Big Data Gathering Predicts Retail Industry Consumer Behavior

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Big Data Gathering Predicts Retail Industry Consumer Behavior

Author : Johnny Ch Lok
Publisher : Independently Published
ISBN 13 : 9781724133618
Total Pages : 770 pages
Book Rating : 4.1/5 (336 download)

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Book Synopsis Big Data Gathering Predicts Retail Industry Consumer Behavior by : Johnny Ch Lok

Download or read book Big Data Gathering Predicts Retail Industry Consumer Behavior written by Johnny Ch Lok and published by Independently Published. This book was released on 2018-09-28 with total page 770 pages. Available in PDF, EPUB and Kindle. Book excerpt: Prepare This book aims to explain why and how future artificial intelligent technology ( big data gathering method) can be applied to assit businesses to predict why and when and how consumer behavior changes in retail industry. I shall explain why traditional psychological and statistic and marketing methods are applied to predict consumer behaviors, human's judgement and analytical effort will be worse to compare AI machine's judgement and analytical effort. Also, I shall indicate different business organizations why they apply AI big data gathering method to help them to design any questionnaires ( surveys) questions which will be more valid and useful to conclude human's questionnaires ( surveys) design questions method. This book has these two research questions need to be answered? (1) Can apply (AI) learning machine predict consumer behaviors in retail industry? (2) Can (AI) learning machine replace human marketing research method, e.g. survey or human psychological and micro and macro economic methods to predict consumer behaviors more accurate in retail industry? Nowadays, many businessmen or marketing research professional hope to apply different methods to predict consumer behaviors in order to know what will be future market activities and market changes to help them to choose to implement what kinds of marketing strategies more accurately. The methods include economic environmental change prediction method, consumer individual psychological change prediction method, micro or macro behavioral economic environmental change prediction method, marketing environmental change prediction method etc. different kinds of methods which can be applied to predict how consumer behavioral changes to influence whose behavioral consumption to the manufacturer products sale within one to two years short term or three to five years middle term, even above five years long term business plans. Hence, if the product manufacturers can apply the most suitable consumer behavioral prediction method to predict how consumers' choice will be changed to influence their products sale easily. It will have more beneficial intangible and tangible advantages to achieve the their product easier sale aim to ensure their businesses' future market share to be increased more easier to their countries' choice target sale markets. Otherwise, if they applied the inaccurate consumer behavioral prediction methods to predict how their consumers' behavioral changes wrongly. Then, it will influence their market shares to be same level, even it will decrease their market shares, when their consumer behavioral prediction inaccurately. In my this book first part, I concentrate on indicate whether any artificial intelligence (AI) tools will be one kind of good consumer behavioral prediction method to be choose to apply to predict consumer behaviors. I shall indicate some examples, cases to give reasonable evidences to analyze whether (AI) tools will be one kind suitable tool to be applied to predict when and how consumer behavioral changes. If (AI) can be one kind tool to attempt to be applied to predict when and how consumer behavioral changes. Will it replace other kinds of methods to predict consumer behaviors? Does it have weaknesses to be applied to predict consumer behaviors, instead of strengths? Can it be applied to predict consumer behaviors depending on any situations of only some situation? Finally, I believe that any readers can find answers to answer above these questions in this book.

Big Data Gathering Predicts Retail Industry Consumer Behavior

Author : Johnnny Ch LOK
Publisher :
ISBN 13 : 9781730741760
Total Pages : 748 pages
Book Rating : 4.7/5 (417 download)

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Book Synopsis Big Data Gathering Predicts Retail Industry Consumer Behavior by : Johnnny Ch LOK

