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Book Why Is Big Data Gathering the Best Method to Predict Consumer Behavior

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.

Book Is Big Data Gathering Tool the Best Method to Predict

Download or read book Is Big Data Gathering Tool the Best Method to Predict written by Johnny Ch LOK and published by . This book was released on 2018-10-26 with total page 573 pages. Available in PDF, EPUB and Kindle. Book excerpt: The factor of student demand for alternative modes of course delivery by (AI) marketing research survey method?The factor of student demand for alternative modes of course delivery is another factor to influence the student who chooses the university to study. Any university's educational program includes program design, material production ( both print and e-version), promotion, essay competition, school networks, budgeting, coordinating with various constructors, data base management and program evaluation etc.Nowadays, university teaching methods may include face-to face, online and hybrid modes of course delivery. However, the several ways to students to deliver their course works ,such as full time, part time, internal/ non campus, external studies/distance education, summer school, winter school, semester study and trimester study. The multi site of a university , e.g. major provider of distance online education operates popular affordable learning for student to use internet to study. Although, students do not need to attend to university classroom to listen lecturer's teaching, but it can reduce face-to-face contact between lecturers and students in university classroom often. Although, it is a technological and innovative and effective learning modalities. In fact, such new technological teaching modalities may be necessitated to the graduated or master degree or doctoral degree students. But, I feel the online teaching method is not suitable to the bachelor degree students. As the delivery of course content or the commoditization of knowledge must be re-thought to the bachelor's if the student can't enquire whose lecturer any questions to give feedback by face-to-face. Then, who will concern the course to feel more difficult possibly if who can't listen whose lecturer's opinion to solve whose challenges about the course any questions immediately in classroom often.The second attractive factor of student demand for alternative modes of course delivery is another factor to influence the student who chooses the university to study. Nowadays, university teaching method include face to face, online and hybrid modes of course delivery. However, the several ways to students to deliver their coursework, such as full time, part time, internal/on campus, external studies/distance education, "summer school, winter school, semester study and trimester study."

Book Big Data Gathering Predicts Retail Industry Consumer Behavior

Download or read book Big Data Gathering Predicts Retail Industry Consumer Behavior written by Johnny Ch Lok and published by Independently Published. This book was released on 2018-09-28 with total page 770 pages. Available in PDF, EPUB and Kindle. Book excerpt: Prepare 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 in retail industry. 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 in retail industry? (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 in retail industry? 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.

Book Learning Big Data Gathering to Predict Retail and Service Industry Consumer Behavior

Download or read book Learning Big Data Gathering to Predict Retail and Service Industry Consumer Behavior written by Johnny Ch LOK and published by . This book was released on 2018-10-05 with total page 691 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book researchs how to apply big dta gathering tool to predict retail and service industry consumer behavior. This book first part 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 in retail industry. 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 in retail industry?(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 in retail industry?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.

Book Big Data in Practice

Download or read book Big Data in Practice written by Bernard Marr and published by John Wiley & Sons. This book was released on 2016-03-22 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: The best-selling author of Big Data is back, this time with a unique and in-depth insight into how specific companies use big data. Big data is on the tip of everyone's tongue. Everyone understands its power and importance, but many fail to grasp the actionable steps and resources required to utilise it effectively. This book fills the knowledge gap by showing how major companies are using big data every day, from an up-close, on-the-ground perspective. From technology, media and retail, to sport teams, government agencies and financial institutions, learn the actual strategies and processes being used to learn about customers, improve manufacturing, spur innovation, improve safety and so much more. Organised for easy dip-in navigation, each chapter follows the same structure to give you the information you need quickly. For each company profiled, learn what data was used, what problem it solved and the processes put it place to make it practical, as well as the technical details, challenges and lessons learned from each unique scenario. Learn how predictive analytics helps Amazon, Target, John Deere and Apple understand their customers Discover how big data is behind the success of Walmart, LinkedIn, Microsoft and more Learn how big data is changing medicine, law enforcement, hospitality, fashion, science and banking Develop your own big data strategy by accessing additional reading materials at the end of each chapter

Book Artificial Intelligence Big Data Gathering Predicts Consumer Behavior

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.

