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Author: Johnny Ch LOK Publisher: ISBN: 9781791311704 Category : Languages : en Pages : 555
Book Description
Can apply artificial intelligent learning machine " big data" gathering method to predict manufacturers' behavioral performance ?In consumer view point, can they apply (AI) learning machine to predict manufacturers' behavioral performance to judge whether whose products are value to buy. Nowadays, (AI) and big data are reshaping the risk in consumer privacy. For example, consumers want to hide their willingness to pay just as firms want to hide their real marginal cost, and buyers have less favorable information, say a low credit shore, prefer to withhold it just as sellers want to conceal poor product quality. So, it implies that it is possible (AI) learning machine can help customers to gather any manufacturers' past sale performance, e.g. how many complaints or appreciation from clients, product quality etc. sale data to let consumers to make judgement whether it is value to buy to compare other competitors. So, it has risk to the poor product quality of manufacturers. Otherwise, it has benefits to the good product quality of manufacturers. It also implies all manufacturers' privacy is not protected or secret when (AI) learning machine is popular to be used to predict manufacturers' behaviors by consumers.Information economists suggest that both buyers and sells have an incentive to hide or reveal private information, and these incentives are crucial for market efficiency. Data technology that reveals consumers type could facilitate a better match between product and consumer type, and data technology that helps buyers to assess product quality could encourage high quality production. Thus, (AI) big data technology can also assist consumers to gather different manufacturers' data to compare what their advantages and disadvantages of their products are. Then, consumers can make comparison to choose which brand of product is the suitable to whom to buy in these more choice consumption market. (AI) learning machine will gather similar brand their products' data to analyze to make conclusion to let consumers know or feel to make final judge to find what advantages or disadvantages of these sample brands of similar products' comparison from internet. On the other hand, it means that manufacturers can gather consumers' past purchase behaviors or purchase experience from (AI) big data gathering method to record and analyze to give opinions to let manufacturers to know what reasons or factors influence consumers choose not to buy their products from internet.(AI) big data gathering consumer behavior prediction method can give these benefits to manufacturers and consumers both, such as: New concerns arise because (AI) technological advance which have enables reducing cost of collecting, storing, processing and using data in mass quantities extend information beyond a single transaction. These advances are often summarized by the big data, it means charge volume of transaction-level data that could identify individual consumers by itself or in combination with the datasets.The popular (AI) takes big data as in input in order to understand, predict and influence consumer behavior. Modern (AI) is used by legitimate companies, could improve management efficiency motivate innovations and better match demand and supply. But (AI) in the wrong hand, also allows the mass production of fraud and deception. Since , data can be stored, traded and used long after the transaction. Future data use is likely to grow with data processing technology, such as (AI) big data gathering consumer and manufacturer behavioral prediction method from internet channel.
Author: Johnny Ch LOK Publisher: ISBN: 9781791311704 Category : Languages : en Pages : 555
Book Description
Can apply artificial intelligent learning machine " big data" gathering method to predict manufacturers' behavioral performance ?In consumer view point, can they apply (AI) learning machine to predict manufacturers' behavioral performance to judge whether whose products are value to buy. Nowadays, (AI) and big data are reshaping the risk in consumer privacy. For example, consumers want to hide their willingness to pay just as firms want to hide their real marginal cost, and buyers have less favorable information, say a low credit shore, prefer to withhold it just as sellers want to conceal poor product quality. So, it implies that it is possible (AI) learning machine can help customers to gather any manufacturers' past sale performance, e.g. how many complaints or appreciation from clients, product quality etc. sale data to let consumers to make judgement whether it is value to buy to compare other competitors. So, it has risk to the poor product quality of manufacturers. Otherwise, it has benefits to the good product quality of manufacturers. It also implies all manufacturers' privacy is not protected or secret when (AI) learning machine is popular to be used to predict manufacturers' behaviors by consumers.Information economists suggest that both buyers and sells have an incentive to hide or reveal private information, and these incentives are crucial for market efficiency. Data technology that reveals consumers type could facilitate a better match between product and consumer type, and data technology that helps buyers to assess product quality could encourage high quality production. Thus, (AI) big data technology can also assist consumers to gather different manufacturers' data to compare what their advantages and disadvantages of their products are. Then, consumers can make comparison to choose which brand of product is the suitable to whom to buy in these more choice consumption market. (AI) learning machine will gather similar brand their products' data to analyze to make conclusion to let consumers know or feel to make final judge to find what advantages or disadvantages of these sample brands of similar products' comparison from internet. On the other hand, it means that manufacturers can gather consumers' past purchase behaviors or purchase experience from (AI) big data gathering method to record and analyze to give opinions to let manufacturers to know what reasons or factors influence consumers choose not to buy their products from internet.(AI) big data gathering consumer behavior prediction method can give these benefits to manufacturers and consumers both, such as: New concerns arise because (AI) technological advance which have enables reducing cost of collecting, storing, processing and using data in mass quantities extend information beyond a single transaction. These advances are often summarized by the big data, it means charge volume of transaction-level data that could identify individual consumers by itself or in combination with the datasets.The popular (AI) takes big data as in input in order to understand, predict and influence consumer behavior. Modern (AI) is used by legitimate companies, could improve management efficiency motivate innovations and better match demand and supply. But (AI) in the wrong hand, also allows the mass production of fraud and deception. Since , data can be stored, traded and used long after the transaction. Future data use is likely to grow with data processing technology, such as (AI) big data gathering consumer and manufacturer behavioral prediction method from internet channel.