Download or read book Big Data Gathering Predicts Retail Industry Consumer Behavior written by Johnnny Ch LOK and published by . This book was released on 2018-11 with total page 748 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to explain why and how future artificial intelligent technology ( big data gathering method) can be applied to assit businesses to predict why and when and how consumer behavior changes in retail industry. I shall explain why traditional psychological and statistic and marketing methods are applied to predict consumer behaviors, human's judgement and analytical effort will be worse to compare AI machine's judgement and analytical effort. Also, I shall indicate different business organizations why they apply AI big data gathering method to help them to design any questionnaires ( surveys) questions which will be more valid and useful to conclude human's questionnaires ( surveys) design questions method.This book has these two research questions need to be answered?(1)Can apply (AI) learning machine predict consumer behaviors in retail industry?(2)Can (AI) learning machine replace human marketing research method, e.g. survey or human psychological and micro and macro economic methods to predict consumer behaviors more accurate in retail industry?Nowadays, many businessmen or marketing research professional hope to apply different methods to predict consumer behaviors in order to know what will be future market activities and market changes to help them to choose to implement what kinds of marketing strategies more accurately. The methods include economic environmental change prediction method, consumer individual psychological change prediction method, micro or macro behavioral economic environmental change prediction method, marketing environmental change prediction method etc. different kinds of methods which can be applied to predict how consumer behavioral changes to influence whose behavioral consumption to the manufacturer products sale within one to two years short term or three to five years middle term, even above five years long term business plans.Hence, if the product manufacturers can apply the most suitable consumer behavioral prediction method to predict how consumers' choice will be changed to influence their products sale easily. It will have more beneficial intangible and tangible advantages to achieve the their product easier sale aim to ensure their businesses' future market share to be increased more easier to their countries' choice target sale markets. Otherwise, if they applied the inaccurate consumer behavioral prediction methods to predict how their consumers' behavioral changes wrongly. Then, it will influence their market shares to be same level, even it will decrease their market shares, when their consumer behavioral prediction inaccurately.

Big Data, Analytics, and the Future of Marketing and Sales

Author : Mckinsey Chief Marketing & Sales Officer Forum
Publisher : Createspace Independent Pub
ISBN 13 : 9781500721091
Total Pages : 156 pages
Book Rating : 4.7/5 (21 download)

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Book Synopsis Big Data, Analytics, and the Future of Marketing and Sales by : Mckinsey Chief Marketing & Sales Officer Forum

Download or read book Big Data, Analytics, and the Future of Marketing and Sales written by Mckinsey Chief Marketing & Sales Officer Forum and published by Createspace Independent Pub. This book was released on 2014-08-02 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data is the biggest game-changing opportunity for marketing and sales since the Internet went mainstream almost 20 years ago. The data big bang has unleashed torrents of terabytes about everything from customer behaviors to weather patterns to demographic consumer shifts in emerging markets. This collection of articles, videos, interviews, and slideshares highlights the most important lessons for companies looking to turn data into above-market growth: Using analytics to identify valuable business opportunities from the data to drive decisions and improve marketing return on investment (MROI) Turning those insights into well-designed products and offers that delight customers Delivering those products and offers effectively to the marketplace.The goldmine of data represents a pivot-point moment for marketing and sales leaders. Companies that inject big data and analytics into their operations show productivity rates and profitability that are 5 percent to 6 percent higher than those of their peers. That's an advantage no company can afford to ignore.

Big Data Gathering Predicts Sevice Industry

Author : Johnny Ch LOK
Publisher :
ISBN 13 : 9781092150484
Total Pages : 399 pages
Book Rating : 4.1/5 (54 download)

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Book Synopsis Big Data Gathering Predicts Sevice Industry by : Johnny Ch LOK

