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Artificial Intelligence Customer Psychological Predictive Method: Appies to Marketing Information Gathering

Artificial Intelligence Customer Psychological Predictive Method: Appies to Marketing Information Gathering
Author: Johnny Ch Lok
Publisher: Independently Published
Total Pages: 254
Release: 2019-01-20
Genre: Business & Economics
ISBN: 9781794466005
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2.2How can apply (AI) digital channel to predict consumer behaviors?(AI) digital channel can be applied to help businesses to evaluate whether how much the product price is the most attractive to persuade consumers feel it is the most reasonable price to sell. It helps consumers to feel which brands of products which ought change the price to let consumers to choose to buy the brand of product. It can be applied to predict whether how many consumer numbers can be increased or decreased when the brand of product's price is variable. It aims to give opinions to help any brand of product manufacturers or sellers to judge whether which price is the most reasonable to let consumers to accept to choose to buy the brand of product in popular.Thus, (AI) price measurement technology can be preference to be applied online communication ecommerce and mobile phone internet platform aspect. As businesses can enter their past products prices data and past customer number data into computer or mobile. Then, (AI) price measurement technology can gather these data to analyze these product prices and past customer number to compare their prices variable changing range level to find their price variable difference to measure to make conclusion about every product's price variable changing will influence how many customer number increase or decrease changing to choose to sell their different kinds of products more accurate. Then, (AI) price measurement software will help them to analyze all past price variable changing data to compare whether which price range can let customers to feel it is more reasonable and attractive to influence them to choose to buy the product among different brands of product choice.Because any product's price is one important factor to influence consumers to choose to buy the product, instead of quality, durability, shape, appearance, color, brand familiarity etc. factors. Any online businesses with a focus on Asia should considerate (AI) customer care, and virtual shopping experience, whereas is Europe and North America still value face-to-face and/or real human interaction over (AI) or virtual worlds.

What Are Marketing Information and Artificial Intelligence Customer Psychological Predictive

What Are Marketing Information and Artificial Intelligence Customer Psychological Predictive
Author: Johnny Ch Lok
Publisher: Independently Published
Total Pages: 254
Release: 2019-01-04
Genre:
ISBN: 9781793171849
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(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.

Artificial Intelligence Customer Psychological Predictive

Artificial Intelligence Customer Psychological Predictive
Author: Johnny Ch LOK
Publisher:
Total Pages: 253
Release: 2019-04-07
Genre:
ISBN: 9781093115413
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The challenges of (AI) big data gather shapingthe future of retail for consumer industriesAnother challenge of (AI) big data gather is that how to shape the consumer behavior to let business owner to feel or know or 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.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.

Marketing Information Prediction and Artificial Intelligence Customer Psychological Prediction