Book Learning Big Data Gathering to Predict Travel Industry Consumer Behavior

Download or read book Learning Big Data Gathering to Predict Travel Industry Consumer Behavior written by Johnny Ch Lok and published by Independently Published. This book was released on 2018-10-04 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: PrepareI 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 individal 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 researchs how to apply big dta 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 assit 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.This book has these two research questions need to be answered?(1)Can apply (AI) learning machine predict future travelling consumer behaviors from past travelling consumer behavioral data gathering?(2)Can (AI) learning machine replace human marketing research method, e.g. survey or human psychological and micro and macro economic methods to predict future travelling consumer behavioral need changes more accurate in travelling industry?This book second part aims to explain why and how future artificial intelligent technology ( big data gathering method) can be applied to predict why and when and how travelling consumer behavioral need changes in travelling industry. 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 in travel industryNowadays, many businessmen or marketing research professional hope to apply different methods to predict travelling consumer behavioral needs in order to know what will be future travelling market activities changes to help them to choose to implement what kinds of travelling service 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 travelling consumer needs changes to influence whose travelling behavioral consumption for every travels season changes.Hence, if the travelling service providers can apply the most suitable travelling consumer service needs prediction method to predict how travelling consumers' different kinds of travelling package design needs will be changed to attract their travel journey entertainment or journey public transportation service or catching air plan etc. different kinds of travelling service choice easily.

Book Big Data Gathering Predicts Sevice Industry Consumption Behavior

Download or read book Big Data Gathering Predicts Sevice Industry Consumption Behavior written by Johnny Ch LOK and published by . This book was released on 2018-11 with total page 622 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 in service industry. 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 in srvice industry. 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 to predict what service requirements can be satisfied to their potential service consumers' needs.This book has these two research questions need to be answered?(1)Can apply (AI) learning machine predict what and how consumers service to satisfy their needs ?(2)Can (AI) learning machine replace human marketing research method, e.g. survey or human psychological and micro and macro economic methods to predict consumers service needs more accurate?Nowadays, many businessmen or marketing research professional hope to apply different methods to predict consumer service needs in order to know what will be future market activities and market changes to help them to choose to implement what kinds of service 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 service needs changes to influence whose behavioral consumption to the service providers 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 service providers can apply the most suitable consumer service needs prediction method to predict how consumers' service needs will be changed to attract their entertainment or public transportation service or catching air plan etc. different kinds of service choice easily. It will have more beneficial intangible and tangible advantages to achieve the their service attraction aim to ensure their businesses' future market share to be increased more easier to their countries' choice target service markets. Otherwise, if they applied the inaccurate service needs prediction methods to predict how their service need changes wrongly. Then, it will influence their market shares to be same level, even it will decrease their market shares, when their consumer service needs prediction inaccurately.

Book Artificial Intelligence And Marketing Research Difference To Predict Consumer Behaviors