Download or read book Big Data Gathering Predicts Sevice Industry written by Johnny Ch LOK and published by . This book was released on 2019-03-30 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: Challenges of artificial intelligence, algorithms technology and machine learning impact to consumption marketMarkets have played a key role in providing individuals and businesses with the opportunity to gain from trade. If (AI) big data gather tool can predict how to change potential customer behavior in success. The challenges to consumers will face that the overall market consumption model will be dominated by the businessmen only. So, it is not fair or reasonable to consumers, because (AI) big data gather tool has controlled or dominated all consumers' minds and it has predicted how and why every kind of product or service consumer shopping model or consumption behaviors how will change.It will bring this questions: How can market designers learn the characteristics necessary to set optimal, or at least better, reserve prices after they had gather all data to conclude the analytical results of their consumers behaviors how will change? How can market designers better learn the environments of their markets?In response to these challenges, artificial intelligence (AI ) and machine learning are important tools for market design. For example, retailers and marketplaces , such as eBay, Amazon and many others are mining their vast amounts of data to identity patterns that help them create better shopping experiences for their clients and increase the efficiency of their markets. By having better prediction tools, these and their companies can predict and better manage dynamic consumption market environments. The improved forecasting that (AI) and machine learning algorithms provide help marketplaces and retailers better anticipate consumer demand and producer supply as well as help target products and activities for segmented markets. Another important application of (AI) 's strength in improving forecasting to help markets operate more efficiently is in electricity market example. To operate efficiently, electricity marker makers can attempt to apply (AI) machine learning tool to follow every household family electricity consumers' past electricity consumption record to judge ( predict) how it will be every family's forecasting in the year.An inaccurate forecast in the electricity supply and demand that can dramatically affect electricity market bad supply outcomes causing high variance in electricity charge prices or worse, blackouts. By better predicting every family's electricity demand and supply , electricity market makers can better allocate power generation to the most efficient power sources and maintain a more reasonable electricity stable charge market. Any example is design market, the application of (AI) algorithms to market design are already widespread and diverse. (AI) algorithms technology , it is a safe that (AI) will play a growing role in the design and implementation of market over a wide range of applications. The challenges are that how (AI) can guarantee accurate to predict when and why and how consumer behavioral changes to any retail industries. In fact, retailers will need to discover the value that (AI) can bring to what benefits to influence their customer behaviors. 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 examaple, 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.

Artificial Intelligence Big Data Gathering Predicts Consumer Behavior

Author : Johnny Ch LOK
Publisher : Independently Published
ISBN 13 : 9781723837647
Total Pages : 488 pages
Book Rating : 4.8/5 (376 download)

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Book Synopsis Artificial Intelligence Big Data Gathering Predicts Consumer Behavior by : Johnny Ch LOK

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.

Big Data Gathering Can Predict

Author : Johnny Ch LOK
Publisher :
ISBN 13 : 9781793049032
Total Pages : 567 pages
Book Rating : 4.0/5 (49 download)

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Book Synopsis Big Data Gathering Can Predict by : Johnny Ch LOK

Download or read book Big Data Gathering Can Predict written by Johnny Ch LOK and published by . This book was released on 2019-01-02 with total page 567 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chapter sixMain barriers influence artificial intelligence consumer behavioral predictionIn future, it is possible that these barriers will influence how to apply (AI technology) to predict consumer behavior in success. The barriers may include: Lacking of a (AI) digital data gathering vision and strategy, lacking of efficient workforce readiness, (AI) technology constraints., non reaching (AI) consumer behavioral prediction mature stage, time and money and resource constraints, law and regulations prohibition to develop (AI) consumer behavioral prediction bug data gather technology.However, the recommendation of solutions to attack the barriers to influence artificial intelligence consumer behavioral prediction not success, it may include gaining employee buy in to participate and develop (AI) consumer behavioral prediction technology, making customer experience to a concern (AI) big data gather questionnaire investigation, providing compensation, training to employees in order to achieve (AI) consumer behavioral big data questionnaire investigation research digital technological goals and strategy, task senior leaders manage any (AI) digital big data gather technology changes, putting policies and (AI) big data gather digital technology in place to support a fully remote, flexible workforce in any (AI) digital big data gather questionnaires research projects, teaching all employees how to code/understand (AI) big data gather consumer behavioral prediction software development, appointing a chief (AI) officer to manage any (AI) big data gather customer behavioral prediction projects and automate everything and encourage customers to attempt experience to self-service and (AI) big data gather questionnaire research to earn beneficial consumption aim after they gave feedback to any (AI) digital questionnaire researches. So, in the future, the (AI) digital big data questionnaire researches can include these industries surveyed, such as automat m financial services, public healthcare, private healthcare, technology, telecoms, insurance, life sciences, manufacturing, media and entertainment , oil and gas, retail and consumer products etc. Hence, in the future, any of these industries can attempt to apply (AI) digital big data gather technology to predict how and why consumer behaviors will change in order to avoid reducing consumer number threat occurrence.6.1(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.

Big Data in Practice

Author : Bernard Marr
Publisher : John Wiley & Sons
ISBN 13 : 1119231396
Total Pages : 320 pages
Book Rating : 4.1/5 (192 download)

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Book Synopsis Big Data in Practice by : Bernard Marr

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

Artificial Intelligent Data Gathering Tool Predicts Travel Industry Consumer Behavior

Author : Johnny Ch LOK
Publisher :
ISBN 13 : 9781728746418
Total Pages : 379 pages
Book Rating : 4.7/5 (464 download)

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Book Synopsis Artificial Intelligent Data Gathering Tool Predicts Travel Industry Consumer Behavior by : Johnny Ch LOK

Download or read book Artificial Intelligent Data Gathering Tool Predicts Travel Industry Consumer Behavior written by Johnny Ch LOK and published by . This book was released on 2018-10-13 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: The challenges of (AI) big data gather shapingthe future of retail for consumer industriesThe future of retail for consumer industries' (AI) big data gather challenges are similar to future travelling industry's entertainment consumption challenges. Another challenge of (AI) big data gather is that how to shape the consumer behavior to let business owner to feel or know oe predict. It means that how it express it's conclusion or opinion for every consumer behavior after it had gather all big data in any data gather period, e.g. three months, half year or one year consumer shopping model data gather period.Because every kind of industry, consumers will continue to demand price and quality change , with a wide range of convenient fulfilment options among of different kinds of products or services supply. Overall, the (AI) big data gather procedure gives opinion concerns every time retail experience will become more exciting, simple and convenient, depending on the consumer's ever-changing needs. So, I believe that (AI) big data gather every conclusion or result will be different, due to consumer's price and quality demand will often change to every kind of product or service supply in retail industry. So, how to shape (AI) big data gathering's analytical conclusion or result more clear. I shall recommend organizations need to build great understanding of and a stronger connection to increasingly empowered consumers before they plan and implement how to apply (AI) big data gather tool to predict consumer behavior as below:Firstly, (AI) is empowered by technology, the consumer is redefining value. The traditional measures of cost, choice and convenience are still relevant, but not control and experience are also important. Globally, consumers have access to more than 2 billion different products choice by a wide range of traditional competitors and dynamic new entrants, all experimenting with new business models and methods of client engagement. As choice increases, loyalty becomes more difficult familiarity and the consumer becomes more empowered. Businesses will have no choice and constantly innovate and disrupt themselves by meeting new technologies of high standards and expectations of consumers. So, (AI) data gather tool will need to follow different target group of consumers' needs to follow their different kinds of product design or style choice preferable to gather data in order to conclude the different target groups of consumer behavior to give opinion more clear and accurate to let businessmen to understand more clear how its customers' behavioral choice trend in the future half month, even to two years period.Secondly, businessmen need to adopt changing technologies rapidly. Technology will be the key driver of this retail industry. Industry participants will only success if they have a clear prediction to focus on how to using technology to increase the value added to consumers. They must , however, do so will I realistic assessment of their costs and benefits. Hence, (AI) big data gather technological tools will need to design to help them to gather data efficiently by these ways, such as the internet of things ( IOT), artificial intelligence (AI) machine learning, augmented reality (AR)/virtual reality (VR), digital traceability. So, future (AI) big data gather tool are predicted to be most influential customer behavioral positive emotion changing tool for retail , due to their widespread applications , ability to drive efficiencies and impact on labor in order to impact consumer behavior changing effort from negative emotion to positive.