Marketing Information Prediction and Artificial Intelligence Customer Psychological Prediction
Author: Johnny Ch Lok
Publisher: Independently Published
Total Pages: 254
Release: 2019-01-03
Genre:
ISBN: 9781793110862
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ChapterSixIs Artificial Intelligent the most effective andaccurate consumer behavioral tool?Is (AI) the best and the most effective and accurate consumer behavioral prediction tool to compare other kinds of consumer behavioral prediction tools? Nowadays, retailing competitions are serious businessmen often find different kinds of methods to attempt to predict consumer changes. The consumer behavioral predictive methods can include as these below methods, instead of (AI) big data gathering tool.Firstly, statistics is the popular mathematic method, it applies auto-regression, liner regression, structural equation modelling, logistic regression statistic techniques to be used to predict consumer behaviors. Secondly, it is classification method, it sis a support vector machine to assist businessmen to make consumer behavioral prediction, it also includes decision making tress diagram technique. Thirdly, it is rule mining method, it is algorithm, market base analytic etc. business marketing concept analytical tool, it also includes graph mining technique tool. Next, it is psychological prediction model tool, it is psychology prediction model too, it is a kind of psychological method to predict consumer behaviors. Finally, it is the most updated and potential artificial neural network (ANN) machine tool, it gathered big data, then it will carry on analyzing and applies psychological method to conclude the most accurate and reasonable solutions to give recommendation to businesses to predict when and how and why their consumer behaviors will change. So, it is one owned human mind's machine and owned psychological and analytical efforts to replace humans to make any judgement in order to make the most accurate predictive behavioral changes for consumers, instead of the traditional marketing concept and psychological and mathematic methods to predict consumer behavior, (AI) big data gathering tool will be another new tool.What are the advantages of (AI) tool to be used to predict consumer behaviors as well as what are the different between it and other traditional consumer behavioral predictive tools? I shall explain as below: Firstly, as above all case studies are explained to (AI) questionnaire design method benefit, I believe (AI) big data gathering tool can be applied to help human to analyze and design any the suitable valid questions to enquire any kinds of business consumers in order to gather the most meaning and useful opinions to conclude the most accurate consumer behavioral prediction for every questionnaire. So, future (AI)'s analytical effort and decision making effort most be exceed above human's judgement efforts. So, future (AI) can help human to design the most useful and meaning different kinds of valid questionnaire ( survey) questions as well as assist humans to analyze and make accurate decision making and conclusions to give opinions to help businessmen to predict when consumer behaviors will change and how their consumption behaviors will change to influence their businesses in order to help them to make any efficient and effective and accurate solutions to avoid consumer number to be decreased and the most important benefit is that it can give opinions to help businessmen to explain why ( what the factors ) cause their consumer behaviors change suddenly. It will be human's efforts can not achieve to exceed (AI)'s efforts in the future.Secondly, (AI) can make artificial machine judgement and analytical effort, without human misleading or unfair or unreasonable judgement. So, it can make more fair and reasonable and accurate conclusion to give opinions to predict when, how and why consumer behaviors will change suddenly to the kind of business in customer model building process and evaluating the results of customer relationship management -related investment more accurate.

Marketing Information and Artificial Intelligence Customer Psychological Predictive Methods

Marketing Information and Artificial Intelligence Customer Psychological Predictive Methods
Author: Johnny Ch Lok
Publisher: Independently Published
Total Pages: 254
Release: 2019-01-12
Genre:
ISBN: 9781793961334
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Chapter Three(AI) tool judges the difference between utility factor and emotionto influence consumer decision making In economic utility or immediate (expected) emotion aspects, whether which is more influential to excite consumption. To analyze whether it is economic utility or immediate ( expected) emotion more influential to excite consumption. It depends on the consumer individual consumption choice is in which situations. For example, if the industry's general consumer individual consumption decision is concentrate on emotion influential aspect, such as cruise entertainment industry, hospital care service industry, theme park entertainment industry, movie watching entertainment industry etc. Above all these industries have same nature, it is service. So, it seems that service industry's main influential factor is immediate ( expected) emotion influence, it is not economic utility influence. Otherwise, product sale industry's main influential factor is utility. 3.1(AI) judges consumer utility factorFor this toy choice situation example, parent choose to buy one toy to give whose child to play. They usually considerate which kind of toy is attractive to their child whom like to play. In many different kinds of toys choice, if the child likes to choose the kind of toy to play. After the child's parents had purchased the kind of toy to let whose child to play one period time, e.g. six month. Then, when the child feel that who has need to buy another new toy to play, due to he/she feels bored to play this toy. So, it seems that the child feels this toy has less utility or it's utility is decreased. So, he/she expects whose parent can buy another new kind of toy to let whom to play. It also implies that it is not emotion factor to influence the child to feel boredom and unfunny to play this kind of old toy after six months. It is the product's utility factor which can not attract the child to play it any more. So, this old toy's utility is decreased when this child spends six months to play it. This toy's value is only six month utility to this child to play. Otherwise, if this kind of toy is bought by another parent. It is possible that the another child like to play this kind of toy one year or more. So, it's utility to another child is one year or more period. So, product's utility period is difference, it depends on how long time of the user's satisfactory time.

Artificial Intelligence Customer Psychological Predictive Tool

Artificial Intelligence Customer Psychological Predictive Tool
Author: Johnny Ch Lok
Publisher:
Total Pages: 254
Release: 2020-04-27
Genre:
ISBN:
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Can artificial intelligence be better to compare economists to judge books prices whether what level is the most influential price to raise readers purchase decision ?However, some economists also demonstrated that given a free market economy, such as in free publish industry, the factors of production ( land, labor and capital) were important in understanding the economic system. Can apply the factor of production, e.g. publishing book sale location ( land); publishing book salespeople sale experience ( labor); and attractive book printing quality (capital printing expense) to influence the publishing industry reading consumer reading habit or purchase book activities?However, some economists suggested two important contributions: Analysis of monopoly and price discrimination and the market for labor will influence consumer number. Such as publishing case: Can analysis of which famous royalty publishing book sale firm to the most monopoly and then following its different topic of books sale price to evaluate whether how much every different topic of its similar book topic sale price to be higher to avoid reduce reader numbers, due to the not famous royalty book seller which similar topic book to the famous royalty book seller's prices are too higher than the famous royalty publishers' book prices? Book salespeople individual sale experience and sale ability and book knowledge ( labor supply) influence the book publishing shop's reading clients buying decisions, such as the more experience book sellers can persuade many readers to buy the book store's books. Otherwise, the less sale experience book sellers can not persuade many readers to buy the store's books.As the found in the field of economics, it became more refined, scholars began investigate many different economic concepts and principles to predict consumers behaviors, such as media reading customer. Nowadays, the media industries provides all of the elements required for studying the economic process. Content providers can offer information and entertainment, education etc. different topic books, magazine reading products which became the media publishing suppliers. Whereas, reading consumers and media advertisers formed the demand side of the media market.

Artificial Intelligence in Behavioral and Mental Health Care

Artificial Intelligence in Behavioral and Mental Health Care
Author: David D. Luxton
Publisher: Academic Press
Total Pages: 309
Release: 2015-09-10
Genre: Psychology
ISBN: 0128007923
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Artificial Intelligence in Behavioral and Mental Health Care summarizes recent advances in artificial intelligence as it applies to mental health clinical practice. Each chapter provides a technical description of the advance, review of application in clinical practice, and empirical data on clinical efficacy. In addition, each chapter includes a discussion of practical issues in clinical settings, ethical considerations, and limitations of use. The book encompasses AI based advances in decision-making, in assessment and treatment, in providing education to clients, robot assisted task completion, and the use of AI for research and data gathering. This book will be of use to mental health practitioners interested in learning about, or incorporating AI advances into their practice and for researchers interested in a comprehensive review of these advances in one source. Summarizes AI advances for use in mental health practice Includes advances in AI based decision-making and consultation Describes AI applications for assessment and treatment Details AI advances in robots for clinical settings Provides empirical data on clinical efficacy Explores practical issues of use in clinical settings

Marketing Information and Artificial Intelligence Customer Psychological Predictive