Download or read book Artificial Intelligence And Marketing Research Difference To Predict Consumer Behaviors written by Johnny Ch Lok and published by . This book was released on 2019-12-22 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: To apply (AI) learning machine technology to understand customer online purchase behavior, it will raise business e-commerce successful chance: For example, (AI) learning machine can help businesses to gather data to analyze to determine whether short-term or long-term signals in the online consumer behavior that indicate higher purchase intents to let every online business to know. (AI) learning machine can find that online users with long-term purchasing intent tend to save and click through on more content.However, as online users approach the time of purchase their activity becomes more topically focused and actions shift from saves to searches from online consumption channel. Then, (AI) learning machine will further find that the brand product purchase signals in online behavior can exist weakness before an online purchase is made and can also be traced across different online purchase categories. Finally, (AI) learning machine synthesize these insights in predictive models of online user purchasing intent to the brand of product. Taken together, it's work identifies a set of general principles and signals that can be used to model online user purchasing intent across many online content discovery applications. Thus, (AI) learning machine can help online businesses to gather any online users' click online behaviors data to judge whether there are how many online users will choose to find their online business websites to make final decisions to buy their products from online channels. Then, it will give opinions to help the online businesses to let it to judge whether what are the important website factors will help its online business to attract many online consumers, e.g. designing unattractive website issue, online unattractive product photos issue, unclear website color issue, unclear website advertisement message, contents and words impressions issue, lacking image movement frequent attractive seeing issue etc. different website factors. Thus, online digital channel will be one good choice to apply (AI) learning machine to help businesses to predict consumer behaviors.Can apply artificial intelligent learning machine " big data" gathering method to predict manufacturers' behavioral performance ?

Book Methods Predict Consumer Behavior

Download or read book Methods Predict Consumer Behavior written by John Lok and published by . This book was released on 2022-03-21 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Artificial Intelligence Big Data Gathering How Impacts Consumer Behavior

Download or read book Artificial Intelligence Big Data Gathering How Impacts Consumer Behavior written by Johnny Ch LOK and published by Independently Published. This book was released on 2018-09-21 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: How to apply online psychological advertising method to predict passenger behavioral consumption?Online advertising can give relevance information to represent the similarity between advertisement and queries. These existing online advertisement works mainly focused on interpreting advertisements clicks in term of what consumers seek. ( i.e. relevance information) and how consumers choose to watch TV or magazine or online advertisement etc. from different promotion media. ( historically to know the product is selling on the market through advertising information). However, few of manufacturers or sellers attempted to understand why consumers chose to watch the advertising from TV or magazine or internet etc. different media.Why can MTR can choose online advertisement to predict passenger behavior? Online Advertisement can be as a commercial search engine for manufacturers or sellers to gather data to concern how behavioral consumption is. The online advertisement's each observations motivate who to systemically model to test what each consumer individual psychological desire in order for a precise prediction on behavioral consumption after online advertisement promotion from internet media.Today, internet is one kind of effective psychological advertising promotion method. For example, an online advertisement system, sponsored search has been one of the most important business models for commercial web search engines. It generates most of the revenue of search engines by presenting to users sponsored search results, i.e. advertisements (ads), along with organic search results. To deliver the most interesting ads to the users, a sponsored search system consists of technical components, including query-to-ads matching, online click prediction for matched ads, online click probability and auction to determine the ranking, placement, and pricing of the remaining ads. To aim to attempt to predict behavioral consumption for any kinds of product sale from online advertisement media.In today's industry, generalized second price auction (GSP) is the most widely-used auction mechanism , in which the price that an advertiser has to pay depends on the predicted online click probability of the online buyers, whose own ads as well as the bid price and predicted online click probability of the ads ranked in the next position. The online sponsored search systems typically employ a machine learning model top predict the probability that an online user clicks an advertising from internet. However, in practical sponsored search system. There are many ads without adequate historical click through data, even after query levels. Then online ads can been click improved prediction accuracy to consumer individual behavioral consumption when each click is occurred to the seller individual website. For example, online ads, such as : free Nike coupons ad. It shows " Go-Get_couptons.com/Nike, Download and print Nike coupons ( 100% Free)" ; another Nike-sales prices ad. It shows www.calibex.com, clothing, latest fashions and styles on sale. Buy Nike Fast!" ; another Perfume.com official site ad. It shows "www.perfume.com, 10,000 + brand name perfumes and colognes-up to 80% off retail!" ; another Luxury English Perfume Ad. It shows " www.florislondon.com, shop online for luxury perfumes for men, women and the home". Above of these are example online ads. For two queries, "Nike" and "Perfume" , and two ads under the same query field similar relevance to the query.