Artificial Intelligence Influences: Marketing Strategy

Author : Johnny Ch Lok
Publisher : Independently Published
ISBN 13 : 9781091760240
Total Pages : 400 pages
Book Rating : 4.7/5 (62 download)

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Book Synopsis Artificial Intelligence Influences: Marketing Strategy by : Johnny Ch Lok

Download or read book Artificial Intelligence Influences: Marketing Strategy written by Johnny Ch Lok and published by Independently Published. This book was released on 2019-03-27 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: However, (AI) big data gather tool will encounter these challenges when any business plans and implements to apply it to predict consumer behavior in retail industry. The challenges include that as below:1.The high cost and difficulty of implementing new technologies . The (AI) big data gather tool needs capital and capabilities to be designed to implement to be applied to different retail industry users. so, expensive barriers to innovation, an organization and the skillsets of its people to support a new design of (AI) big data gather tool, highly digital technology may be required.2.Slow pace of cultural change. Consumers need to adapt or accept (AI) new technology consumption model in the traditional retail industry. The rate of change is outpacing the ability of businesses to keep up. (AI) big data gather tool needs to be designed to adopt in new or evolved business model requires, in most cases, a new level of customer behavioral predictive machine operation will impact to influence any retail businesses' consumer behavioral changes at a minimum, an organization's structure, capabilities, culture and decision making. If the retail business expects to apply (AI) big data gather tool to predict how to change its consumer behaviors and how their consumption behaviors will tend to change in order to achieve to change their positive emotion from negative emotion before they choose to buy its product or consume its service in success.6.3Challenge to using (AI) neural networks to predict customer behavior from big data gather tool(AI) big data gather tool will encounter the challenge: How can predict customer behavior be represented as sequential data describing the interactions of the customer with a company or an (AI) data gather system through the time, e.g. these interactions are items that the customer purchase or views ? So, every customer data gather, (AI) needs to spend time to analyze how and why to cause whose consumption behavioral choice. It is too difficult matter or judgement for (AI) learning. So, (AI) needs to spend time to learn how to analyze every customer's shopping behavior or actin in order to gather all different consumers' past shopping action information in order to help business owners to predict future its potential customer shopping behavior how to change more clear and accurate prediction. (AI) big data gather tool needs to learn to know that how to judge every customer interaction likes purchases over time can be represented with sequential data. Sequential data has the main property that the order of the information is important. Many (AI) machine learning models are not suited for sequential data, as they consider each input sample independent from previous ones. Therefore, at the end of the sequence, (AI) big data gather learn machines need to keep in their internal state of every customer purchase data, kind of product or service, price, whole year consumption times form all previous inputs, making them suitable for this type of data.

Methods Predict Consumer Behavior

Author : John Lok
Publisher :
ISBN 13 :
Total Pages : 164 pages
Book Rating : 4.8/5 (864 download)

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Book Synopsis Methods Predict Consumer Behavior by : John Lok

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

THE FOODIE CULTURE

Author : DAVID SANDUA
Publisher : David Sandua
ISBN 13 :
Total Pages : 225 pages
Book Rating : 4./5 ( download)

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Book Synopsis THE FOODIE CULTURE by : DAVID SANDUA

Download or read book THE FOODIE CULTURE written by DAVID SANDUA and published by David Sandua. This book was released on with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the fascinating world of "Foodie" culture, a culinary odyssey that captures the essence of our collective love of food. On this journey, we delve into the most exquisite corners of food, exploring not only the flavors that excite our palate, but also the deep connection between food, culture, and society. Through detailed and passionate analysis, this book unfolds the layers of a global phenomenon that has transformed the way we experience, enjoy, and value food. From the evolution of food appreciation to the influence of digital media on our gastronomic choices, each page invites you to savor the richness of culinary diversity, the importance of conscious consumption, and the hedonistic pleasure that resides in every bite. "Foodie Culture" is a celebration of food as an art, a science, and a means of human connection, offering an in-depth perspective on how a passion for gastronomy shapes our world.

What Are Marketing Information and Artificial Intelligence Customer Psychological Predictive

Author : Johnny Ch Lok
Publisher : Independently Published
ISBN 13 : 9781793171849
Total Pages : 254 pages
Book Rating : 4.1/5 (718 download)

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Book Synopsis What Are Marketing Information and Artificial Intelligence Customer Psychological Predictive by : Johnny Ch Lok

