Download or read book Artificial Intelligent Data Gathering Tool Predicts Travel Industry Consumer Behavior written by Johnny Ch LOK and published by . This book was released on 2018-10-13 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: The challenges of (AI) big data gather shapingthe future of retail for consumer industriesThe future of retail for consumer industries' (AI) big data gather challenges are similar to future travelling industry's entertainment consumption challenges. Another challenge of (AI) big data gather is that how to shape the consumer behavior to let business owner to feel or know oe predict. It means that how it express it's conclusion or opinion for every consumer behavior after it had gather all big data in any data gather period, e.g. three months, half year or one year consumer shopping model data gather period.Because every kind of industry, consumers will continue to demand price and quality change , with a wide range of convenient fulfilment options among of different kinds of products or services supply. Overall, the (AI) big data gather procedure gives opinion concerns every time retail experience will become more exciting, simple and convenient, depending on the consumer's ever-changing needs. So, I believe that (AI) big data gather every conclusion or result will be different, due to consumer's price and quality demand will often change to every kind of product or service supply in retail industry. So, how to shape (AI) big data gathering's analytical conclusion or result more clear. I shall recommend organizations need to build great understanding of and a stronger connection to increasingly empowered consumers before they plan and implement how to apply (AI) big data gather tool to predict consumer behavior as below:Firstly, (AI) is empowered by technology, the consumer is redefining value. The traditional measures of cost, choice and convenience are still relevant, but not control and experience are also important. Globally, consumers have access to more than 2 billion different products choice by a wide range of traditional competitors and dynamic new entrants, all experimenting with new business models and methods of client engagement. As choice increases, loyalty becomes more difficult familiarity and the consumer becomes more empowered. Businesses will have no choice and constantly innovate and disrupt themselves by meeting new technologies of high standards and expectations of consumers. So, (AI) data gather tool will need to follow different target group of consumers' needs to follow their different kinds of product design or style choice preferable to gather data in order to conclude the different target groups of consumer behavior to give opinion more clear and accurate to let businessmen to understand more clear how its customers' behavioral choice trend in the future half month, even to two years period.Secondly, businessmen need to adopt changing technologies rapidly. Technology will be the key driver of this retail industry. Industry participants will only success if they have a clear prediction to focus on how to using technology to increase the value added to consumers. They must , however, do so will I realistic assessment of their costs and benefits. Hence, (AI) big data gather technological tools will need to design to help them to gather data efficiently by these ways, such as the internet of things ( IOT), artificial intelligence (AI) machine learning, augmented reality (AR)/virtual reality (VR), digital traceability. So, future (AI) big data gather tool are predicted to be most influential customer behavioral positive emotion changing tool for retail , due to their widespread applications , ability to drive efficiencies and impact on labor in order to impact consumer behavior changing effort from negative emotion to positive.

Download or read book Artificial Intelligent Data Gathering Tool Predicts Retail and Service Industry written by Johnny Ch LOK and published by . This book was released on 2020-08-12 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: Is 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.

Download or read book Is Artificial Intelligence The Best Traveler Behavior Prediction Tool written by John Lok and published by . This book was released on 2022-06-27 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: I write this book aim to let readers to judge whether it is possible to predict future travel behaviour from past travel behaviour for travel agents benefits as well as big data gathering technology can be applied to predict travel consumption behavior if travel agents can gather any past travel consumer data to predict future travel consumption behavior from AI ( big data gathering tool). This book is suitable to any readers who have interest to predict any individual or family or friend groups of travel target's psychological mind to design the different suitable travel packages to satisfy their needs from big data gathering tool prediction method in possible. This book researches how to apply big data gathering tool to predict future travel consumer behavior from past travel consumer data. This book first part aims to explain why and how future artificial intelligent technology ( big data gathering method) can be applied to assist businesses to predict why and when and how consumer behavior changes in entertainment industry, e.g. cruise travel and vehicle leisure activities. If AI, big data gathering tool can be applied to predict such as leisure market consumption behavior, it is possible that future big data gathering tool can be used to gather past travel consumer behavioral data in order to conclude more accurate information to predict future travel behavioral need changes.

