Can Apply Artificial Intelligence To Predict Consumer Behavior In Business Envi PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Can Apply Artificial Intelligence To Predict Consumer Behavior In Business Envi PDF full book. Access full book title Can Apply Artificial Intelligence To Predict Consumer Behavior In Business Envi.

Can Apply Artificial Intelligence Predicts Consumer Behavior in Business Environment

Can Apply Artificial Intelligence Predicts Consumer Behavior in Business Environment
Author: Johnny Ch Lok
Publisher: CA Apply Artificial Intelligen
Total Pages: 572
Release: 2018-09-09
Genre: Business & Economics
ISBN: 9781720183808

Download Can Apply Artificial Intelligence Predicts Consumer Behavior in Business Environment Book in PDF, ePub and Kindle

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


Can Apply Artificial Intelligence to Predict Consumer Behavior in Business Envi

Can Apply Artificial Intelligence to Predict Consumer Behavior in Business Envi
Author: Johnny Ch lok
Publisher:
Total Pages: 376
Release: 2018-09-13
Genre:
ISBN: 9781727337785

Download Can Apply Artificial Intelligence to Predict Consumer Behavior in Business Envi Book in PDF, ePub and Kindle

In my this book first part, I concentrate on indicate whether any artificial intelligence (AI) tools will be one kind of good consumer behavioral prediction method to be choose to apply to predict consumer behaviors. I shall indicate some examples, cases to give reasonable evidences to analyze whether (AI) tools will be one kind suitable tool to be applied to predict when and how consumer behavioral changes. If (AI) can be one kind tool to attempt to be applied to predict when and how consumer behavioral changes. Will it replace other kinds of methods to predict consumer behaviors? Does it have weaknesses to be applied to predict consumer behaviors, instead of strengths? Can it be applied to predict consumer behaviors depending on any situations of only some situation? Finally, I believe that any readers can find answers to answer above these questions in this book. In my this book second part, I shall explain why and how human can possible apply (AI) tool to predict consumer individual emotion. I shall indicate case studies to explain how consumer individual better or worse emotion how to influence whose consumption behavior in different situation. Finally, I shall indicate evidences to conclude how and why (AI) tool that can be used to predict consumer individual emotion and it will have direct relationship to influence consumption behavior, as well as how (AI) tool can assist businessmen to judge whether what reasons case the customer does not choose to buy its product, it is possible because the product high price factor, poor product quality or poor staff service performance or attitude etc. different factors to influence the consumer decides to choose to buy the other product consequently, when the (AI) tool can confirm consumer has good or bad emotion to judge what factors are the causes his decision making at the moment. Readers can understand why and how (AI) tool can be attempt to be applied to predict customer emotion and it can influence positive or negative consumption behavior to the product clearly in this part. This book third part has these two research questions need to be answered?(1) Can apply (AI) learning machine as well as micro and macro economic methods predict consumer behavioral changing?(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? The part indicates whether micro and macro economic methods can be attempted to apply to predict when, how and why consumer behavioral changing for every kind of different business. The second part indicates whether artificial intelligence can be attempted to apply to predict when, how and why consumer behavioral changing for every kind of different business.


Artificial Intelligence Big Data Gathering Predicts Consumer Behavior

Artificial Intelligence Big Data Gathering Predicts Consumer Behavior
Author: Johnny Ch LOK
Publisher: Independently Published
Total Pages: 488
Release: 2018-09-19
Genre:
ISBN: 9781723837647

Download Artificial Intelligence Big Data Gathering Predicts Consumer Behavior Book in PDF, ePub and Kindle

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.


Artificial Intelligence Predicts Consumer Behavioral Tool ?

Artificial Intelligence Predicts Consumer Behavioral Tool ?
Author: Johnny Ch Lok
Publisher: Createspace Independent Publishing Platform
Total Pages: 64
Release: 2018-06-03
Genre:
ISBN: 9781720723516

Download Artificial Intelligence Predicts Consumer Behavioral Tool ? Book in PDF, ePub and Kindle

In my this book, I concentrate on indicate whether any artificial intelligence (AI) tools will be one kind of good consumer behavioral prediction method to be choose to apply to predict consumer behaviors. I shall indicate some examples, cases to give reasonable evidences to analyze whether (AI) tools will be one kind suitable tool to be applied to predict when and how consumer behavioral changes. If (AI) can be one kind tool to attempt to be applied to predict when and how consumer behavioral changes. Will it replace other kinds of methods to predict consumer behaviors? Does it have weaknesses to be applied to predict consumer behaviors, instead of strengths? Can it be applied to predict consumer behaviors depending on any situations of only some situation? Finally, I believe that any readers can find answers to answer above these questions in this book.


Can Apply Artificial Intelligence to Predict Consumer Behavior in Business Environment

Can Apply Artificial Intelligence to Predict Consumer Behavior in Business Environment
Author: Johnny Ch LOK
Publisher:
Total Pages: 377
Release: 2018-09-13
Genre:
ISBN: 9781720285090

Download Can Apply Artificial Intelligence to Predict Consumer Behavior in Business Environment Book in PDF, ePub and Kindle

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


Can Apply Artificial Intelligence to Predict Consumer Behavior: In Any Business Environment ?