Book Artificial Intelligence and Marketing Consumer Behavioral Prediction

Download or read book Artificial Intelligence and Marketing Consumer Behavioral Prediction written by Johnny Ch Lok and published by . This book was released on 2020-01-17 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Thus, future (AI) big data learning machine can also help consumers to choose the best brand of manufacturer's products among different brands of manufacturers products choice to compare their past sale performance from internet. They can apply (AI) big data statistic method to gather all different manufacturers' similar products past sale data to compare their advantages and disadvantages to make the best decision to choose to buy which brand of product is the most suitable to them to buy to use. It seems (AI) big data can also help consumers to predict any manufacturers' manufacturing behaviors or manufacturing performance whether they are improving their product quality or are deteriorating their product quality. Thus, (AI) big data tool is also important to help customers to predict future the different brands of manufacturer performance will have improvement in possible.

Book What Are Marketing Information and Artificial Intelligence Customer Psychological Predictive

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.

Book Big Data Gathering Can Predict

Download or read book Big Data Gathering Can Predict written by Johnny Ch LOK and published by . This book was released on 2019-01-02 with total page 567 pages. Available in PDF, EPUB and Kindle. Book excerpt: Can advertising influence consumption behavior by (AI) marketing research survey method?Advertising is a subject on which people tend to hold strong and often opposing views, and economists are not expectations to this. Some economists regard advertising as one means by which firms concentrate on promoting whose tastes and opinions in the direction of their products and also more generally in favor of private consumption ( consumer behavior). Other economists see advertising as an efficient way by which firms supply information to potential consumers. Otherwise, some economists see advertising as a barrier inhibiting new entrants into an industry thereby enabling the established firms to reap high profits, when others see advertising as evidence of competition and an aid to new entrants in establishing themselves. So, it seems advertising can influence consumer choices possibly. Advertising relatives to sales varies considerably between industries. For example, the ratio of advertising in 1968 year varied from over 15% in the toilet preparations industry to over 10% in the soap and detergents industry to near is in a number of toilet preparation producer industries. A distinction is frequently made between information an persuasive advertising , and it is often suggested that some forms of advertising ( such as classified ads.) are likely to have more informative content than other forms ( such as television advertising).What is the sale of advertising in the demand function? One response is that a firm can sell more of its products because consumers have more information on that product. The information may relate to its existence, price, quality etc. Thus advertising is seen as essentially supplying information to consumers how to choose the similar kinds of products to decide which is the suitable product to buy. The other response is that advertising seeks to persuade consumers to purchase with favored people or situations, repetition of the same message. This advertising seeks to promote tastes rather than to inform. One firms' advertising may not be successful through false judgement by that firm and its advertisers or because of the impact of the advertising of other firms. The difference between the two responses can be put in terms of the conventional; utility maximization approach top consumer demand theory. The first response regards consumers' taste ( i.e. the utility function) as fixed and advertising informs the consumer about availability, price etc. So, that utility maximizing process can take place more effectively . The second response regards advertising and seeking to promote consumers' tastes and change the consumers' utility function in a manner favorable to the advertiser. So, different types of advertising have been as containing information and persuasion in varying proportions and varying in the degree of desirability. But for the firm, the intention is to sell its products, and it will present any information in a way which seeks to influence the consumer to purchase its products.

Book Big Data Gathering Predicts Retail Industry Consumer Behavior

Download or read book Big Data Gathering Predicts Retail Industry Consumer Behavior written by Johnnny Ch LOK and published by . This book was released on 2018-11 with total page 748 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 in retail industry. 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 in retail industry?(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 in retail industry?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.

Book Artificial Intelligent Data Gathering Tool Predicts Retail and Service Industry

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.

Book How Applying Robots To Improve Consumer Behavior

Download or read book How Applying Robots To Improve Consumer Behavior written by John Lok and published by . This book was released on 2022-07-18 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: