Psychological And Technological Methods Predict Consumer Behaviors

Psychological And Technological Methods Predict Consumer Behaviors
Author: Johnny Ch LOK
Publisher: Independently Published
Total Pages: 55
Release: 2019-04-27
Genre:
ISBN: 9781096055266

The impact of emotions on judge , evaluations and decisions has long been important to psychology and consumer behavior on consumption. It seems face reading technology can predict whether the consumer likes or dislikes these confectionery foods, chocolates, sweets or juice, soft drinks liking ratings to measure whether sugar element is excess or less from young consumers' face expression, such as enjoying or not enjoying of feeling, smile or no smile response. Hence, face measuring technology can be more difficult to detect consumers 'emotion for product manufacturer. Because consumers need to spend more time to attempt to use their new innovative products. *Recommendation Ethnographic consumer behavior research is for video camera recording to product manufacturers at home Otherwise, it seems product manufacturers can't use face reading technology to detect consumers' emotion in the short time immediately. The products include any kind of products, e.g. high technological products, such as space mining of resources machines, satellite navigation system ,cars , machines etc. as well as home useful technological electronic products, such as mobile phones, washing machines, televisions, laptops as well as daily products, such as shirts, shoes, furniture, toys, tooth pastes etc. These essential home product and high technologic product manufacturers who need to continue to innovate their old style products to follow consumers' taste to invent new style products to be accepted to their fresh taste. It seems that manufacturers need to spend a long time to touch consumers' feeling whether whose old style technological products which are still accepted to them to use or not. Hence, it implies that a consumer decides to buy these high technological innovation products, whose choice isn't performed to show who must accept to use these high technological innovation productsfor long time, whose emotion is not sure whether who feels satisfactory to consume to use this product for a long time. When he/she uses this technological product for a long time, it is possible that who will feel it was not valuable to buy it before. Hence, video camera can used to record the consumer's behavior record whose image and to analyze whose facial expressions and bodily gestures at home about one week.

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

Why Is Big Data Gathering the Best Method to Predict Consumer Behavior
Author: Johnny Ch Lok
Publisher: Independently Published
Total Pages: 574
Release: 2018-10-26
Genre:
ISBN: 9781729294741

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.

The Difference Between Artificial Intelligence and Psychological Method Predicts Consumer Behavior

The Difference Between Artificial Intelligence and Psychological Method Predicts Consumer Behavior
Author: Johnny Ch LOK
Publisher:
Total Pages: 173
Release: 2018-09-08
Genre:
ISBN: 9781720160496

Chapter Five Can apply artificial intelligent learning machine " big data" gathering method to predict manufacturers' behavioral performance ? In consumer view point, can they apply (AI) learning machine to predict manufacturers' behavioral performance to judge whether whose products are value to buy. Nowadays, (AI) and big data are reshaping the risk in consumer privacy. For example, consumers want to hide their willingness to pay just as firms want to hide their real marginal cost, and buyers have less favorable information, say a low credit shore, prefer to withhold it just as sellers want to conceal poor product quality. So, it implies that it is possible (AI) learning machine can help customers to gather any manufacturers' past sale performance, e.g. how many complaints or appreciation from clients, product quality etc. sale data to let consumers to make judgement whether it is value to buy to compare other competitors. So, it has risk to the poor product quality of manufacturers. Otherwise, it has benefits to the good product quality of manufacturers. It also implies all manufacturers' privacy is not protected or secret when (AI) learning machine is popular to be used to predict manufacturers' behaviors by consumers. Information economists suggest that both buyers and sells have an incentive to hide or reveal private information, and these incentives are crucial for market efficiency. Data technology that reveals consumers type could facilitate a better match between product and consumer type, and data technology that helps buyers to assess product quality could encourage high quality production. Thus, (AI) big data technology can also assist consumers to gather different manufacturers' data to compare what their advantages and disadvantages of their products are. Then, consumers can make comparison to choose which brand of product is the suitable to whom to buy in these more choice consumption market. (AI) learning machine will gather similar brand their products' data to analyze to make conclusion to let consumers know or feel to make final judge to find what advantages or disadvantages of these sample brands of similar products' comparison from internet. On the other hand, it means that manufacturers can gather consumers' past purchase behaviors or purchase experience from (AI) big data gathering method to record and analyze to give opinions to let manufacturers to know what reasons or factors influence consumers choose not to buy their products from internet. (AI) big data gathering consumer behavior prediction method can give these benefits to manufacturers and consumers both, such as: New concerns arise because (AI) technological advance which have enables reducing cost of collecting, storing, processing and using data in mass quantities extend information beyond a single transaction. These advances are often summarized by the big data, it means charge volume of transaction-level data that could identify individual consumers by itself or in combination with the datasets. The popular (AI) takes big data as in input in order to understand, predict and influence consumer behavior. Modern (AI) is used by legitimate companies, could improve management efficiency motivate innovations and better match demand and supply. But (AI) in the wrong hand, also allows the mass production of fraud and deception. Since , data can be stored, traded and used long after the transaction. Future data use is likely to grow with data processing technology, such as (AI) big data gathering consumer and manufacturer behavioral prediction method from internet channel.

