Using Artificial Intelligence to increase customer trust in Beverages company

Running head: AI IN BEVERAGE COMPANIES 1

AI in Beverage Companies

Introduction and Methodology

Table of Contents

Introduction ………………………………………………………………………………………4

Methodology...................................................................................................................................6

Action Research..............................................................................................................................8

References ………………………………..………………………………….……….………….11

List of Figures

Figure 1. Fuzzy Logic ……………………………………............................................................9

This particular research proposal aims to emphasize over showing how to increase customer trust in beverage industry. The primary utilization of innovative technology in this aspect is artificial intelligence in beverage industry. In this current trend of industry, use and application of artificial intelligence is most important for transforming the business as of in 2017 (Galanakis, 2016). It is stated that with application of artificial intelligence in market, the beverage industry has a major tendency of growing up to $5.05 billion by 2020. This is meant to be a significant opportunity for food and beverage business to harness its potential, improve the service, and optimize the current process along with increasing number of customers with better experience. There are some examples of product and organizations that have implemented artificial intelligence in operation and business (Hemalatha, 2012). “Hello Egg” is a product that started its journey at CES 2017; it is AI-powered ‘home cooking sidekick’ empowers individuals for healthy appetite.

This particular study is to be conducted under separate sections with iteration-based implementation. This study has to be followed with suitable mythology of action research. Action research is stated as a combination of some steps alongside the method to incorporate implementation of artificial intelligence in beverage industry. Furthermore, the literature review is included for showing prior studies and how these studies are essential for depicting the quality of study to be dealt with. Review of literature is important to encompass examples of beverage companies those have already implemented artificial intelligence in their business. These industries and their mode of operation will pinpoint the advantages of incorporating artificial intelligence in their business. Furthermore, the proposal part is segmented under four iterations of implementation and how to improve customer trust in this aspect. Finally, the study will provide learnt lessons for realizing the limitations and future scope of the study.

As per some studies, customers are eager to know what kind of help the industries could offer in terms of food and beverage. The previous study shows that 77% of the US and UK customers want the technology for offering suitable plans for cooking. The customers have proper appetite for application of AI in food and beverage industry (Leong et al., 2015). In terms of beverage industries, the production and manufacturing of the process should implement artificial intelligence to increase customer trust. Customers should expect suitable services in beverages such as coke, soft drinks, beer, and other health drinks. They anticipate and imagine their services should be automatic and instant with serving products within minutes (Galanakis, 2016; Hemalatha, 2012). In other sectors such as food, banking, retail; the implementation cost of artificial intelligence is quite low.

Some brands and industries are utilizing artificial intelligence-powered machine, robots, and humanoids for reaching more customers. These artificial intelligence-powered robots follow individual, personal, physiological and behavioral factors of customers. In terms of food and beverage industry, the AI-powered mechanical bots are effective with storing personal preference data for beverages. Some beverage industries and brands use AI to integrate flavor profiler for every customer (Saglietto et al., 2016). Artificial intelligence is supported with cognitive engine to cater customer needs and their best-suited preference of flavor profile of beverages. In terms of customer choice, their preference should be considered as primary in any industry.

Methodology

Action research explains two sections: one is "activity," and another part is "research" that connections it together. Activity inquire about tasks are by and large situational based interesting, yet there are components in the strategies that can be utilized by different scientists in various conditions. It involves completing deliberate request as systems towards grabbing enhance their practices. These upgrades help in better working conditions and in addition working situations. Activity research is of two sorts one is contemplating concerning, and other is contribution of individuals. Masterminding every single objective amid the examination procedure is an imperative part of the procedure. Management activity looks into aides in achieving the wanted changes.

Action research is utilized as a part of an existent circumstance, and its most vital concentration is on real understand inconveniences. The beverage industry assumes an essential part in the formation of information distribution centers while guaranteeing that the varieties in information bits of knowledge and examples can be broke down. The beverage industry procedure gives the information a mapping that is good, despite the fact that it might have started from heterogeneous sources. Heterogeneous information might be difficult to examine utilizing any projects inside an association, subsequently denying the association the genuinely necessary business knowledge that can be gotten from such information investigation handle. The exploration is situated inside a predefined authentic and monetary setting of the associations that are incorporated into the accumulation of information. In gathering information, different techniques are utilized, for example, reviews from the customers of beverage industry, perceptions on the exercises of the clients, the utilization surveys to accumulate information from different sources, and in addition the data gave by beverage industry in regards to the utilization of the beverage industry and information mix by their clients.

Step 1

Firstly, in beverage industry, The underlying stage comprises of an examination of the information distribution center methodology and documentation of qualified information sources (Srikanth, 2013). Though the particular subset of the records distribution center, have perceived the impression and were scattered by their individual providers.

Step 2

Amid the prerequisite and examination arrange, the candidates are included in information stores. The way the choice is taken cannot be completely mechanized, for instance, our own insight prescribes that the records fabulousness and the attainable quality of the sources assumes a noteworthy part in this sort of choice. The recommendations a rich arrangement of geologies like procedures at line smooth on information, mix of information from various outlined, semi-organized or ill defined frameworks, planning of information activity.

Step 3

Amid this stage, the data is outlined, and a physical model is created which incorporates executable code. Though the physical model is reliant on the particular usage innovation for actualizing the information incorporation streams. Along these lines, a physical model for beverage industry would vary from one for collected data given the distinctive capacities of these beverage industry.

Action Research:

The Methodology for making the AI for the beverage company is action research. Action research is a method of researching about the actions to be done in order to get the project done in the way it is aspired. The Action research will consist of various stages. They are

1. Primary research of requirements

2. Secondary research of requirements

3. Tertiary research of requirements

1. Primary research of requirements:

Primarily the requirements of the company to make the AI should be listed. The aim and the results that are expected of the research should be documented. The stake holders of the project and the duties of the stake holders should be listed and the deployment should be done in this phase. The actual research starts in secondary research.

2. Secondary research of requirements:

Secondary research consists of the flow of functions which should be in the AI. A concept called as fuzzy logic is used in this phase. Fuzzy logic is a method which acts similar to the human thinking. The logic consists of the controls which are formulated by the project makers which can direct the AI to function in the way needed. The rules which are to be followed by the AI are prescribed here and the fuzzifier module will assign the logic an make the AI to think in the way of human thinking. The rules with the intelligence module will add to this logic and make the decisions made by the AI very human making. The defuzzifier will make the software give an output which is delivered to the customer. The customer then will have the trace of his / her pattern of consumption of drinks and the rise of levels of minerals in the body . At later stages of research such as tertiary stage, advanced requirements of the AI also will be added. A picture which shows the fuzzy logic is shown below.

Picture is retrieved from

https://www.tutorialspoint.com/artificial_intelligence/artificial_intelligence_fuzzy_logic_systems.htm

Fuzzy Logic:

Fuzzy Logic is a combinations of patterns which will automatically take decisions which are realistic. The making of fuzzy logic consists of various steps. They are :

• Collection of samples of drinks

• Collection of patterns of levels in human body

• Correlation

Collections of samples of drinks will consists of testing the drinks for the formula of the drink and the procedure in which the drink is made until the final stage. The amount of artificial colors, the amount of soda, the amount of water and the amount of carbon in the drinks are documented.

Collection of patterns of levels of sugar, minerals in human body have to be done. This can make it easy to know how much amount of drinks can be taken by an average healthy human being. The average levels can be taken from the medical statistics from the world health organization.

Correlation of both the aforementioned collections should be made in this phase. This gives an output which can compare and decide the output according to the statistics.

Tertiary Research :

The tertiary research is about how to make the customer know about this details and the useful information. The online users can easily get the offer by logging into their accounts in the beverage company website customer log in and enter their information such as age, height and weight. They also have to give information about number of drinks they had in the week and also the gap of time. This gives them the result of if they can drink the drink they have ordered, the quantity they have ordered and the AI will also suggest a better drink which can be drunk considering the person's inputs.

Galanakis, C. M. (Ed.). (2016). Innovation Strategies in the Food Industry: Tools for Implementation. Academic Press.

Hemalatha, M. (2012). Market basket analysis–a data mining application in Indian retailing. International Journal of Business Information Systems, 10(1), 109-129.

Leong, L. Y., Hew, T. S., Lee, V. H., & Ooi, K. B. (2015). An SEM–artificial-neural-network analysis of the relationships between SERVPERF, customer satisfaction and loyalty among low-cost and full-service airline. Expert Systems with Applications, 42(19), 6620-6634.

Saglietto, L., Fulconis, F., Bédé, D., De Almeida Goes, J., & Forradellas, R. (2016, April). Wine industry supply chain: international comparative study using social networks analysis. In Supply Chain Forum: An International Journal (Vol. 17, No. 2, pp. 55-67). Taylor & Francis.