Ai Impacts In Digital Consumer Behavior

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AI Impacts in Digital Consumer Behavior

Author : Musiolik, Thomas Heinrich,Rodriguez, Raul Villamarin,Kannan, Hemachandran
Publisher : IGI Global
Page : 392 pages
File Size : 45,7 Mb
Release : 2024-03-04
Category : Business & Economics
ISBN : 9798369319192

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AI Impacts in Digital Consumer Behavior by Musiolik, Thomas Heinrich,Rodriguez, Raul Villamarin,Kannan, Hemachandran Pdf

In the ever-evolving landscape of digital innovation, businesses grapple with the challenge of deciphering dynamic consumer behavior. AI Impacts in Digital Consumer Behavior is a pioneering exploration tailored for academic scholars seeking insights into the profound influence of artificial intelligence on consumer dynamics. As businesses strive to harness the potential of data, this book serves as a beacon, offering a comprehensive understanding of the intricacies involved in tracking, analyzing, and predicting shifts in consumer preferences. This groundbreaking work not only identifies the complexities posed by the rapidly changing digital landscape but also presents a solution-oriented approach. It unveils a theoretical framework and the latest empirical research, providing scholars with a toolkit of concepts, theories, and analytical techniques. With a multidisciplinary focus on behavioral analysis, the book equips academic minds with the knowledge to navigate the challenges of the digital age. Furthermore, it addresses the ethical dimensions and ethic considerations associated with the accelerating pace of consumer behavior analysis, shedding light on the responsible use of AI technologies.

Enhancing and Predicting Digital Consumer Behavior with AI

Author : Musiolik, Thomas Heinrich,Rodriguez, Raul Villamarin,Kannan, Hemachandran
Publisher : IGI Global
Page : 464 pages
File Size : 55,5 Mb
Release : 2024-05-13
Category : Business & Economics
ISBN : 9798369344545

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Enhancing and Predicting Digital Consumer Behavior with AI by Musiolik, Thomas Heinrich,Rodriguez, Raul Villamarin,Kannan, Hemachandran Pdf

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.

Enhancing and Predicting Digital Consumer Behavior with AI

Author : Thomas Heinrich Musiolik,Raul Villamarin Rodriguez,Hemachandran Kannan
Publisher : Business Science Reference
Page : 0 pages
File Size : 40,8 Mb
Release : 2024-04-12
Category : Business & Economics
ISBN : 9798369344538

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Enhancing and Predicting Digital Consumer Behavior with AI by Thomas Heinrich Musiolik,Raul Villamarin Rodriguez,Hemachandran Kannan Pdf

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. Through multidisciplinary research and practice, specifically focusing on behavioral analysis, the book equips executives, entrepreneurs, marketers, and data analysts with the tools to make informed decisions that drive business success. Enhancing and Predicting Digital Consumer Behavior with AI goes beyond immediate challenges, identifying future trends companies can leverage to develop new products and businesses. It also addresses the ethical implications of rapidly advancing technologies in consumer behavior analysis. 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.

Artificial Intelligence Influences: Marketing Strategy

Author : Johnny Ch Lok
Publisher : Independently Published
Page : 400 pages
File Size : 43,9 Mb
Release : 2019-03-27
Category : Business & Economics
ISBN : 1091760241

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Artificial Intelligence Influences: Marketing Strategy by Johnny Ch Lok Pdf

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.

Strategic Innovative Marketing and Tourism

Author : Androniki Kavoura,Efstathios Kefallonitis,Apostolos Giovanis
Publisher : Springer
Page : 1330 pages
File Size : 55,6 Mb
Release : 2019-07-03
Category : Business & Economics
ISBN : 9783030124533

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Strategic Innovative Marketing and Tourism by Androniki Kavoura,Efstathios Kefallonitis,Apostolos Giovanis Pdf

This book covers a very broad range of topics in marketing, communication, and tourism, focusing especially on new perspectives and technologies that promise to influence the future direction of marketing research and practice in a digital and innovational era. Among the areas covered are product and brand management, strategic marketing, B2B marketing and sales management, international marketing, business communication and advertising, digital and social marketing, tourism and hospitality marketing and management, destination branding and cultural management, and event marketing. The book comprises the proceedings of the International Conference on Strategic Innovative Marketing and Tourism (ICSIMAT) 2018, where researchers, academics, and government and industry practitioners from around the world came together to discuss best practices, the latest research, new paradigms, and advances in theory. It will be of interest to a wide audience, including members of the academic community, MSc and PhD students, and marketing and tourism professionals.