Author: Johnny Ch Lok Publisher: Independently Published ISBN: 9781720160410 Category : Business & Economics Languages : en Pages : 174
Book Description
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.
Author: Johnny Ch Lok Publisher: Independently Published ISBN: 9781793104038 Category : Business & Economics Languages : en Pages : 254
Book Description
Economic science or economic art methods predict consumer behaviorEconomic is both a science and art. Economic is considered as science because systematic knowledge derived from observation, study and experimentation. An art is the practical application of knowledge for achieving definition ends. A science teaches us to know a phenomenon and art traches us to do a thing. How to apply economic science or art method to predict consumer behavior? for example, there is a inflation US this year. This information is derived from positive science. The government takes certain fiscal and monetary measures to bring down to general level of prices in the country. The study of the monetary measures to bring down inflation makes the subject of economics as an art. Hence, as this case, if US government applies economic science or art method to predict this year will have inflation in US, then US government will attempt to avoid social general product prices to be raised, due to inflation influence. It aims to avoid US consumers reduce consumption desire in this year.For another example, nothing could be more useful than water. But in much of the world waste is plentiful enough that another glass more or less matters little to a fresh water supply agent businessman. So, water is chap. But, if any offices buy bottle of glass fresh water to let employees to drink. It will bring advantages that they do not spend time to buy water to drink when they are working in the office time in any offices as well as employees do not need to heat water to drink to waste time to work in offices. So, the bottle of fresh drinking water supply agent is one kind of drinking water product monopoly fresh drinking water supplier to supply fresh drinking water to satisfy office employees who do not need to spend time to heat water to drink in offices. Hence, it is possible that replace other different kind taste of drink or office employees themselves heat water drink in offices. It is general office employees' drinking habits and drinking choice in offices popularly. So, the bottle of fresh drinking water supply agents will concentrate on selling their fresh drinking water to office employee customers only in global fresh drinking water consumption target market. The office employees must be fresh drinking water companies' main target consumers.What is economic laws qualitative or quantitative method to predict consumer behavior? Law of economic are qualitative in nature. They are not exactly stated in quantitative terms. They tell the direction of change which is expected rather than the amount of change. For example, according to the law of consumer demand, the quantity demanded varies inversely with price, We don't say that 10% rise in price will lead to 30% fall in the customers' quantity demand.What is economic merits of deduction method? This method is near to reality. It is less time consuming and less expensive. the use of mathematical techniques in deducing theories of economics brings exactness and clarity in economic analysis. The deductive method is highly abstract. It require a great deal of care to avoid bad logic or faulty economic reasoning. This method makes conclusions to predict consumer behavior, due to reliance on imperfect and correct assumptions. It involves the process of reasoning from particular facts to general principle on the basic of experimentations, observations and statistical methods. In this method, data is collected about a certain economic phenomenon. There are systematically arranged and the general conclusions are drawn from them.What are the advantages of inductive method to predict consumer behavior? It is based on facts as such the method is realistic. In order to test the economic principles, method makes statistical techniques. The inductive method is therefore more reliable, inductive method is dynamic
Author: Johnny Ch Lok Publisher: Independently Published ISBN: 9781731438157 Category : Languages : en Pages : 554
Book Description
How AI technology influnce productivities and service performance ? Whether it can raise productivities and improve service performance?This book aims to explain why and how future artificial intelligent technology ( big data gathering method) can be applied to assit businesses to predict why and when and how consumer behavior changes. I shall explain why traditional psychological and statistic and marketing methods are applied to predict consumer behaviors, human's judgement and analytical effort will be worse to compare AI machine's judgement and analytical effort. Also, I shall indicate different business organizations why they apply AI big data gathering method to help them to design any questionnaires ( surveys) questions which will be more valid and useful to conclude human's questionnaires ( surveys) design questions method.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.
