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: In -store consumer digital signage behavior how can influence consumer behavior by (AI) marketing research survey method?Digital signage is a new technology, where people broadcasting displays adapt their content to the audience demographic and features. In some shopping centers, retailers like to use machine learning methods on real-world digital signage viewer data to predict consumer behavior in a retail environment. Digital signage systems are nowadays primarily used as public information interfaces. They display general information, advertise content or serve as media for enhanced customer experience.Interaction design studies show that the interaction level of users with digital signage systems will increase, including also the mobility of users around the display. Since digital signage systems can have a significant effect on commerce, which are also rapidly shopping centers ad retail stores. Retail generalization studies reveal that in-store digital signage increases customer traffic and sales ( Burke, 2009).Some consumer psychologists believe purchase decision processes can be described with five stages. The first stage is problem recognition, where consumer recognizes a problem is a need. The second stage is search for information via heightened attention of consumer towards information about a certain product, which can even resolve in actual proactive search for information. The third stage represents the evaluation of alternatives , which usually involves a comparison between various options and features based in the models of the expected value and beliefs. In the fourth stage of the purchase decision process, a provider, place, time, value , type and quality of the selected product or service and determined. The fifth stage are the final stage describes the post purchase use, behavior and actions.Why will digital signage influence consumers choose to buy the product? It is possible that some consumers who like to use visa card to go to shopping as well as who like to use digital signage to confirm who are the visa card holders to let the businessmen to feel who are rich to let bank give trust to issue visa card to them to use. So, who do not need to bring much money to leave home to prepare to buy anything and who only bring one visa card to leave home safely. Thus, the digital signage systems are a new approach to automatic modelling of in-store consumer behavior based on audience measurement data. It is a unique machine payment method, which can also be used to predict more distinctive characteristics, such as an consumer individual's role in the purchase decision process. So, I believe digital signage audience measurement data can be used to model various user behavior for one kind of in-store consumer behavior prediction of method. Hence, it seems travel agent or airline can choose to apply visa card signature method to encourage travelers to make travel package purchase decision more easily by this electronic card payment method.

Download or read book The Difference Between Artificial Intelligence and Psychological Method Predicts Consumer Behavior written by Johnny Ch Lok and published by Independently Published. This book was released on 2018-09-08 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chapter One Can apply economic models solve marketing changing challenges? Economists indicate economic modeling can provide a logical, data to help organize the analyst's thoughts. The model helps the economist logically isolate and sort out complicated chains of cause and effect and influence between the numerous interacting elements in an economy. There are four types of models used in economic analysis: Visual models, mathematical models, empirical models and simulation models. Visual models are simply pictures of an abstract economy: graphs will lines and curves that tell an economic story. It is one kind of micro or macro-economic method to predict consumer behavioral change. Some visual models are diagrammatic such as which flow the income thought the economy from one sector to another ( micro economic environment). It is mathematical model, when it is presented the mathematics are explained what the data analysis is or not. The model does not normally require a knowledge of mathematics, but still allow the presentation of complex relationship between economic variable. For example, the common supply-and demand model is meant to show the effect of inflationary expectations upon price and output. In this application, an increase in inflationary expectations causes demand to shift, raising prices and outputs (macro-economic environment). For another example, a very simple micro-economic model would include a supply function (explaining the behavior of products or those who supply commodities to the market), a demand curve ( explaining the behavior of purchasers) and an equilibrium equation, specifying the simple conditions that must be met if the model's equilibrium is to be satisfied. So, the variables in a model like this represent a type of economic activity (such as demand) or data ( information ) that either determines or is determined by that activity ( such as a price or interest rate variable change activity). Dynamic models, in contrast, directly incorporate time into their structure. This is usually done in economic modeling by this mathematical systems of difference of differential equations. For example, it can use a difference equation from a business cycle model, investment now depends upon changes in income in the past. Time is incorporated into the model. Dynamic models, when they can be used, sometimes better represent the business cycles, because certainly behavioral response and timing strongly shape the character of a cycle. For another example, if there is a delay between the time income is received and when it is spent. A model that can capture the delay is likely to those higher consumption desire to the consumer. It is a micro-personal behavioral consumption predict method. So, the user can experiment with an endless variety of values and assumptions to see whether results obtained are realistic or insightful. Since computers are now powerful and cheaper, the importance of dynamic simulation models should follow the future prediction time, when the consumer income receive and when it is spent to predict how much degree of the consumer's consumption desire in micro-economic view point. Another model to be applied to predict consumption behavior. It is expectations and enhanced model, it includes one or more variables based upon economic expectations about future values. For example, if consumers for whatever reason, expect the inflation rate to be much higher next year, then this year, they are said to have formed inflationary expectations. If numerical values are being used in a model and the current inflation rate is 9%, if they expect inflation to be higher next year, the variable for inflationary expectations might be given be a value if 12% or more.