Download or read book What Are Marketing Information and Artificial Intelligence Customer Psychological Predictive written by Johnny Ch Lok and published by Independently Published. This book was released on 2019-01-04 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: (AI) digital data gather technology predicts food consumer behavior's main barriersWhat are the main barriers to food industry? When the food manufacturer applies (AI) big data gather technology to predict food consumer behavior? The barriers include that the food manufacturer / provider needs to decide whether when the right time is applied to the right (AI) digital big data prediction tool channel to find the right food consumers to be chose to full food consumption satisfactory questionnaires, how to gather multi-class food consumption classifiers on real-world food consumers transactional data from the food sale domain consistently to show the critical numbers of different kinds of food items at which the predictive performance most accurate? So, any food manufacturer / provider's advanced in (AI) digital data gather warehousing and management technologies can provide that opportunities for food business to enhance long term relationship with the food providers' clients. However, food industry's (AI) digital data gather aims to improve food customer product targeting, increase food customer loyalty and food purchase probability to the food supplier. To effective identify, understand and satisfy the needs of their food customers, the food suppliers need to develop the right (AI) digital questionnaire questions and find the right food customers to fill every right questions from every digital questionnaire at the right time through the right channel. Above of all these, they will be the barriers when one food supplier expects its (AI) digital data gather questionnaires which can conclude the most accurate prediction concerns any kinds of consumer food product choices. So, such as (AI) digital data prediction model, it is needed to incorporate into the food market segmentation, food customer targeting, and food challenging decisions with the goal of maximizing the total food customer lifetime. For example, (AI) big data gather transaction data is reasonable and accurate for building predictive models. Transaction data can be electronically collected and readily made available for data mining in lot quantity at minimum extra costs.Suggestion to apply (AI) prototypes of food customer profiles method to predict food customer behavioral changes. Prototypes of food customer profiles mean to be extracted from the discovered bins and multi-class classifies models are built using those prototypes. The learned models can than be used to predict the class of food customer profiles ( e.g. restaurants, school canteens, supermarkets etc. food suppliers) based on their food purchases. The approach is validated on the case study of a food retail and food service company operating in food and beverages market.So, a food customer profile, it is a description (AI) data gather tool will record every of food customer using available information, which help in understanding their background and food consumption behavior. (AI) data gather tool can well develop every food customer profile, every food customer data is essential in food market analysis as they aid food suppliers in saving time and money by highlighting the real potential food consumers whose needs are to be met rather a range of individuals.So, (AI) data gather tool can record every food consumer profile and every can be factual or behavioral food consumption. A factual food customer profile consists of a set of characteristics for (AI) big data gather record, e.g. demographic information, such as food customer name, gender, birth date, when a behavioral food customer profile consists of what the food customer is actually doing and is usually derived from (AI) digital transactional data gather record.

Artificial Intelligence Big Data Gathering Consumer Behavior Prediction

Author : Johnny Ch Lok
Publisher : Independently Published
ISBN 13 : 9781723987021
Total Pages : 734 pages
Book Rating : 4.9/5 (87 download)

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Book Synopsis Artificial Intelligence Big Data Gathering Consumer Behavior Prediction by : Johnny Ch Lok