Psychology Methods Predict

Psychology Methods Predict
Author: Johnny Ch Lok
Publisher:
Total Pages: 196
Release: 2021-04-26
Genre:
ISBN:

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

Psychological Methods Predict Education Service and Consumption Behavior

Psychological Methods Predict Education Service and Consumption Behavior
Author: Johnny Ch LOK
Publisher:
Total Pages: 387
Release: 2018-01-11
Genre:
ISBN: 9781976870736

I write this book concerns how to apply psychological methods to solve education service to student psychological need challenges as well as how to apply psychological methods to solve consumption challenges for some enterprises. These book divides two part. Part one concerns my recommendations how to attempt to solve students' learning psychological need challenges. Part two concerns my recommendations how to attempt to solve client consumption challenges.At part one, this book concerns how to apply psychological and economic behavioral methods to predict customer emotion. The first part concerns to how to apply psychological method to predict consumer emotion. The second part concerns to explain what behavioral economy means and how to apply behavioral economic method to predict consumer behavior. It concerns how to apply psychological method to predict how to manufacture the right food taste to let your consumers to like to eat your food as well as how to produce or design your products to sell to them successfully. I shall use three science and psychology ethnographic research and facial reading technology and online consumption behavioral methods to explain how to predict your client's individual taste and need more accurate. Also, it concerns how to apply psychological method to predict consumer behavior. I shall indiate how to use face reading technology predicts consumer emotion to predict how to do the acceptable ingradients to produce foods to let them to feel more enjoyable to eat sweet foods or drink softdrinking as well as how to use video camera to investigate to predict customer emotion to find what factors had attracted them to choose to buy the manufacturers' products to use and judge whether how to increase your product more attractive to win your competitors. It concerns how to find both what the worst attributed factor(s) had influenced the consumers to be caused to decide not to choose to buy your product as well as what the best attributed factor(s) had influenced the consumers to be caused to decide to buy your product in constructive choice process. I shall indicate how manufacturers can analyze to judge whether what the best and worst attributed factor(s) are during every consumer chooses to buy which kind of product or food in constructive choice process.

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

(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.

Learning Technology How Predicts

Learning Technology How Predicts
Author: John Lok
Publisher:
Total Pages: 0
Release: 2022-07
Genre:
ISBN:

This book consists three sections: This three parts concern my three different psychological and technological methods to explain how to predict consumer emotion to achieve to reduce the risk to avoid to invent the new products or foods to sell unsuccessfully. This book concerns how to predict customer' emotion to judge how to manufacture the right food taste to let your consumers to like to eat your food as well as how to produce or design your products to sell to them successfully. I shall use three science and psychology ethnographic research and facial reading technology and online consumption behavioral methods to explain how to predict your client's individual taste and need more accurate.

Psychology Methods Predict Consumer Behaviors

Psychology Methods Predict Consumer Behaviors
Author: John Lok
Publisher:
Total Pages: 204
Release: 2022-01-07
Genre:
ISBN:

This book is concerned how to apply behavioral economy method to predict consumer behavior. Also I shall compare to explain what advantages and disadvantages between any one of my solvable suggestions and the any one of the company's choice of solvable method to these any one sample industry consumer behavioral economic challenges to aim to let any reader to judge whether how to choose the solvable method is better. This book can provide sample industries to let students to learn how to behavioral economy method to predict consumer behaviors. This book divides part one and part two. Part one explains what behavioral economy function and mean is and how applying this method to predict consumer behavior. Part two explains what psychological method mean and function and how appling this method to predict consumer behavior.

The Difference Between Economic and Artificial Intelligent Methods

The Difference Between Economic and Artificial Intelligent Methods
Author: Johnny Ch Lok
Publisher: Independently Published
Total Pages: 554
Release: 2018-11-16
Genre:
ISBN: 9781731438157

How AI technology influnce productivities and service performance ? Whether it can raise productivities and improve service performance?This book aims to explain why and how future artificial intelligent technology ( big data gathering method) can be applied to assit businesses to predict why and when and how consumer behavior changes. I shall explain why traditional psychological and statistic and marketing methods are applied to predict consumer behaviors, human's judgement and analytical effort will be worse to compare AI machine's judgement and analytical effort. Also, I shall indicate different business organizations why they apply AI big data gathering method to help them to design any questionnaires ( surveys) questions which will be more valid and useful to conclude human's questionnaires ( surveys) design questions method.This book has these two research questions need to be answered?(1)Can apply (AI) learning machine predict consumer behaviors?(2)Can (AI) learning machine replace human marketing research method, e.g. survey or human psychological and micro and macro economic methods to predict consumer behaviors more accurate?Nowadays, many businessmen or marketing research professional hope to apply different methods to predict consumer behaviors in order to know what will be future market activities and market changes to help them to choose to implement what kinds of marketing strategies more accurately. The methods include economic environmental change prediction method, consumer individual psychological change prediction method, micro or macro behavioral economic environmental change prediction method, marketing environmental change prediction method etc. different kinds of methods which can be applied to predict how consumer behavioral changes to influence whose behavioral consumption to the manufacturer products sale within one to two years short term or three to five years middle term, even above five years long term business plans.Hence, if the product manufacturers can apply the most suitable consumer behavioral prediction method to predict how consumers' choice will be changed to influence their products sale easily. It will have more beneficial intangible and tangible advantages to achieve the their product easier sale aim to ensure their businesses' future market share to be increased more easier to their countries' choice target sale markets. Otherwise, if they applied the inaccurate consumer behavioral prediction methods to predict how their consumers' behavioral changes wrongly. Then, it will influence their market shares to be same level, even it will decrease their market shares, when their consumer behavioral prediction inaccurately.In my this book first part, I concentrate on indicate whether any artificial intelligence (AI) tools will be one kind of good consumer behavioral prediction method to be choose to apply to predict consumer behaviors. I shall indicate some examples, cases to give reasonable evidences to analyze whether (AI) tools will be one kind suitable tool to be applied to predict when and how consumer behavioral changes. If (AI) can be one kind tool to attempt to be applied to predict when and how consumer behavioral changes. Will it replace other kinds of methods to predict consumer behaviors? Does it have weaknesses to be applied to predict consumer behaviors, instead of strengths? Can it be applied to predict consumer behaviors depending on any situations of only some situation? Finally, I believe that any readers can find answers to answer above these questions in this book.