Download or read book Can Apply Artificial Intelligence Predicts Consumer Behavior in Business Environment written by Johnny Ch Lok and published by CA Apply Artificial Intelligen. This book was released on 2018-09-09 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: Can implicit design questionnaire (survey) or /and interview methods can test consumer behavior for measuring consumer response to environment protection product by AI marketing research survey method? Some design researchers often use interviews and/or questionnaires to measure consumer response to any product design method, such as environment protection product. In psychology, " implicit" tests have been developed in an attempt to overcome self-report biases and to obtain a more automatic measure of attitudes. Two exploratory studies have conducted to (i) establishing an acceptable methodology for implicit tests using product images, and (ii) determining whether response to products can produce significant effects in affection. How to contribute design-research methodological developments for measuring consumer response. For example, product design research and conventional methods need to be gathered consumer feedback. How can consumer research in product design? Understanding how consumer experience designed products has important implications for design research and design practice. Thus, product manufacturers need to attempt to develop knowledge about the relationship between product designs and the responses who elicit from consumers, e.g. borrowing which product features can contribute to consumer preference by presenting consumers with a range of products or design variants and measuring subjective responses to them. This process can offer guidance for what products or design variants might be most preferred and can give useful clues for further design development. Consumer response can be measured by questionnaires( surveys), interviews and focus groups. Questionnaire methods are especially popular and often feature attitude response. However, consumer survey responses may not fully capture reactions to a product or predict future behavior, such as purchasing decisions in the marketplace. This is evidence that actual product-related behavior is affected any more spontaneous or impulse processes, as consumers are often distracted or processes for time when consuming products or making product decisions ( Friese, Hofman & Wanke, 2009). For example, cell phone images can be replaced with cars in order to develop the experiment using a second product category. As with phones, vehicles were chose, due to their wide appeal, user involvement and variety of models for potential testing. In these experimental studies, the consumption psychologists selected products from two categories ( phone models and car models) with the intention of measuring significant differences in approach bias among product stimuli. These consumption psychologists aim to test that of the method could be defined to measure attitudes with sufficient sensitivity, variants of particular designs could also be used as stimuli, offering feedback on the viability of different design directions. The consumption psychologists feel it will be helpful to add multiple questions to the self-report stage . Instead of a single attractiveness rating, who might as about " liking" or "employing additional methods." Comparison with real would measure, such as willingness to pay, prior ownership or observed consumption behavior may also be instructive. It may also be worthwhile test a version of the task where the correct response is determined by a feature, such as class membership ( product color), shape, brand etc. instead of image, location or rotation. It seems survey method can be used to predict whether how to design environment protection product to attract many consumer choices. In the economic view point, instead of consumer will compare different similar product price, who also compare product color, shape, size of design factor to decide to make final consumption decision.

