intended to explain why consumer behaviors and economy has close relationship and apply economic concept to explain how the consumer chooses to do whose consumption of decision. In part one, it shall indicate how the process of behaviour economic field develops, then I shall show what methods are used to measure behavioural economy. Next, I shall indicate what the main two categories of behavioural economy are as well as I shall explain what risky and uncertain outcomes of individual behavior economic theories are as well as what behavioral game theory is. Finally, I shall explain how policy makers or decision makers can apply behavioral economy concept to do whose policy decision as well as I shall also indicate why behavioral economy and psychology which has close relationship to influence consumption of decision. In this part, I shall indicate underground train and Disney entertainment theme park and University and unground train transportation and environmental protection businessmen etc. enterprises to explain how which can apply psychological methods to predict which client's preferable behavioral choice to achieve economic benefits more easily. Thus, if company or individual businessman can predict labour psychology or client psychologic consumption behavior. Then, which can have more confidence to attract more clients or reduce labour turnover. This book is suitable to any economists or policy makers or individual consumption makers or students or businessmen who have interest to learn how to apply behavioural economy methods to judge to do the most reasonable or the most right economic activities to achieve economic benefit in everyday life.

Download or read book Psychological Methods to Predict Behavioral Consumption written by Johnny Ch LOK and published by . This book was released on 2017-07-12 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to be given my opinions to any businessmen to learn how to apply different kinds of psychological methods to predict how to make behavioral consumption will be caused more easily. I shall introduce the different kinds of behavioral consumption of prediction methods include: the standard economic model of behavioral consumption of prediction method, online psychological advertising of prediction method, brand image attention of behavioral consumption of prediction method, store atmosphere environment influence prediction method, knowledge of the factors prediction method, constructive consumer choice processes influence prediction method, survey research prediction method ,consumer neuroscientific research prediction method etc. different psychological research of consumption methods. I shall indicate that how to predict customer behavior in marketing view point, analyzing and predicting consumer behavior can include demographics, personality, personal values and lifestyles. First, demographics is the size, structure and distribution of a population. How marketers use demographic analysis as market segment, descriptors and in trend analysis to predict customer behavior as well as how consumer analysts use demographic trends to predict changes in demand for and consumption of specific products and services. To explain how demographic analysis provides information for social policy and demographics used in analyzing policy questions related to the aggregate performance of marketing in society ( macro marketing) to predict how industrial demand is ultimately derived from consumer demand. I shall explain why analysis of demographic trends is only important for industrial and business-to-business marketing and why it can't concentrate on consumer individual consumption marketing both as well as to explain why in an individual firm, which must understand not only the customer's minds, but also the minds of the customers'and to explain how to apply demographic analysis to predict consumer behavior factors include: changing structure of markets , geographic factors, economic resources and global markets. I shall explain why market analysis requires information about consumers with needs, ability to buy, willingness to pay and authority to pay, changing structure of consumer markets, such as how many consumers will there be? e.g. birthrate, national increase, fertility rate, total fertility rate, population momentum etc. information. In my this book, the main important aim, I give examples to explain how to apply psychological view point methods to predict consumer individual behavior to let businessmen learn how to choose the reasonable or right methods to attract consumers to choose to buy whose products or consume whose services to win competitors more easily.