Artificial Intelligence along the Customer Journey

Author : Ada Maria Barone,Emanuela Stagno
Publisher : Springer Nature
Page : 132 pages
File Size : 51,7 Mb
Release : 2023-12-19
Category : Business & Economics
ISBN : 9783031487927

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Artificial Intelligence along the Customer Journey by Ada Maria Barone,Emanuela Stagno Pdf

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.

Artificial Intelligence Consumer Behavioral Predictive Methods Comparision

Author : Johnny Ch LOK
Publisher : Unknown
Page : 555 pages
File Size : 44,8 Mb
Release : 2018-12-09
Category : Electronic
ISBN : 179131077X

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Artificial Intelligence Consumer Behavioral Predictive Methods Comparision by Johnny Ch LOK Pdf

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.

Impact of Digital Transformation on the Development of New Business Models and Consumer Experience

Author : Rodrigues, Maria Antónia,Proença, João F.
Publisher : IGI Global
Page : 347 pages
File Size : 44,5 Mb
Release : 2022-03-11
Category : Business & Economics
ISBN : 9781799891819

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Impact of Digital Transformation on the Development of New Business Models and Consumer Experience by Rodrigues, Maria Antónia,Proença, João F. Pdf

In a highly competitive market, digital transformation with internet of things, artificial intelligence, and other innovative technological trends are elements of differentiations and are important milestones in business development and consumer interaction, particularly in services. As a result, there are several new business models anchored in these digital and technological environments and new experiences provided to services consumers and firms that need to be examined. Impact of Digital Transformation on the Development of New Business Models and Consumer Experience provides relevant theoretical and empirical research findings and innovative and multifaceted perspectives on how digital transformation and other innovative technologies can drive new business models and create valued experiences for consumers and firms. Covering topics such as business models, consumer behavior, and gamification, this publication is ideal for industry professionals, managers, business owners, practitioners, researchers, professors, academicians, and students.

Convergence of Human Resources Technologies and Industry 5.0

Author : Kumar, Pawan,Kumar, Sunil,Verma, Rajesh,Dadwal, Sumesh
Publisher : IGI Global
Page : 386 pages
File Size : 51,7 Mb
Release : 2024-04-29
Category : Business & Economics
ISBN : 9798369313442

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Convergence of Human Resources Technologies and Industry 5.0 by Kumar, Pawan,Kumar, Sunil,Verma, Rajesh,Dadwal, Sumesh Pdf

Through a combination of rapid technological advancement and the ongoing digital revolution, the role of Human Resources (HR) in shaping organizational trajectories has seen unprecedented growth. The amalgamation of digital HR technologies and the advent of Industry 5.0 pose both exceptional opportunities and formidable challenges, especially for developing economies grappling with resource constraints and skill gaps. These nations stand at a crossroads, where leveraging digital HR technologies becomes imperative for bolstering their competitive edge in the global arena. The book Convergence of Human Resources Technologies and Industry 5.0 undertakes a comprehensive exploration of the impacts, implementation, and repercussions of digital HR technologies within the framework of Industry 5.0 in developing economies. Bridging the gap between theory and practice, it employs a comprehensive approach encompassing theoretical frameworks, empirical investigations, and practical insights from both academia and industry. By offering tangible takeaways, and approaches, it equips readers to adeptly harness the power of digital HR technologies, enabling organizations to thrive in the era of Industry 5.0. Designed for HR professionals, executives, managers, researchers, policymakers, and students, this book delves into critical topics such as understanding the notion of Industry 5.0 in developing economies, exploring the transformative potential of digital HR technologies, and addressing challenges associated with their implementation.