Author: Johnny Ch LOK Publisher: ISBN: 9781795405935 Category : Languages : en Pages : 253
Book Description
How to apply media economic methods to predict media consumer's psychology? Some media economists believe the market structure-conduct performance model is as a tool for analysis, it has been widely used in the study of media markets and industries, such as book publishing industry. How to choose the attractive topic for every book product structure? They believe attractive book structure will help book structure firm to grow reader numbers. So, book topic and content factor is more influential to raise reader number more than cheaper book price sale factor.In its most simply for the industries organizational model indicates that of the structure of the market is known, it allows explanation of the likely conduct and performance among firms. For example, in terms of market structure, the variables used for analysis include the numbers of sellers/buyers, e.g. US publishing book market number of US book reading publishers/number of US book publishing sellers every year in US book publishing market; product differentiation, e.g. US different topic and content of electronic book or paper book product ; barriers to entry, e.g. economic recession, tariff book import tax, limitation of import book number etc. different external barriers factors to influence overseas ( foreign) book publishing import to US to sell their paper books ; cost structures, e.g. US book publishing firms need to spend how much printing expenditure to print high quality paper production of every paper book to sell and the degree of vertical integration, e.g. US book publishing firms how to choose middlemen to help them to sell books, e.g. themselves book publishing shops, other book retailers, themselves electronic book publishing website online platform sale channel or other book publishing sellers' websites online platform sale channel etc. different channels to sell the paper of electronic books to US readers. Hence, predicting the country' book market structure, it will have more confidence to evaluate book publishing competitors' effort and book sale price and how to design book content and topic to raise reading quality to let readers to feel much attractive to choose to buy the books from the book publishing shop.Media economics research is in the sense that many different types of methods are used to answer research questions and investigate hypotheses. However, many economists accept to choose to apply any one of methods to predict media reader behavior, such as trend studies, financial analysis, econometrics and case studies.Trend studies compare and contrast data over a time series. In assessing media concentration. Most trend studies use annual data as the unit of analysis. Trend studies are useful, due to their descriptive nature and ease of presentation and they aid in analyzing the performance of media companies and industries, e.g. study of changes in newspaper pricing and subscription costs.Financial analysis is another common methodological tool used in media economics research. Financial analysis can take many different forms and use different types of data. The most common data include information derived from financial statements and the use of various types of financial ratio.Econometrics involves the use of statistical and mathematical models to verify and develop economic research questions, hypotheses and theory.Case studies represent another useful method in media economics research. Case studies are popular because they allow a researcher to gather different types of data as well as different methods. Case studies in media economics research tend to be very targeted and focused examinations.