Can Apply Artificial Intelligence to Predict Consumer Behavior: In Any Business Environment ?
Author: Johnny Ch Lok
Publisher: Can Apply Artificial Intellige
Total Pages: 362
Release: 2018-09-09
Genre: Business & Economics
ISBN: 9781720180869

Download Can Apply Artificial Intelligence to Predict Consumer Behavior: In Any Business Environment ? Book in PDF, ePub and Kindle

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


Artificial Intelligence Predicts Consumer Behavioral Tool Business Journey

Artificial Intelligence Predicts Consumer Behavioral Tool Business Journey
Author: Johnny C. H. Lok
Publisher: Independently Published
Total Pages: 62
Release: 2018-11-21
Genre:
ISBN: 9781790161348

Download Artificial Intelligence Predicts Consumer Behavioral Tool Business Journey Book in PDF, ePub and Kindle

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


How Ai Predicts Consumer Behavior in Economic Environment

How Ai Predicts Consumer Behavior in Economic Environment
Author: Johnny Ch LOK
Publisher:
Total Pages: 75
Release: 2020-09-10
Genre:
ISBN:

Download How Ai Predicts Consumer Behavior in Economic Environment Book in PDF, ePub and Kindle

It seems that in future, (AI) machine learning will allow search to evolve even further. Search engineers will deliver refined recommendations to their business users and use less human input to predict consumers' needs. For IBM computer example, it indicated 90% of the data that exists today has been created in the last two years. This huge explosion of data gives brands the opportunity to quickly spot and react to the latest trends, fashion and fads among its clients and potential clients. This will allow companies to better engage with younger consumers, who gain influence access to the latest trends, and use the brands. They associate with to help define who they are as individuals. Thus, brands have to identify and make use of them before consumers move on, but the vast quantity of data available makes. This a resource-intensive task. For next example, Lesara, a based online clothes store, uses this machine learning to inform its product decision often gathering information from internal and external sources. When its trends -spotting shoes. Lesara has a range of over 20 styles and sells hundreds of pairs a day. It focus on giving consumers, the very latest trends allow Lesara to develop on average of 50,000 new items each year. It compared to 11,000 old items each year. Thus, (AI) brain seems to human brain to own analytical ability to predict consumer behaviors. For another example, Lesara is one online clothes store, uses machine learning decisions after gathering information from internal and external sources. One of its most popular products, shoes with LED started life when its trend spotting software flagged up a blogger wearing similar shoes. Now Lesara has a range of over 20 styles and sells hundreds of pairs a day. Its focus on giving consumers the very latest trends allows Lesara to develop an average of 50,000 new items each year, compared to 11,000 for its competitor Lara. it seems (AI) machine learning can help Lesara business to predict what kinds of shoes design or style that shoe consumers will prefer choose to buy in future shoe market trend. Thus, Lesara can predict shoe consumers' taste successfully and it can manufacture many attractive style of shoes. (AI) machine learning can gather global past shoe consumer's shoe shopping experiences, then analyzes to make conclusion to give lesara recommendation successfully. This will make the experience more enjoyable for shoe consumers and allow Lesara to advert whose different new style or design of shoes to deliver them move relevant messages by understanding the context of the experience.However, (AI) machine learning will have this risk who manufacturers need to concern if they applied this technology to predict consumer behavior. It is on sample consumers' privacy issue, in order to avoid complaint chance occurrence. However, machine learning can tie this data together to identify which f the billions of devices are being used by individual consumers. This helps brands understand how consumer engagement and actions can be attributed to different messages in different contexts and at different time. So, machine learning can help brands to build confidence to promote their products by any advertisement channels. When, this new (AI) machine learning technology can conclude how to design their products to be the most attractive, due to it has more accurate to predict consumer behaviors to compare human themselves prediction judgement effort. It seems that (AI) machine judgement effort is more accurate to compare to human judgment effort.


Marketing Information and Artificial Intelligence Customer Psychological Predictive: Methods Difference

Marketing Information and Artificial Intelligence Customer Psychological Predictive: Methods Difference
Author: Johnny Ch Lok
Publisher: Independently Published
Total Pages: 254
Release: 2019-01-15
Genre: Business & Economics
ISBN: 9781794160682

Download Marketing Information and Artificial Intelligence Customer Psychological Predictive: Methods Difference Book in PDF, ePub and Kindle

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).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:


Artificial Intelligence Predicts Consumer Behaviors

Artificial Intelligence Predicts Consumer Behaviors
Author: John Lok
Publisher: Independently Published
Total Pages: 78
Release: 2021-09-10
Genre:
ISBN:

Download Artificial Intelligence Predicts Consumer Behaviors Book in PDF, ePub and Kindle

To apply (AI) learning machine technology to understand customer online purchase behavior, it will raise business e-commerce successful chance: For example, (AI) learning machine can help businesses to gather data to analyze to determine whether short-term or long-term signals in the online consumer behavior that indicate higher purchase intents to let every online business to know. (AI) learning machine can find that online users with long-term purchasing intent tend to save and click through on more content. However, as online users approach the time of purchase their activity becomes more topically focused and actions shift from saves to searches from online consumption channel. Then, (AI) learning machine will further find that the brand product purchase signals in online behavior can exist weakness before an online purchase is made and can also be traced across different online purchase categories. Finally, (AI) learning machine synthesize these insights in predictive models of online user purchasing intent to the brand of product. Taken together, it's work identifies a set of general principles and signals that can be used to model online user purchasing intent across many online content discovery applications. Thus, (AI) learning machine can help online businesses to gather any online users' click online behaviors data to judge whether there are how many online users will choose to find their online business websites to make final decisions to buy their products from online channels. Then, it will give opinions to help the online businesses to let it to judge whether what are the important website factors will help its online business to attract many online consumers, e.g. designing unattractive website issue, online unattractive product photos issue, unclear website color issue, unclear website advertisement message, contents and words impressions issue, lacking image movement frequent attractive seeing issue etc. different website factors. Thus, online digital channel will be one good choice to apply (AI) learning machine to help businesses to predict consumer behaviors.