Artificial Intelligence Big Data Gathering How Impacts Consumer Behavior

Author : Johnny Ch LOK
Publisher : Independently Published
Page : 572 pages
File Size : 45,5 Mb
Release : 2018-09-21
Category : Electronic
ISBN : 1723901040

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Artificial Intelligence Big Data Gathering How Impacts Consumer Behavior by Johnny Ch LOK Pdf

How to apply online psychological advertising method to predict passenger behavioral consumption?Online advertising can give relevance information to represent the similarity between advertisement and queries. These existing online advertisement works mainly focused on interpreting advertisements clicks in term of what consumers seek. ( i.e. relevance information) and how consumers choose to watch TV or magazine or online advertisement etc. from different promotion media. ( historically to know the product is selling on the market through advertising information). However, few of manufacturers or sellers attempted to understand why consumers chose to watch the advertising from TV or magazine or internet etc. different media.Why can MTR can choose online advertisement to predict passenger behavior? Online Advertisement can be as a commercial search engine for manufacturers or sellers to gather data to concern how behavioral consumption is. The online advertisement's each observations motivate who to systemically model to test what each consumer individual psychological desire in order for a precise prediction on behavioral consumption after online advertisement promotion from internet media.Today, internet is one kind of effective psychological advertising promotion method. For example, an online advertisement system, sponsored search has been one of the most important business models for commercial web search engines. It generates most of the revenue of search engines by presenting to users sponsored search results, i.e. advertisements (ads), along with organic search results. To deliver the most interesting ads to the users, a sponsored search system consists of technical components, including query-to-ads matching, online click prediction for matched ads, online click probability and auction to determine the ranking, placement, and pricing of the remaining ads. To aim to attempt to predict behavioral consumption for any kinds of product sale from online advertisement media.In today's industry, generalized second price auction (GSP) is the most widely-used auction mechanism , in which the price that an advertiser has to pay depends on the predicted online click probability of the online buyers, whose own ads as well as the bid price and predicted online click probability of the ads ranked in the next position. The online sponsored search systems typically employ a machine learning model top predict the probability that an online user clicks an advertising from internet. However, in practical sponsored search system. There are many ads without adequate historical click through data, even after query levels. Then online ads can been click improved prediction accuracy to consumer individual behavioral consumption when each click is occurred to the seller individual website. For example, online ads, such as : free Nike coupons ad. It shows " Go-Get_couptons.com/Nike, Download and print Nike coupons ( 100% Free)" ; another Nike-sales prices ad. It shows www.calibex.com, clothing, latest fashions and styles on sale. Buy Nike Fast!" ; another Perfume.com official site ad. It shows "www.perfume.com, 10,000 + brand name perfumes and colognes-up to 80% off retail!" ; another Luxury English Perfume Ad. It shows " www.florislondon.com, shop online for luxury perfumes for men, women and the home". Above of these are example online ads. For two queries, "Nike" and "Perfume" , and two ads under the same query field similar relevance to the query.

Digital Technologies for a Resource Efficient Economy

Author : Ordóñez de Pablos, Patricia
Publisher : IGI Global
Page : 346 pages
File Size : 52,9 Mb
Release : 2024-05-06
Category : Business & Economics
ISBN : 9798369327517

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Digital Technologies for a Resource Efficient Economy by Ordóñez de Pablos, Patricia Pdf

In an era marked by escalating environmental concerns and the imperative for sustainable development, a pressing challenge looms large: the urgent need for transitioning towards circular and climate-neutral economies. As industries grapple with the complexities of achieving these critical milestones, Digital Technologies for a Resource Efficient Economy explores innovative conceptual frameworks, case studies, and empirical studies, seeking to unravel the relationship between clean technologies, digital innovation, and knowledge management. Positioned at the intersection of academia and real-world solutions, its insightful exploration engages academic scholars, researchers, industry players, policymakers, and stakeholders in a dynamic discourse on the challenges, opportunities, and trends shaping the path towards a net-zero world in Asia and beyond. Targeting a diverse audience that includes professors, policymakers, corporate leaders, and students, Digital Technologies for a Resource Efficient Economy becomes a cornerstone in the exploration of artificial intelligence, circular economy, clean energy, and other pivotal topics. By combining academic rigor with practical applications, the book becomes an indispensable resource for navigating the complexities of building resilient, inclusive, and green societies. With its recommended topics spanning a global spectrum, encompassing regions from Asia to the EU, USA, Latin America, Africa, and the Gulf Region, the book takes on a truly comprehensive approach. Seamlessly weaving together the intricacies of technology, innovation, and sustainable development, this book positions itself as a crucial guide for anyone invested in shaping a future where economies thrive in harmony with the environment.