Download or read book Artificial Intelligence Predicts Consumer Behavioral Tool Business Journey written by Johnny Ch lok and published by Createspace Independent Publishing Platform. This book was released on 2018-06-18 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 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.

Download or read book Artificial Intelligence in Healthcare written by Adam Bohr and published by Academic Press. This book was released on 2020-06-21 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

Download or read book Artificial Intelligent Predicts Market Behaviors written by Johnny Ch Lok and published by . This book was released on 2020-01-27 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: Challenges of artificial intelligence, algorithms technology and machine learning impact to consumption marketMarkets have played a key role in providing individuals and businesses with the opportunity to gain from trade. If (AI) big data gather tool can predict how to change potential customer behavior in success. The challenges to consumers will face that the overall market consumption model will be dominated by the businessmen only. So, it is not fair or reasonable to consumers, because (AI) big data gather tool has controlled or dominated all consumers' minds and it has predicted how and why every kind of product or service consumer shopping model or consumption behaviors how will change.It will bring this questions: How can market designers learn the characteristics necessary to set optimal, or at least better, reserve prices after they had gather all data to conclude the analytical results of their consumers behaviors how will change? How can market designers better learn the environments of their markets?In response to these challenges, artificial intelligence (AI ) and machine learning are important tools for market design. For example, retailers and marketplaces, such as eBay, Amazon and many others are mining their vast amounts of data to identity patterns that help them create better shopping experiences for their clients and increase the efficiency of their markets. By having better prediction tools, these and their companies can predict and better manage dynamic consumption market environments. The improved forecasting that (AI) and machine learning algorithms provide help marketplaces and retailers better anticipate consumer demand and producer supply as well as help target products and activities for segmented markets. Another important application of (AI) 's strength in improving forecasting to help markets operate more efficiently is in electricity market example. To operate efficiently, electricity marker makers can attempt to apply (AI) machine learning tool to follow every household family electricity consumers' past electricity consumption record to judge ( predict) how it will be every family's forecasting in the year.

Download or read book Artificial Intelligence Predicts Market Behaviors written by Johnny Ch Lok and published by . This book was released on 2020-01-27 with total page 168 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.

Download or read book Artificial Intelligence Big Data Travelling Consumption Prediction written by Johnny Ch Lok and published by Createspace Independent Publishing Platform. This book was released on 2018-06-11 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: In my this book, I concentrate on explain why artificial intelligence (AI) big data gathering tool will be one kind of good traveler consumer behavioral prediction tool to be chose to apply to predict traveler consumer consumption behavior concerns when and why and how their travelling behavior will change. I shall indicate some cases examples to give reasonable evidences to analyze whether (AI) big data gathering tool will be one kind suitable tool to be applied to predict when and how and why travelling consumer behavioral changes. If (AI) big data can be one kind tool to attempt to be applied to predict when and how and why travelling consumer behavioral changes. Will it make more accurate to compare other kinds of methods to predict travelling consumer behaviors, e.g. survey, telephone questionnaire? Does it have weaknesses to be applied to predict travelling consumer behaviors, instead of strengths? Can it be applied to predict travelling consumer behaviors depending on any situations or only some situations? Finally, I believe that any readers can find answers to answer above these questions in this book.

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 2018-10-26 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: I write this book aim to explain how and why whether artificial intelligence ( big data gathering tool) is better method to compare economic or statistics or psychological methods to predict consumer behavior. If future artificial intelligent technology can be developed to apply to predict consumer behavior, what requirements does it need to achieve consumer psychological prediction function? 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.

Download or read book Artificial Intelligence Data Gathering Information Technology written by Johnny Ch Lok and published by Independently Published. This book was released on 2019-01-20 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: Part IIAI predicts customer emotionChapter One(AI) tool predicts consumer immediate and expected emotion how to influence consumption decision If (AI) tool can be confirmed to apply to predict consumer behavior, then I can conclude that it can be attempted to apply to predict what the factor(s) of the product itself can cause the consumer has positive or negative emotion, so the manufacturer can attempt to avoid the bad factors cause to bring negative emotion to influence the consumer chooses not to buy the product more easily, such as vehicle product case. Economists refer to the consumption desirability is as " utility" and the product or service consumption decision making is aroseinfluenced by maximizing utility only. However, they neglect consumer individual immediate emotion change will also influence the consumer individual consumption decision consequently. Expected emotions are those that are anticipated to occur as a result of the outcomes associatedwith different possible courses of action. For example, if a potential investor, were deciding whether to purchase a stock, who might imagine the disappointment who would feel if who ought it and it reduced its price. Otherwise, whose emotion would experience, such as regret if it increased in price, but who does not buy it before the stock rise its price. However, I believe nowadays technology, in the future one day, (AI) tool can be attempted to assist consumer psychology profession or marketing research profession to assist them to find what are the bad factors to influence consumers choose not to buy any manufacturers' products. Then, when the manufacturercan discover what are the bad factor(S) cause(S) consumers who do not choose to buy their products, then the manufacturer can raise whose product of consumption desirability or " utility" to raise whose product's consumption decision making is influenced by maximizing utility. Hence, (AI) tool will be possible to find what the bad factor(S) to cause consumers do not choose to buy the manufacturer's product in order to raise the product's utility to bring consumer positive emotion to choose to buy its product in possible. SO, (AI) tool will be one consumer psychological emotion prediction tool to assist any manufacturersto help their products to build positive emotion to any consumers in possible.

Download or read book Intelligent Data Analytics for Terror Threat Prediction written by Subhendu Kumar Pani and published by John Wiley & Sons. This book was released on 2021-01-12 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent data analytics for terror threat prediction is an emerging field of research at the intersection of information science and computer science, bringing with it a new era of tremendous opportunities and challenges due to plenty of easily available criminal data for further analysis. This book provides innovative insights that will help obtain interventions to undertake emerging dynamic scenarios of criminal activities. Furthermore, it presents emerging issues, challenges and management strategies in public safety and crime control development across various domains. The book will play a vital role in improvising human life to a great extent. Researchers and practitioners working in the fields of data mining, machine learning and artificial intelligence will greatly benefit from this book, which will be a good addition to the state-of-the-art approaches collected for intelligent data analytics. It will also be very beneficial for those who are new to the field and need to quickly become acquainted with the best performing methods. With this book they will be able to compare different approaches and carry forward their research in the most important areas of this field, which has a direct impact on the betterment of human life by maintaining the security of our society. No other book is currently on the market which provides such a good collection of state-of-the-art methods for intelligent data analytics-based models for terror threat prediction, as intelligent data analytics is a newly emerging field and research in data mining and machine learning is still in the early stage of development.

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 2019-01-06 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the future, big data can use data from text to picture, sounds, movies, music satellite coordinates or any other type of input or output data that type of input or output data that came from different influential aspect. It is cloud solutions, bring big data will be for predict insight driven by business strategy, new product strategies and new consumer relationship, predictive consumer behavioral strategy. Using the right data in the right business decision will mean smart decisions, new opportunities and utimately a big competitive advantage. Hence (AI) big data gathering tool is different is that (AI) can be one depth in-memory database function, it can make real-time data analytics that provide meaningful information in short time, it is also the visualization tool, such as SAP Lumira, allow this exploration and understanding of the data, and ultimately supports the decision making process. All above these features, which will be human's data gathering effort who won't exceed (AI) big data gathering effort. Hence, future (AI)big data gathering will be the best choice to assist businesses to predict consumer behaviors successfully.

