What Are Marketing Information and Artificial Intelligence Customer Psychological Predictive PDF Download

Author: Johnny Ch Lok
Publisher: Independently Published
ISBN: 9781797083711
Category : Business & Economics
Languages : en
Pages : 254

View

Book Description
Differentiation through the characteristics of cruising route method from (AI) tool route judgementFuture, (AI) tool can attempt to help any cruise entertainment service providers to judge how to design different route to attract different countries age cruise clients' choices to satisfy their cruise journey entertainment needs. The determinants of the cruising route's characteristics ( functional, social, and emotion) is important factor to influence the cruise service provider's success. Cruising product is no longer selected primarily for the cruising service, but for the content of cruising route. So, the cruising route will influence the cruise consumer individual emotion, because it is the main service need for every cruise consumer.The approach called the " land sea cruising in product development" is increasingly becoming an area of interest, e.g. determining the direction of the effects of the individual cruising route characteristics on service value's perception, and providing an evaluation model of the route's perception, and indicating significance variables of attraction. The questions that cruise planners need to know: How does each of the identified determinants affect the overall perceived value of the cruise route? How the overall perceived value of the cruise route affects customer behavior intentions? Because different routes factor will influence cruise consumer individual emotion changing seriously. It means the ship has become only a tool, when the offered route whose attractiveness highly influences the impression of the guests has become crucial.Consumer behavior in cruising segment includes all the activities and influences in the selection of the specific cruise route. There activities result in decisions and actions related to a defined price, selection and reselection of cruising company ( Cannot, Brink and Brijball, 2006).2.3How to apply (AI) tool to arrange cruise route planning have close relationship to influence cruise consumer emotion?Firstly, use value of cruising routes is based on the subjective experience, and shows how individuals assess the route during, or immediately after sailing. It is affiliated with the benefits that cruising guest realize by choosing a route, and it is subjective because it depends on the individual assessment ( photo taken on the route for one guest presents just a family souvenir, and for professional photographers are embodied financial capital).Secondly, the utilitarian value is also subjective-oriented and is tied on the point where the inner and us ability of cruising routes are compared with the sacrifice of the client ( money and time). Finally, the value is considered as the outcome of the comparison of scarifies and personal benefits, which is resulted in essentially utilitarian nature.Hence, route design is the main value of cruising tourism and it is primarily determined and analyzed from the aspect of observed customers. Otherwise, the cruise is only one tool to be caught for the cruise passengers, whether the cruise can let whom to sleep comfortable, providing what kind of food to them to eat, what kind of entertainment facilities are provided to them to play, these issues are not more important to compare how to design route to bring them to travel to anywhere to enjoy in this cruise journey factor. Because how to design the route factor can bring each cruise passenger to influence them to feel either negative or positive emotion directly. The whole route journey planning is the most influential factor to influence the cruise passengers to feel whether they ought choose it's service again or not in the future.

Author: Johnny Ch LOK
Publisher: Independently Published
ISBN: 9781723837647
Category :
Languages : en
Pages : 488

View

Book Description
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.

Author: Johnny Ch Lok
Publisher: Independently Published
ISBN: 9781793850904
Category : Business & Economics
Languages : en
Pages : 254

View

Book Description
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).

Author: Johnny Ch Lok
Publisher: Independently Published
ISBN: 9781795404556
Category : Business & Economics
Languages : en
Pages : 254

View

Book Description
Chapter TwoMicro economic assess the influence on location choices and growth performance consumption prediction.Some economists indicate idea that seen central to the development of regional science at large and to economic geography and international trade theory. In this terms of economies of specialization increase returns to scale and in the case of regional science and economic geography, economies of localization and urbanization.The questions concern: Can choose the best business location to attract consumption growth performance? Does the best destination attract consumption growth?" Two cities attract trade from an intermediate town in the vicinity of the breaking point, approximately in direct proportion to the population of the two cities, and in inverse proportion to the squares of the distances of the intermediate town" ( Reggiani, 1998).It implies some economists believe that geographic location choice factor can influence consumption growth. It is possible due to the location has many people are living. So, it brings many business chance, or the location is one the country's main in economic development location, it can attract many travelers choose to go to the location to travel. So, it has many travelling clients to prefer to consumer.However, a smaller region can still attract consumption growth, if it had good transportation system. For example, a small region may not have its own university, but inhabitants may still have access to higher education. Elsewhere accessibility measures are also need in activity location models, where access ability is the way through which the quality of the transport system influences the land use.So, it seems although the regional land is small size and far from cities, but if it can have good transportation system to provide any people to travel the small size regional land from outside cities. It is possible to bring consumption growth. However, some economists believe that distance influence relations in economics and economic geography in two ways: first, natural resources are distributed unevenly across space and second, distance separates various activities from each other. They apply " law of demand" to support their reasons.In regional sciences, accessibility plays an important role for analyzing the distribution of economic cities and regional development. Within regional science, the attempt to predict and explain the distribution of economic activity has become known as economic geography. Research in economic geography attempt to answer the question: What forces cause geographic behavioral consumption? Some economists support the production function and into the interaction between transportation cost and plant level scale economies, this geographical factor will bring much geographical behavioral consumption. For example, accessibility of population is an indicator of market size for suppliers of products and services, whereas successful ability to GDP could be an indicator of the market size for suppliers of high level business services ( Spiekermannn and Wegener, 2007).