Artificial Intelligence Big Data Gathering Predicts Consumer Behavior

Author : Johnny Ch LOK
Publisher : Independently Published
Page : 488 pages
File Size : 51,7 Mb
Release : 2018-09-19
Category : Electronic
ISBN : 1723837644

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Artificial Intelligence Big Data Gathering Predicts Consumer Behavior by Johnny Ch LOK Pdf

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.

Cases on AI Ethics in Business

Author : Tennin, Kyla Latrice,Ray, Samrat,Sorg, Jens M.
Publisher : IGI Global
Page : 367 pages
File Size : 54,6 Mb
Release : 2024-05-17
Category : Business & Economics
ISBN : 9798369326442

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Cases on AI Ethics in Business by Tennin, Kyla Latrice,Ray, Samrat,Sorg, Jens M. Pdf

Organizations face a pressing challenge in today's rapidly evolving economies: navigating the ethical complexities of adopting Artificial Intelligence (AI) and related technologies. As AI becomes increasingly integral to operations, transparency, fairness, accountability, and privacy concerns are more critical than ever. Organizations need practical guidance to develop and implement AI ethics strategies effectively. Cases on AI Ethics in Business offers a comprehensive solution by examining AI Ethics through theoretical lenses and innovative practices. It provides a roadmap for organizations to address ethical challenges in AI adoption, offering insights from leaders in the field. With a focus on theory-to-practice, the book equips readers with actionable strategies and frameworks to navigate the ethical implications of AI, ensuring responsible and sustainable AI deployment.

AI and IoT for Proactive Disaster Management

Author : Ouaissa, Mariyam,Ouaissa, Mariya,Boulouard, Zakaria,Iwendi, Celestine,Krichen, Moez
Publisher : IGI Global
Page : 317 pages
File Size : 51,5 Mb
Release : 2024-05-06
Category : Computers
ISBN : 9798369338971

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AI and IoT for Proactive Disaster Management by Ouaissa, Mariyam,Ouaissa, Mariya,Boulouard, Zakaria,Iwendi, Celestine,Krichen, Moez Pdf

In our rapidly evolving digital landscape, the threat of natural disasters looms large, necessitating innovative solutions for effective disaster management. Integrating Artificial Intelligence (AI) and the Internet of Things (IoT) presents a transformative approach to addressing these challenges. However, despite the potential benefits, the field needs more comprehensive resources that explore the full extent of AI and IoT applications in disaster management. AI and IoT for Proactive Disaster Management fills that gap by examining how AI and IoT can revolutionize disaster preparedness, response, and recovery. It offers a deep dive into AI frameworks, IoT infrastructures, and the synergy of these technologies in predicting and managing natural disasters. Ideal for undergraduate and postgraduate students, academicians, research scholars, industry professionals, and technology enthusiasts, this book serves as a comprehensive guide to understanding the intersection of AI, IoT, and disaster management. By showcasing cutting-edge research and practical applications, this book equips readers with the knowledge and tools to harness AI and IoT for more efficient and effective disaster management strategies.

What Are Marketing Information and Artificial Intelligence Customer Psychological Predictive

Author : Johnny Ch Lok
Publisher : Independently Published
Page : 254 pages
File Size : 46,5 Mb
Release : 2019-01-04
Category : Electronic
ISBN : 179317184X

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What Are Marketing Information and Artificial Intelligence Customer Psychological Predictive by Johnny Ch Lok Pdf

(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.