Download or read book Artificial Intelligent Travelling Behavioral Predictive Tool written by Johnny Ch Lok and published by . This book was released on 2019-06-02 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: So, I believe that (AI) big data gather every conclusion or result will be different, due to consumer's price and quality demand will often change to every kind of product or service supply in retail industry. So, how to shape (AI) big data gathering's analytical conclusion or result more clear. I shall recommend organizations need to build great understanding of and a stronger connection to increasingly empowered consumers before they plan and implement how to apply (AI) big data gather tool to predict consumer behavior as below: Firstly, (AI) is empowered by technology, the consumer is redefining value. The traditional measures of cost, choice and convenience are still relevant, but not control and experience are also important. Globally, consumers have access to more than 2 billion different products choice by a wide range of traditional competitors and dynamic new entrants, all experimenting with new business models and methods of client engagement. As choice increases, loyalty becomes more difficult familiarity and the consumer becomes more empowered. Businesses will have no choice and constantly innovate and disrupt themselves by meeting new technologies of high standards and expectations of consumers. So, (AI) data gather tool will need to follow different target group of consumers' needs to follow their different kinds of product design or style choice preferable to gather data in order to conclude the different target groups of consumer behavior to give opinion more clear and accurate to let businessmen to understand more clear how its customers' behavioral choice trend in the future half month, even to two years period.Secondly, businessmen need to adopt changing technologies rapidly. Technology will be the key driver of this retail industry. Industry participants will only success if they have a clear prediction to focus on how to using technology to increase the value added to consumers. They must, however, do so will I realistic assessment of their costs and benefits. Hence, (AI) big data gather technological tools will need to design to help them to gather data efficiently by these ways, such as the internet of things ( IOT), artificial intelligence (AI) machine learning, augmented reality (AR)/virtual reality (VR), digital traceability. So, future (AI) big data gather tool are predicted to be most influential customer behavioral positive emotion changing tool for retail, due to their widespread applications, ability to drive efficiencies and impact on labor in order to impact consumer behavior changing effort from negative emotion to positive.Thirdly, (AI) big data gather tool is an advanced data science of consumer behavior predictive tool. Businesses will have to bring the journey from simply collecting consumer data to using it to scale and systematize enhanced decision making across the entire value chain. When focused on their business goals, industry players should not lose sight of the impact that future capabilities and transformative business models may have on society.However, (AI) big data gather tool will encounter these challenges when any business plans and implements to apply it to predict consumer behavior in retail industry. The challenges include that as below:1.The high cost and difficulty of implementing new technologies . The (AI) big data gather tool needs capital and capabilities to be designed to implement to be applied to different retail industry users. so, expensive barriers to innovation, an organization and the skillsets of its people to support a new design of (AI) big data gather tool, highly digital technology may be required.

Download or read book Artificial Intelligence Big Data Gathering Predicts Consumer Behavior written by Johnny Ch LOK and published by Independently Published. This book was released on 2018-09-19 with total page 488 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 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 Intelligent Data Analysis written by Deepak Gupta and published by John Wiley & Sons. This book was released on 2020-07-13 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on methods and tools for intelligent data analysis, aimed at narrowing the increasing gap between data gathering and data comprehension, and emphasis will also be given to solving of problems which result from automated data collection, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring, and so on. This book aims to describe the different approaches of Intelligent Data Analysis from a practical point of view: solving common life problems with data analysis tools.