Download or read book Artificial Intelligence Big Data Gathering Consumer Behavior Prediction written by Johnny Ch Lok and published by Independently Published. This book was released on 2018-09-24 with total page 734 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding food industry marketing communication ( pull marketing communication strategy) In food industry, it needs have an efficient marketing communication strategy in order to the food providers can persuade their food consumers to choose to buy their food easily. Firstly, the food provider needs to understand the global consumer's prefence to find how any why to persuade they to choose to buy their food products. It is important to develop marketing communication strategies to solve challenges and find or seek opportunities in the communicaion process between the food providers (manufacturers) and its food retailers, food wholesalers ( supermarkets, food stores). In its communication marketing strategy, it needs to consider two channels: The first channel is supply chain development and management channel. The food supplier ( manufacturer) needs to learn how to manage its differene kinds of food supply chain, learn how to manage its food quality and food transportation logistics methods and learn how to communicate to its food retailers or food wholesalers how to help it to sell its different kinds of food to let consumers to buy attractively. The another channel is that it needs to learn how drive food consumer behavioral consumptionand learn hoe to predict why whose consumption behavioral change. Hence, the food supplier ( manufacturer) needs to learn how to communicate with its food retailers and food wholesalers to know how any why its food consumers' choices to but its foods behavioral change. It concerns that it needs to communicate with them to learn how and why its old food consumers' taste change, researchs and builds new food product brand development as well as learns how to achieve efficient marketing communication strategy and point of sale strategies. Finally, the food supplier ) manfacturer) will gather all data from there both channels to brings all data together to implement strategy revisited and revised the weaknesses and keep strengths in order to find the most useful solvable method to attract new potential food consumers to choose to buy to food or keep its old consumers to continue to choose to buy its food. Hence, one efficient marketing communication strategy which can represent the " PROMOTION" element of the marketing mix. Such on this food industry case, food marketing is all about food selling and communicating ideas be they to buy a good taste of food or good food salespeople service or take notice of a publis health apeal ( e.g. eat fruit and vegetabl). None of this is possible without a good and effective communication strategy between the food supplier ( manufacturer) and its food retailers or food wholesalers. In many food and agricultural markets, the food and agriculture suppliers ( producers and supply chain/ channel partners, it has become increasingly difficult to differentiate between food or agricultural product offerings. So, the number of available and visable positioning opportunities also diminishes. So, it implies that efficient communication strategy can assist them to create long-life marketing communication opportunities to promote their any agriculturl food success. Some of the key roles that promotion can play in food marketing include as below:

Artificial Intelligence Consumer Behavioral Predictive Methods Comparision

Author : Johnny Ch LOK
Publisher :
ISBN 13 : 9781791310776
Total Pages : 555 pages
Book Rating : 4.3/5 (17 download)

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Book Synopsis Artificial Intelligence Consumer Behavioral Predictive Methods Comparision by : Johnny Ch LOK

Download or read book Artificial Intelligence Consumer Behavioral Predictive Methods Comparision written by Johnny Ch LOK and published by . This book was released on 2018-12-09 with total page 555 pages. Available in PDF, EPUB and Kindle. Book excerpt: The challenges of (AI) big data gather shapingthe future of retail for consumer industriesAnother challenge of (AI) big data gather is that how to shape the consumer behavior to let business owner to feel or know or predict. It means that how it express it's conclusion or opinion for every consumer behavior after it had gather all big data in any data gather period, e.g. three months, half year or one year consumer shopping model data gather period.Because every kind of industry, consumers will continue to demand price and quality change , with a wide range of convenient fulfilment options among of different kinds of products or services supply. Overall, the (AI) big data gather procedure gives opinion concerns every time retail experience will become more exciting, simple and convenient, depending on the consumer's ever-changing needs. So, I believe that (AI) big data gather every conclusion or result will be different, due to consumer's price and quality demand will often change to every kind of product or service supply in retail industry. So, how to shape (AI) big data gathering's analytical conclusion or result more clear. I shall recommend organizations need to build great understanding of and a stronger connection to increasingly empowered consumers before they plan and implement how to apply (AI) big data gather tool to predict consumer behavior as below:Firstly, (AI) is empowered by technology, the consumer is redefining value. The traditional measures of cost, choice and convenience are still relevant, but not control and experience are also important. Globally, consumers have access to more than 2 billion different products choice by a wide range of traditional competitors and dynamic new entrants, all experimenting with new business models and methods of client engagement. As choice increases, loyalty becomes more difficult familiarity and the consumer becomes more empowered. Businesses will have no choice and constantly innovate and disrupt themselves by meeting new technologies of high standards and expectations of consumers. So, (AI) data gather tool will need to follow different target group of consumers' needs to follow their different kinds of product design or style choice preferable to gather data in order to conclude the different target groups of consumer behavior to give opinion more clear and accurate to let businessmen to understand more clear how its customers' behavioral choice trend in the future half month, even to two years period.Secondly, businessmen need to adopt changing technologies rapidly. Technology will be the key driver of this retail industry. Industry participants will only success if they have a clear prediction to focus on how to using technology to increase the value added to consumers. They must , however, do so will I realistic assessment of their costs and benefits. Hence, (AI) big data gather technological tools will need to design to help them to gather data efficiently by these ways, such as the internet of things ( IOT), artificial intelligence (AI) machine learning, augmented reality (AR)/virtual reality (VR), digital traceability. So, future (AI) big data gather tool are predicted to be most influential customer behavioral positive emotion changing tool for retail , due to their widespread applications , ability to drive efficiencies and impact on labor in order to impact consumer behavior changing effort from negative emotion to positive.Thirdly, (AI) big data gather tool is an advanced data science of consumer behavior predictive tool. Businesses will have to bring the journey from simply collecting consumer data to using it to scale and systematize enhanced decision making across the entire value chain. When focused on their business goals, industry players should not lose sight of the impact that future capabilities and transformative business models may have on society.