Marketing Information and Artificial Intelligence Customer Psychological Predictive
Author: Johnny Ch Lok
Publisher: Independently Published
Total Pages: 254
Release: 2019-01-29
Genre: Business & Economics
ISBN: 9781795404198
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Chapter TwoWhat is (AI) deep learning techniques to forecast environment behavioral consumptionThe (AI) deep-learning technology leads to performance enhancement and generalization of artificial intelligent technology. It influences the global leader in the field of information technology has declared its intention to utilize the deep-learning technology to solve environmental problems, such as climate change. So, it will help agriculture farming businesses can raise any plant food: vegetable, fruit, rice which grow up very easily if farmers can apply (AI) deep-learning technology to solve environment problems to influence their plant food grow. If the whole year seasonal change is very good and it is suitable for any plant food to grow in farming land easily, e.g. rain is enough and soil is enough for any plant food to grow in the farm lands. Then, fruit, rice, vegetable etc. agriculture businesses will have much beneficial attribution to global farmers. The question is how to use deep-learning technologies in the environmental field to predict the status of pro-environmental consumption. We predicted the pro-environmental consumption index based on Google search query data, using a recurrent neural network ( RNN model). To certify the accuracy of the index, we compared the prediction accuracy of the RNN model with that of the ordinary least square and artificial necessary network models. For example, the RNN model predicts the pro-environmental consumption index better than any other model. we expect the RNN model to perform still better in a big data environment because the deep-learning technologies would be increasingly as the volume of data grows. So, deep-learning technologies could be useful in environmental forecasting to prevent damage caused by climate change to influence any rice, vegetable, tomato, potato, fruit etc. different plant food grow in any countries' farming land easily.For South Korea example, over 800 government agencies spent 2.2 trillion Korea won on eco-products in 2014 year. However, green products are rarely purchased outside these agencies. This phenomenon occurs because there is a gap between consumer attitudes and behavior, that is environmental attitude is a major factor in decision making vis-a-vis the consumption of " green" food and services ( Jorea Ministry of Environment, 2015). Therefore, it is necessary to understand those consumer attitude, that will lead to sustainability-conductive behavior and consumption.2.1Environmental consumption predictionRecently, many researchers have studied pro-environmental consumption and household indexes as well as suicide rate predictions using messages posted by internet users on Google trend, Tweets etc. channel. Whether can environmental consumption be predicted by (AI) deep-learning technological internet channel? How can impact the pro-environmental consumption attitudes of green policies? Korea scientists estimated pro-environmental attitudes using search query data provided by Google trend and confirmed through regression analysis, that pro-environmental attitude has a positive correlation with the pro-environmental attitude index. They also explained that environment-friendly attitude of residents plan an important role in policy making. In the past, most household consumption indexed were calculated through surveys, but (AI) deep-learning technological tool " big data" have recently gained research attention ( Lee et al. 2016).It seems that (AI) deep-learning technology can help agricultural export countries' farmers, e.g. US, UK, Canada, New Zealand, Australia, Japan, China, India etc. they can predict environmental behavioral consumption to any rice, tomato, potato, fruit, vegetable etc. plant food consumers. The beneficial advantages to them include as below:

Marketing Information Prediction and Artificial Intelligence Customer Psychological Prediction

Marketing Information Prediction and Artificial Intelligence Customer Psychological Prediction
Author: Johnny Ch Lok
Publisher: Independently Published
Total Pages: 254
Release: 2019-01-06
Genre:
ISBN: 9781793285034
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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.

Predicting Personality

Predicting Personality
Author: Drew D'Agostino
Publisher: John Wiley & Sons
Total Pages: 336
Release: 2019-11-19
Genre: Business & Economics
ISBN: 1119630991
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The ultimate playbook for using artificial intelligence to communicate effectively, build teams, and win customers Not long ago, we imagined a hyper-connected world full of trust and openness—a world where effortless communication would bring about a new understanding between people everywhere. Judging from our current environment, this vision of the future may have been overly optimistic. With infinite channels and countless voices flooding them with messages, most people have become highly skeptical and guarded by necessity. As a result, communication is much harder than ever before. Despite the unprecedented connectivity enabled by modern technology, we are far less likely to trust and to invest the time needed to build strong relationships. How can we use technology to reverse this trend? A groundbreaking new branch of artificial intelligence—Personality AI—may be the answer. Combining traditional machine learning, data analytics, and behavioral psychology, Personality AI helps professional communicators tear down walls, establish trust with their audiences, and utilize data to build meaningful relationships, strengthen empathy, and win more customers. Predicting Personality is a practical, real-world playbook for any individual or business whose success hinges on the ability to communicate effectively and build teams. Authors Drew D’Agostino and Greg Skloot—CEO and President, respectively, of Crystal, the app that tells you anyone's personality—show you how businesses can leverage Personality AI and machine learning to grow faster and communicate more effectively than was previously possible. This reader-friendly guide teaches you what Personality AI is, how it works, and demonstrates its practical applications in both life and business. This book: ● Explains how to understand personality types in various contexts, including sales, recruiting, coaching ● Provides guidelines for using personality data to learn and execute ● Explores ethics and compliance considerations surrounding the use of Personality AI ● Offers valuable insights from a leader in the business applications of Personality AI Predicting Personality: Using AI to Understand People and Win More Business is a must-have guide for C-suite executives, sales and marketing professionals, coaches, recruiters, and business owners.