Author: Johnny Ch Lok Publisher: Independently Published ISBN: 9781793111111 Category : Languages : en Pages : 254
Book Description
Part ThreeEconomy And Marketing Predictive MethodChapter OnePsychological method predictsconsumer behavior1.1Can apply economic models solve marketing changing challenges?Economists indicate economic modeling can provide a logical, data to help organize the analyst's thoughts. The model helps the economist logically isolate and sort out complicated chains of cause and effect and influence between the numerous interacting elements in an economy. There are four types of models used in economic analysis: Visual models, mathematical models, empirical models and simulation models.Visual models are simply pictures of an abstract economy: graphs will lines and curves that tell an economic story. It is one kind of micro or macro-economic method to predict consumer behavioral change. Some visual models are diagrammatic such as which flow the income thought the economy from one sector to another ( micro economic environment). It is mathematical model, when it is presented the mathematics are explained what the data analysis is or not. The model does not normally require a knowledge of mathematics, but still allow the presentation of complex relationship between economic variable.For example, the common supply-and demand model is meant to show the effect of inflationary expectations upon price and output. In this application, an increase in inflationary expectations causes demand to shift, raising prices and outputs (macro-economic environment). For another example, a very simple micro-economic model would include a supply function (explaining the behavior of products or those who supply commodities to the market), a demand curve ( explaining the behavior of purchasers) and an equilibrium equation, specifying the simple conditions that must be met if the model's equilibrium is to be satisfied. So, the variables in a model like this represent a type of economic activity (such as demand) or data ( information ) that either determines or is determined by that activity ( such as a price or interest rate variable change activity).Dynamic models, in contrast, directly incorporate time into their structure. This is usually done in economic modeling by this mathematical systems of difference of differential equations. For example, it can use a difference equation from a business cycle model, investment now depends upon changes in income in the past. Time is incorporated into the model. Dynamic models, when they can be used, sometimes better represent the business cycles, because certainly behavioral response and timing strongly shape the character of a cycle. For another example, if there is a delay between the time income is received and when it is spent. A model that can capture the delay is likely to those higher consumption desire to the consumer. It is a micro-personal behavioral consumption predict method. So, the user can experiment with an endless variety of values and assumptions to see whether results obtained are realistic or insightful. Since computers are now powerful and cheaper, the importance of dynamic simulation models should follow the future prediction time, when the consumer income receive and when it is spent to predict how much degree of the consumer's consumption desire in micro-economic view point.Another model to be applied to predict consumption behavior. It is expectations and enhanced model, it includes one or more variables based upon economic expectations about future values. For example, if consumers for whatever reason, expect the inflation rate to be much higher next year, then this year, they are said to have formed inflationary expectations. If numerical values are being used in a model and the current inflation rate is 9%, if they expect inflation to be higher next year, the variable for inflationary expectations might be given be a value if 12% or more.
Author: Johnny Ch Lok Publisher: Independently Published ISBN: 9781795404198 Category : Business & Economics Languages : en Pages : 254
Book Description
Chapter TwoWhat is (AI) deep learning techniques to forecast environment behavioral consumptionThe (AI) deep-learning technology leads to performance enhancement and generalization of artificial intelligent technology. It influences the global leader in the field of information technology has declared its intention to utilize the deep-learning technology to solve environmental problems, such as climate change. So, it will help agriculture farming businesses can raise any plant food: vegetable, fruit, rice which grow up very easily if farmers can apply (AI) deep-learning technology to solve environment problems to influence their plant food grow. If the whole year seasonal change is very good and it is suitable for any plant food to grow in farming land easily, e.g. rain is enough and soil is enough for any plant food to grow in the farm lands. Then, fruit, rice, vegetable etc. agriculture businesses will have much beneficial attribution to global farmers. The question is how to use deep-learning technologies in the environmental field to predict the status of pro-environmental consumption. We predicted the pro-environmental consumption index based on Google search query data, using a recurrent neural network ( RNN model). To certify the accuracy of the index, we compared the prediction accuracy of the RNN model with that of the ordinary least square and artificial necessary network models. For example, the RNN model predicts the pro-environmental consumption index better than any other model. we expect the RNN model to perform still better in a big data environment because the deep-learning technologies would be increasingly as the volume of data grows. So, deep-learning technologies could be useful in environmental forecasting to prevent damage caused by climate change to influence any rice, vegetable, tomato, potato, fruit etc. different plant food grow in any countries' farming land easily.For South Korea example, over 800 government agencies spent 2.2 trillion Korea won on eco-products in 2014 year. However, green products are rarely purchased outside these agencies. This phenomenon occurs because there is a gap between consumer attitudes and behavior, that is environmental attitude is a major factor in decision making vis-a-vis the consumption of " green" food and services ( Jorea Ministry of Environment, 2015). Therefore, it is necessary to understand those consumer attitude, that will lead to sustainability-conductive behavior and consumption.2.1Environmental consumption predictionRecently, many researchers have studied pro-environmental consumption and household indexes as well as suicide rate predictions using messages posted by internet users on Google trend, Tweets etc. channel. Whether can environmental consumption be predicted by (AI) deep-learning technological internet channel? How can impact the pro-environmental consumption attitudes of green policies? Korea scientists estimated pro-environmental attitudes using search query data provided by Google trend and confirmed through regression analysis, that pro-environmental attitude has a positive correlation with the pro-environmental attitude index. They also explained that environment-friendly attitude of residents plan an important role in policy making. In the past, most household consumption indexed were calculated through surveys, but (AI) deep-learning technological tool " big data" have recently gained research attention ( Lee et al. 2016).It seems that (AI) deep-learning technology can help agricultural export countries' farmers, e.g. US, UK, Canada, New Zealand, Australia, Japan, China, India etc. they can predict environmental behavioral consumption to any rice, tomato, potato, fruit, vegetable etc. plant food consumers. The beneficial advantages to them include as below:
Author: Johnny Ch Lok Publisher: Independently Published ISBN: 9781793110862 Category : Languages : en Pages : 254
Book Description
ChapterSixIs Artificial Intelligent the most effective andaccurate consumer behavioral tool?Is (AI) the best and the most effective and accurate consumer behavioral prediction tool to compare other kinds of consumer behavioral prediction tools? Nowadays, retailing competitions are serious businessmen often find different kinds of methods to attempt to predict consumer changes. The consumer behavioral predictive methods can include as these below methods, instead of (AI) big data gathering tool.Firstly, statistics is the popular mathematic method, it applies auto-regression, liner regression, structural equation modelling, logistic regression statistic techniques to be used to predict consumer behaviors. Secondly, it is classification method, it sis a support vector machine to assist businessmen to make consumer behavioral prediction, it also includes decision making tress diagram technique. Thirdly, it is rule mining method, it is algorithm, market base analytic etc. business marketing concept analytical tool, it also includes graph mining technique tool. Next, it is psychological prediction model tool, it is psychology prediction model too, it is a kind of psychological method to predict consumer behaviors. Finally, it is the most updated and potential artificial neural network (ANN) machine tool, it gathered big data, then it will carry on analyzing and applies psychological method to conclude the most accurate and reasonable solutions to give recommendation to businesses to predict when and how and why their consumer behaviors will change. So, it is one owned human mind's machine and owned psychological and analytical efforts to replace humans to make any judgement in order to make the most accurate predictive behavioral changes for consumers, instead of the traditional marketing concept and psychological and mathematic methods to predict consumer behavior, (AI) big data gathering tool will be another new tool.What are the advantages of (AI) tool to be used to predict consumer behaviors as well as what are the different between it and other traditional consumer behavioral predictive tools? I shall explain as below: Firstly, as above all case studies are explained to (AI) questionnaire design method benefit, I believe (AI) big data gathering tool can be applied to help human to analyze and design any the suitable valid questions to enquire any kinds of business consumers in order to gather the most meaning and useful opinions to conclude the most accurate consumer behavioral prediction for every questionnaire. So, future (AI)'s analytical effort and decision making effort most be exceed above human's judgement efforts. So, future (AI) can help human to design the most useful and meaning different kinds of valid questionnaire ( survey) questions as well as assist humans to analyze and make accurate decision making and conclusions to give opinions to help businessmen to predict when consumer behaviors will change and how their consumption behaviors will change to influence their businesses in order to help them to make any efficient and effective and accurate solutions to avoid consumer number to be decreased and the most important benefit is that it can give opinions to help businessmen to explain why ( what the factors ) cause their consumer behaviors change suddenly. It will be human's efforts can not achieve to exceed (AI)'s efforts in the future.Secondly, (AI) can make artificial machine judgement and analytical effort, without human misleading or unfair or unreasonable judgement. So, it can make more fair and reasonable and accurate conclusion to give opinions to predict when, how and why consumer behaviors will change suddenly to the kind of business in customer model building process and evaluating the results of customer relationship management -related investment more accurate.
Author: Johnny Ch LOK Publisher: ISBN: 9781790252923 Category : Languages : en Pages : 62
Book Description
PrepareThis AI science fiction brings readers to image whether what are influenced by artificial intelligent big data gathering tool if it can be invented to replace human marketing research method to predict when, how and why consumer behaviors changes successfully. This book let readers to image themselve are such consumer behavior predictive professional how to apply AI tool to predict customer behavior changes for themselve example product industries in this consumer behavioral predictive journey.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, 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.
Author: Johnny C. H. Lok Publisher: Independently Published ISBN: 9781723774508 Category : Languages : en Pages : 572
Book Description
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.