Author: Johnny Ch Lok
Publisher: Independently Published
ISBN: 9781793284693
Category : Business & Economics
Languages : en
Pages : 254

View

Book Description
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:

Author: Johnny Ch Lok
Publisher: Independently Published
ISBN: 9781720160762
Category :
Languages : en
Pages : 174

View

Book Description
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.

Author: Musiolik, Thomas Heinrich
Publisher: IGI Global
ISBN:
Category : Business & Economics
Languages : en
Pages : 464

View

Book Description
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.

Author: Johnny Ch Lok
Publisher: Independently Published
ISBN: 9781793169921
Category :
Languages : en
Pages : 254

View

Book Description
How to achieve an efficient marketing communication strategy? To achieve an efficient marketing communication strategy to the organization. It includes this process: It needs to identify who are its target customers ( main target customer) potential customer and prospects. Then, it needs to measure the valuation of its different groups of client ( e.g. age, sex, shopping characteristics). Next, it needs to create and deliver the right or suitable or useful or persuasive messages and incentives to let its different group clients to know what its product or service existing in its country or global market places. Next, it needs to estimate how much it can earn return on its customer investment for its future possible reward. Because it if estimated that its marketing communication expenditure can not achieve its budget return in customer investment reward. Then, it needs revise its this ( these) kind of marketing communication tool (s) whether it ( they) is ( are) useful to promote its product or service to let clients to know. Finally, it needs to implement its budgeting allocation and evaluation to review its every time marketing communication tool(s) whether is (are) achieved its original aim. If it believed or confirmed its slae result is not successful. Then, it needs to revise its marketing communication tool(S) whether they (it) is (are) the most suitable or useful one tool(s) t be used to promote to its clients in the future. Hence, the whole process of marketing communication strategy is very important to influence its sale number. Every product or service provider needs to spend enough time and human resource to marketing communication tool resources to decide how to design to implement in order to sell in failure finally.For one integrated marketing communication model of brand contact delivery system case example: The brands customer ( prospect exposure will include message and incentive both aspects. Message and incentive will bring promotion communication information concern relevance and receptivity to the brand's product or service to let its customers to know or remember or familiar by these any one or more than one delivery systems, such as product/use of the package product message tool or directed marketer channel or undirected member channel or traditional media tools ( accesses or unintentional, such as TV, radio, magazine, signage outdoor direct marketing tool or electronic media tools ( wired or wireless ) such as website second intranet or mobile phone engines GPS or special events promotion methods ( natural or sponsored), such as holiday events or sport cultural trade events. All any one of these media delivery systems will be one choice tool to let the product/ service providers to be chosen to find which tool is the most efficient delivery tool. Hence, one marketing communication strategy elements include the marketing communication source is the company/brand or agency, the brand message concerns ( planned, unplanned, product or/and service) and the channel includes newspapers, TV, radio, magazine, e-mails, salespeople sale service, customer service, internet and the receiver is the target audience in the whole marketing communication process. Finally, the delivery system will bring feedback to the company/brand, agency and the target audience both. The feedback includes that purchase/not purchase, request information, visit store, sample product, repeat visit/purchase.

Author: Johnny Ch Lok
Publisher: Independently Published
ISBN: 9781793961334
Category :
Languages : en
Pages : 254

View

Book Description
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.

Author: A. K. Pradeep
Publisher: John Wiley & Sons
ISBN: 1119484081
Category : Business & Economics
Languages : en
Pages : 272

View

Book Description
Get on board the next massive marketing revolution AI for Marketing and Product Innovation offers creatives and marketing professionals a non-tech guide to artificial intelligence (AI) and machine learning (ML)—twin technologies that stand poised to revolutionize the way we sell. The future is here, and we are in the thick of it; AI and ML are already in our lives every day, whether we know it or not. The technology continues to evolve and grow, but the capabilities that make these tools world-changing for marketers are already here—whether we use them or not. This book helps you lean into the curve and take advantage of AI’s unparalleled and rapidly expanding power. More than a simple primer on the technology, this book goes beyond the “what” to show you the “how”: How do we use AI and ML in ways that speak to the human spirit? How to we translate cold technological innovation into creative tools that forge deep human connections? Written by a team of experts at the intersection of neuroscience, technology, and marketing, this book shows you the ins and outs of these groundbreaking technological tools. Understand AI and ML technology in layman’s terms Harness the twin technologies unparalleled power to transform marketing Learn which skills and resources you need to use AI and ML effectively Employ AI and ML in ways that resonate meaningfully with customers Learn practical examples of how to reinvest product innovation, brand building, targeted marketing and media measurement to connect with people and enhance ROI Discover the true impact of AI and ML from real-world examples, and learn the thinking, best practices, and metrics you need to capture this lightning and take the next massive leap in the evolution of customer connection. AI for Marketing and Product Innovation shows you everything you need to know to get on board.