Download or read book Artificial Intelligence Applies to Consumer Behavioral Predictive Technology written by Johnny Ch LOK and published by . This book was released on 2018-11-30 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Artificial Intelligence and Consumer Behavior Relationship written by Johnny Ch Lok and published by Independently Published. This book was released on 2018-09-14 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Economic science or economic art methods predict consumer behavior Economic is both a science and art. Economic is considered as science because systematic knowledge derived from observation, study and experimentation. An art is the practical application of knowledge for achieving definition ends. A science teaches us to know a phenomenon and art traches us to do a thing. How to apply economic science or art method to predict consumer behavior? for example, there is a inflation US this year. This information is derived from positive science. The government takes certain fiscal and monetary measures to bring down to general level of prices in the country. The study of the monetary measures to bring down inflation makes the subject of economics as an art. Hence, as this case, if US government applies economic science or art method to predict this year will have inflation in US, then US government will attempt to avoid social general product prices to be raised, due to inflation influence. It aims to avoid US consumers reduce consumption desire in this year. For another example, nothing could be more useful than water. But in much of the world waste is plentiful enough that another glass more or less matters little to a fresh water supply agent businessman. So, water is chap. But, if any offices buy bottle of glass fresh water to let employees to drink. It will bring advantages that they do not spend time to buy water to drink when they are working in the office time in any offices as well as employees do not need to heat water to drink to waste time to work in offices. So, the bottle of fresh drinking water supply agent is one kind of drinking water product monopoly fresh drinking water supplier to supply fresh drinking water to satisfy office employees who do not need to spend time to heat water to drink in offices. Hence, it is possible that replace other different kind taste of drink or office employees themselves heat water drink in offices. It is general office employees' drinking habits and drinking choice in offices popularly. So, the bottle of fresh drinking water supply agents will concentrate on selling their fresh drinking water to office employee customers only in global fresh drinking water consumption target market. The office employees must be fresh drinking water companies' main target consumers. What is economic laws qualitative or quantitative method to predict consumer behavior? Law of economic are qualitative in nature. They are not exactly stated in quantitative terms. They tell the direction of change which is expected rather than the amount of change. For example, according to the law of consumer demand, the quantity demanded varies inversely with price, We don't say that 10% rise in price will lead to 30% fall in the customers' quantity demand. What is economic merits of deduction method? This method is near to reality. It is less time consuming and less expensive. the use of mathematical techniques in deducing theories of economics brings exactness and clarity in economic analysis. The deductive method is highly abstract. It require a great deal of care to avoid bad logic or faulty economic reasoning. This method makes conclusions to predict consumer behavior, due to reliance on imperfect and correct assumptions. It involves the process of reasoning from particular facts to general principle on the basic of experimentations, observations and statistical methods. In this method, data is collected about a certain economic phenomenon. There are systematically arranged and the general conclusions are drawn from them.

Download or read book Enhancing and Predicting Digital Consumer Behavior with AI written by Musiolik, Thomas Heinrich and published by IGI Global. This book was released on 2024-05-13 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding consumer behavior in today's digital landscape is more challenging than ever. Businesses must navigate a sea of data to discern meaningful patterns and correlations that drive effective customer engagement and product development. However, the ever-changing nature of consumer behavior presents a daunting task, making it difficult for companies to gauge the wants and needs of their target audience accurately. Enhancing and Predicting Digital Consumer Behavior with AI offers a comprehensive solution to this pressing issue. A strong focus on concepts, theories, and analytical techniques for tracking consumer behavior changes provides the roadmap for businesses to navigate the complexities of the digital age. By covering topics such as digital consumers, emotional intelligence, and data analytics, this book serves as a timely and invaluable resource for academics and practitioners seeking to understand and adapt to the evolving landscape of consumer behavior.