Big Data

Author : Amandeep Singh
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110733714
Total Pages : 254 pages
Book Rating : 4.1/5 (17 download)

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Book Synopsis Big Data by : Amandeep Singh

Download or read book Big Data written by Amandeep Singh and published by Walter de Gruyter GmbH & Co KG. This book was released on 2022-09-06 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: Imagine being able to target an audience made up of highly qualified and purchase-ready prospects and easily building them into loyal clients by anticipating their needs and hence offering true value. This is the power of big data for digital marketing. Big Data: A Roadmap for Successful Digital Marketing explores recent trends in the use of big data to predict consumer behavior, strategies to engage online customers, integration of big data with other data sources, and its applications in social media analytics, mobile marketing, search engine optimization and customer relationship management. As the marketing world moves into a data-focused future, the success of marketing efforts will be wholly based on attention to detail in data analysis and effectively acting on insights in order to implement changes that will deliver improved results. This book will help professionals succeed in their digital marketing efforts as well as provide food for thought for students and researchers in the fields of digital marketing, customer behavior and big data analytics.

Global Challenges and Strategic Disruptors in Asian Businesses and Economies

Author : Ordóñez de Pablos, Patricia
Publisher : IGI Global
ISBN 13 : 1799847888
Total Pages : 358 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Global Challenges and Strategic Disruptors in Asian Businesses and Economies by : Ordóñez de Pablos, Patricia

Download or read book Global Challenges and Strategic Disruptors in Asian Businesses and Economies written by Ordóñez de Pablos, Patricia and published by IGI Global. This book was released on 2020-09-25 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: Strategic disruptors in companies and economies, including blockchain technology, big data, and artificial intelligence, can contribute to the creation of new business opportunities, jobs, and growth. Research is needed on the impacts of these disruptors in Asia, as well as analyses on new business ecosystems and policy implications. Global Challenges and Strategic Disruptors in Asian Businesses and Economies presents a rich collection of chapters that explore and discuss the state of the art, emerging topics, challenges, and success factors in business, big data, innovation, and technology in Asia. The book explores how the internet of things, big data, and artificial intelligence can provide solutions for global challenges and companies. Including topics on digital economy, strategic management, and information technologies, this book is ideal for managing directors, general managers, corporate heads of firms, politicians, executives, entrepreneurs, academicians, decision makers, policymakers, researchers, and students looking to enhance their understanding and collaboration in business, disruptive innovation, and technology in Asia.

Demand Prediction in Retail

Author : Maxime C. Cohen
Publisher : Springer Nature
ISBN 13 : 3030858553
Total Pages : 166 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Demand Prediction in Retail by : Maxime C. Cohen

Download or read book Demand Prediction in Retail written by Maxime C. Cohen and published by Springer Nature. This book was released on 2022-01-01 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: From data collection to evaluation and visualization of prediction results, this book provides a comprehensive overview of the process of predicting demand for retailers. Each step is illustrated with the relevant code and implementation details to demystify how historical data can be leveraged to predict future demand. The tools and methods presented can be applied to most retail settings, both online and brick-and-mortar, such as fashion, electronics, groceries, and furniture. This book is intended to help students in business analytics and data scientists better master how to leverage data for predicting demand in retail applications. It can also be used as a guide for supply chain practitioners who are interested in predicting demand. It enables readers to understand how to leverage data to predict future demand, how to clean and pre-process the data to make it suitable for predictive analytics, what the common caveats are in terms of implementation and how to assess prediction accuracy.