Download or read book Artificial Intelligence Big Data Travelling written by Johnny Ch LOK and published by . This book was released on 2018-06-17 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book indicates whether human technological AI (big data gathering tool) which can be applied to predict when, how and why consumer behavior will change. Does it is science story or actual fact to be applied in our future business society. Parent can learn their children to make judgement whether our future society will be either assistance by AI technological development absolutely or AI is only science story product. This book has these two research questions need to be answered?(1) Can apply (AI) learning machine predict travelling consumer behavior?(2) Can (AI) big data gathering learning machine be replaced to human travelling marketing research method, e.g. survey or traveler psychological and travelling marketing research or travelling environment micro and macro economic human judgement of traveler consumption behavior prediction methods to predict travelling consumer behaviors more accurate? Nowadays, many airline firms or travelling agents hope to apply different methods to predict travelling consumer behaviors in order to know what will be future next month, even next year travelling market destination choice and travelling package design preferable choice activities and travelling consumers travelling packages or travelling destination taste changes to help them to choose to implement what kinds of travelling marketing strategies or what are travelling packages or airline ticket prices more reasonable or more accurate range price level to attract travelers choose to the airline or travel agent to buy paper or e- ticket or help them to arrange travel package more attractive. Hence, if the travel agent or airline can apply the most suitable travelling consumer behavioral prediction method to predict how and the reasons why future travelling consumers' choice will be changed to influence their frequent travelling destination or travelling package choice. It will have more beneficial intangible advantages to compare the non-predictive travelling consumer behavioral variable changes travel agents or airlines, e.g. what will be the hot travel entertainment destinations and tangible advantages, what are the most suitable airline and hotel reasonable price range level to attract many travelers to choose to find the airline or travel agent to help them to buy air ticket or they ought know how to design their arrange travel package which will be accepted more popular for next or next year travelling customer's hot needs .Otherwise, if they applied the inaccurate traveler consumer behavioral prediction market research methods, e.g. survey, telephone questionnaire to predict how their consumers' behavioral changes. It will waste their time and money to attempt to make wrong travelling hot destinations and travelling package design to make unattractive travelling market strategy to cause travelling customer number to be reduced. In my this book, I concentrate on explain why artificial intelligence (AI) big data gathering tool will be one kind of good traveler consumer behavioral prediction tool to be chose to apply to predict traveler consumer consumption behavior concerns when and why and how their travelling behavior will change. I shall indicate some cases examples to give reasonable evidences to analyze whether (AI) big data gathering tool will be one kind suitable tool to be applied to predict when and how and why travelling consumer behavioral changes. If (AI) big data can be one kind tool to attempt to be applied to predict when and how and why travelling consumer behavioral changes. Will it make more accurate to compare other kinds of methods to predict travelling consumer behaviors, e.g. survey, telephone questionnaire? Does it have weaknesses to be applied to predict travelling consumer behaviors, instead of strengths?

Download or read book Artificial Intelligence Predicts Manufacturer Behaviors written by Johnny Ch LOK and published by . This book was released on 2019-01-02 with total page 555 pages. Available in PDF, EPUB and Kindle. Book excerpt: 5.(AI) and machine learning technologies make it possible to capture, process, and inter data on a massive scale effectively , then any human being could ever do. For example, Criteo's creative technology " Kinetic design" can apply insights from 1.2 billion monthly impressions to select and optimize individual branded advertisements components according to each shopper's preference and intent. This ensures more personalization and visually inspiring on brand ads. resulting in up to 12% more sales for (AI) technology advertiser clients.Moreover, advertisers can now engage and inspire shoppers on a more personal level, rendering custom ads. it real-time for every impression. So, designer continues to learn from each design's success to makeads. more and more effective over time. Furthermore, brands are increasingly using paid search on retail sites to draw attention to their products on the crowded online shelf, e.g. Google shopping is a key growth area's more users are engaging with shopping ads. and across the globe. Google shopping has become essential to retailers' marketing strategies, but is a difficult channel to apply its tool to be promoted effectively . Thus, future (AI) and machine -learning technologies can dramatically improve digital commerce performance application to apply (AI) and machine learning to digital consumer. So, future (AI) technology can be applied to digital commerce aspect, it will fall into the categories of pattern recognition, classification, prediction and consumer behavior.In conclusion, the benefits of using (AI) in digital commerce include: improved efficiency in discovering the relationships between datasets over traditional methods, which require complex modeling and coding, improved accuracy for clearly defined processes that involve a lot of manual processing, ability to deal with a large emotion of data with many attributes, for example: customer behavior data, multichannel and multi-device data , complex product data and fraud detection, more accurate analysis, such as customer segmentation sentiment, analysis and personalization frequent algorithum refreshes, such as several times a day, to capture the changes in customer and market behavior. Finally, however, a lot of types predictive consumption behavior around (AI), in particulars that driven by vendors claiming their solutions are (AI) , ready and can deliver dramatic improvements over existing technologies. Application leaders for digital commerce can be misled into believing that (AI) can solve all their problems, which is not true for n in-depth discussion of the (AI) consumers and market behavioral predictive tool and machine -learning technologies bot. Thus, (AI) prediction consumer behavioral technology can give beneficial quantitative analysis for forecasting in business and market especially in consumer behavior and in the consumer decision-making process ( consumer choice model) more effectively and efficiently.ChaptersevenIs 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.