Download or read book Artificial Intelligence Big Data Gathering How Impacts Consumer Behavior written by Johnny Ch LOK and published by . This book was released on 2018-09-21 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has these two research questions need to be answered?(1) Can apply (AI) learning machine predict consumer behaviors?(2) Can (AI) learning machine replace human marketing research method, e.g. survey or human psychological and micro and macro economic methods to predict consumer behaviors more accurate? Nowadays, many businessmen or marketing research professional hope to apply different methods to predict consumer behaviors in order to know what will be future market activities and market changes to help them to choose to implement what kinds of marketing strategies more accurately. The methods include economic environmental change prediction method, consumer individual psychological change prediction method, micro or macro behavioral economic environmental change prediction method, marketing environmental change prediction method etc. different kinds of methods which can be applied to predict how consumer behavioral changes to influence whose behavioral consumption to the manufacturer products sale within one to two years short term or three to five years middle term, even above five years long term business plans. Hence, if the product manufacturers can apply the most suitable consumer behavioral prediction method to predict how consumers' choice will be changed to influence their products sale easily. It will have more beneficial intangible and tangible advantages to achieve the their product easier sale aim to ensure their businesses' future market share to be increased more easier to their countries' choice target sale markets. Otherwise, if they applied the inaccurate consumer behavioral prediction methods to predict how their consumers' behavioral changes wrongly. Then, it will influence their market shares to be same level, even it will decrease their market shares, when their consumer behavioral prediction inaccurately. In my this book first part, I concentrate on indicate whether any artificial intelligence (AI) tools will be one kind of good consumer behavioral prediction method to be choose to apply to predict consumer behaviors. I shall indicate some examples, cases to give reasonable evidences to analyze whether (AI) tools will be one kind suitable tool to be applied to predict when and how consumer behavioral changes. If (AI) can be one kind tool to attempt to be applied to predict when and how consumer behavioral changes. Will it replace other kinds of methods to predict consumer behaviors? Does it have weaknesses to be applied to predict consumer behaviors, instead of strengths? Can it be applied to predict consumer behaviors depending on any situations of only some situation? Finally, I believe that any readers can find answers to answer above these questions in this book. In my this book second part, I shall explain why and how human can possible apply (AI) tool to predict consumer individual emotion. I shall indicate case studies to explain how consumer individual better or worse emotion how to influence whose consumption behavior in different situation. Finally, I shall indicate evidences to conclude how and why (AI) tool that can be used to predict consumer individual emotion and it will have direct relationship to influence consumption behavior, as well as how (AI) tool can assist businessmen to judge whether what reasons case the customer does not choose to buy its product, it is possible because the product high price factor, poor product quality or poor staff service performance or attitude etc. different factors to influence the consumer decides to choose to buy the other product consequently, when the (AI) tool can confirm consumer has good or bad emotion to judge what factors are the causes his decision making at the moment. Readers can understand why and how (AI) tool can be attempt to be applied to predict customer emotion and it can influence positive or negative consumption behavior to the product clearly in this part.

Download or read book Artificial Intelligence in Marketing and Consumer Behavior Research written by Taewoo Kim and published by . This book was released on 2023-10-03 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence in Marketing and Consumer Behavior Research reviews the state of the art of behavioral consumer research involving AI-human interactions and divides the literature into two primary areas based on whether the reported effects are instantiations of consumers displaying a positive or negative response to encounters with AI.

Download or read book Marketing Information Prediction and Artificial Intelligence Customer Psychological Prediction written by Johnny Ch Lok and published by Independently Published. This book was released on 2019-01-12 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.

Download or read book Artificial Intelligence Predicts Consumer Behavioral Tool written by Johnny Ch Lok and published by Createspace Independent Publishing Platform. This book was released on 2018-06-05 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chapter One How can artificial intelligent tools predict consumer behavior in vehicle market Nowadays, many vehicle manufacturers hope their vehicles can attract to vehicle buyers to choose to buy their vehicles. However, there are many different brands of vehicles to provide to them to choose, so the vehicle market competition is very serious. How to judge their different kinds of vehicle price which is reasonable acceptance to attract vehicle buyers to choose to buy the brand of vehicle manufacturers' any kinds of vehicles, e.g. fast speed sport style vehicles, comfortable and slow speed common cars, for four passengers common small size or more than four passengers common large car size? How to evaluate the vehicle prices issue is important factor to influence vehicle buyers' choices. Either if the brand of vehicle price is too high to compare brands, it will influence many vehicle buyers choose to buy other brands' vehicles or if the brand of vehicle price is too low, it will influence vehicle buyers feel this brand's vehicle's quality is worse to compare to other vehicle brands' similar vehicle products.

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 ?

Download or read book Artificial Intelligence along the Customer Journey written by Ada Maria Barone and published by Springer Nature. This book was released on 2023-12-19 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of several AI solutions has revolutionized the way in which consumers behave. Serving as a guide to the role that AI plays on different aspects of consumers’ life, this book provides a comprehensive understanding of the main artificial intelligence (AI) solutions available in the market. In particular, the authors adopt a customer experience approach to investigate how different AI technologies play a role at different stages of the customer journey (e.g., from pre-purchase to post-purchase decisions). Covering a range of technologies, such as augmented reality, voice assistants, chatbots and robots, readers will be able to learn which strategies and AI solutions are more effective at different stages of the customer journey.

Download or read book What Are Marketing Information and Artificial Intelligence Customer Psychological Predictive Methods written by Johnny Ch Lok and published by Independently Published. This book was released on 2019-01-06 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: The (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:

Download or read book Artificial Intelligence Predicts Consumer Behaviors written by Johnny Ch Lok and published by . This book was released on 2020-12-05 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the future, (AI) will bring their benefits to influence customers to build positive emotions to any retailers in these aspects as below:1.Future (AI) big data gather tool will be an area of compute science that deals with giving machines, the ability to seem like they have human intelligence. In short, it is the power of a machine to copy intelligent human behavior. For example, machine learning algorithms are being integrated into analytics and customer relationship management platforms to uncover information on how to better serve customers, chat bots have been incorporated into websites to provide immediate service to customers.2.(AI) adoption continue to rise with chat bots taking the lead. Due to increasing ease of deployment, instant availability and improved quality, chat bots will become more and more common to manage customer service queries and to make intelligent purchase recommendations. Also, retailers can engage this kind of technology to answer continue questions and supplement customer support with chat-based shopping experience. So, (AI) and declines personalized, customized and localized experiences to customers. (AI) will be applied across the entire retail product and service cycle, firm manufacturing to post-sale customer service interactions. Hence, retailers can use (AI) to its fullest potential will be also to influence purchases in the moment and anticipate future purchases, guiding shoppers towards the right products in a regular and highly personalized manner.3.(AI) technology can rise the conscious customers. Customers are demanding an increased interest in the ethical practice of the brands they buy from. Todays, customers have a well-developed sense of what is solely intended to drive sales. This has lead to a rise in consumers ho make values based judgements about what to buy and where to shop. These consumers believe their purchase habits have an impact on the world. To win customers, retailers need have good conscious to predict consumers' desire. Future, (AI) data gather technology will be a good consumer behavior predictive tool to predict about for years will now become customer expectations and will have drastically changed the path to purchase. So, (AI) data gather tool is the predictive consumer expectations tool on every interaction, they have these brands.4.Future (AI) can be impacted to influence consumer behaviors by its potential to free up time, enhance, quality, and enhance personalization. The industries include: Healthcare industry can apply (AI) to support diagnosis by detecting variations in patient data, early identification of potential pandemics, imaging diagnostics; automat industry can apply (AI) to autonomous fleets to ride sharing, semi-autonomous features, such as driver assist, engine monitoring and predictive, autonomous maintenance; financial service industry can apply (AI) to design the suitable personalized financial planning, fraud detection and anti-money laundering and automation of customer operation; transportation and logistics industry can apply (AI) to autonomous trucking and delivery, traffic control and reduced congestion and enhanced security; technology, media and telecommunications industry can apply (AI) to search media, and recommendation, customized content creation and personalized marketing and advertising to attract retailers to promote; retail and consumer industry can apply (AI) to design personalized production, anticipating customer demand, inventory and delivery management; energy industry can apply (AI) to read and record smart metering, more efficient grid operation and storage and predictive maintenance; manufacturing industry can apply (AI) to enhance monitoring and auto-correction of processes, supply chain and production optimization and on-demand production.

Download or read book Artificial Intelligence Predicts Consumer Behavioral Tool Business Journey written by Johnny C. H. Lok and published by Independently Published. This book was released on 2018-11-21 with total page 62 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, I concentrate on indicate whether any artificial intelligence (AI) tools will be one kind of good consumer behavioral prediction method to be choose to apply to predict consumer behaviors. I shall indicate some examples, cases to give reasonable evidences to analyze whether (AI) tools will be one kind suitable tool to be applied to predict when and how consumer behavioral changes. If (AI) can be one kind tool to attempt to be applied to predict when and how consumer behavioral changes. Will it replace other kinds of methods to predict consumer behaviors? Does it have weaknesses to be applied to predict consumer behaviors, instead of strengths? Can it be applied to predict consumer behaviors depending on any situations of only some situation? Finally, I believe that any readers can find answers to answer above these questions in this book.

Download or read book Artificial Intelligence Predicts Consumer Behaviors written by John Lok and published by Independently Published. This book was released on 2021-09-10 with total page 78 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.

Download or read book Artificial Intelligence How Influences Consumer Behaviors written by Johnny Ch LOK and published by . This book was released on 2020-04-10 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.