Integration of Artificial Intelligence Marketing to Get Brand Recognition for Social Business

The purpose of this article is to conduct a detailed analysis of the integration of Artificial Intelligence (AI) marketing to get brand recognition for social business. It has been seen that AI is immensely popular with businesses these days. This article mainly focuses on the use of AI marketing elements to increase brand recognition for social businesses, which are not very well-known to consumers in Bangladesh. No research was done previously focused on the impact of these variables on Social Business. This study makes use of a quantitative research approach that includes a survey questionnaire consisting of seven-point Likert scales. Inferential statistics have been used to explain the kind of impact AI may have on brand recognition for social businesses. The authors have approached 500 respondents from 25th February 2021 to 15th March 2021 and got close to an 81% response rate, 403 responses. With the support of SPSS, the collected answers from the sample were analyzed. The results show that integration of AI marketing strategies will play a significant role in leading to increase brand awareness and recognition for social business. This research will add a new perspective in the existing literature in the field and allow the professionals to integrate AI marketing elements to achieve improved brand recognition. This study will additionally encourage establishing of more social businesses ultimately benefiting society.


INTRODUCTION
Artificial Intelligence (AI) has received noteworthy growth and interest over the years, and businesses are benefitting greatly due to the implementation of AI. AI is highly supported by entrepreneurs and consumers as well (Black and Ferolie, 2019). It is believed by many that AI has the potential to change the way marketers make strategies and the way consumers behave. AI is the imitation of human intelligence in machines, which are set to think like people and repeat their actions. Machine learning is considered a subset of AI . Social businesses are those enterprises, which have some aims to benefit society besides making profits. Social businesses investigate earning maximum profits, besides maximizing all the benefits that they can offer society. The profits earned by social businesses are used for funding that is needed for the operation of social programs (Davenport et al., 2020).
It has been found from recent studies that AI marketing is becoming a popular concept in the business world. It has also been seen that it can critically affect social businesses when it comes to social businesses achieving brand recognition. This paper aims to create awareness of the existence of social businesses, as they are not very well-known to consumers (Kong, 2017).
Although social businesses operate with a cause of benefitting society, they also must face several challenges. Several studies have shown that social businesses struggle due to the lack of funding and financial support. Most social businesses face hardships in arranging startup finance. Social businesses are held accountable for several actions as well (Richter, 2019). Some massive social businesses such as Grameen Bank in Bangladesh had faced several criticisms that they charge higher interest rates from the poor. Big Issue, another social business faced criticism for profiting off the money made by poor people besides having their source of profits. Although both the social businesses are greatly successful even today and continue doing their social activities, they also must take accountability on several occasions as questions are raised on what they are doing (Alon et al., 2020).
Some studies have also suggested that there are some challenges of AI marketing as well, which need to be taken into consideration. It needs to be implemented consciously, keeping in mind the possible challenges it comes with and how those challenges can have an impact on the organization. AI would make the businesses more updated with the latest technology and would also help improve customer engagement activities (Urban and Gaffurini, 2018).

Artificial Intelligence Marketing
Several businesses, followed by the marketing teams working with them are speedily implementing smart technological solutions to boost the efficiency in their operations, which automatically leads to an increase in customer satisfaction (Venkatesan and Lecinski, 2021). With the help of these platforms, marketers are being able to attain more comprehensive knowledge of the audience they are targeting. AI marketing is a unique concept in the business world, that is greatly achieving popularity. However, no research has been done on this field before (Conick, 2017). AI marketing has brought in a lot of benefits to businesses as it helps build customer engagement better. Elements of AI Marketing include Machine Learning, Big Data and Analytics, and AI platform solutions (Wirth, 2018). However, such advanced technology does not always come with benefits only. There are some challenges to it. Marketers need to know very well how they are implementing AI in their operations and campaigns, as the development and implementation of the AI tools are still at their initial phase (Jarek and Mazurek, 2019). These tools need to be trained to learn the goals of the organization, preferences of consumers, trends, etc. They do not know everything automatically. Privacy of data is a great concern when AI marketing is involved. Marketing teams must use consumer data ethically to avoid the risk of a negative brand image (Overgoor et al., 2019). AI marketing makes use of technologies linked to AI that help them make programmed decisions by considering the data collection, analysis, and more interpretations of the target consumers and the trends in the economy, which might influence marketing strategies. Often, AI is preferable in marketing areas that require speed (Paschen et al., 2019). AI tools make use of data and the profiles of consumers to understand the best ways to communicate with them. Once that is done, these tools also send customized messages to the consumers when the time is right, and for this to be done, marketing team members do not need to intervene at all -this, therefore, ensures the maximum amount of efficiency (Shaily, 2021). Therefore, H 1 : There is a relationship between elements of AI Marketing and Brand Recognition of Social Business.

Social Business
A social business aims to work towards a social cause. The investors that invest in social businesses do not aim to only make profits, but also benefit society besides making profits. These businesses aim to operate with the vision of value creation for society. Social businesses encourage innovation, uniqueness, and social responsibility (Schweizer et al., 2017). One of the biggest considerations made by social businesses is cost-effectiveness, which is also a great challenge for them. It is easier for social businesses to come up with marketing campaigns because their campaigns would involve tackling problems in the environment, which is a noble cause, and would easily attract the attention of the consumers. Social businesses can be carried out in any area of business, but the sectors that attain more priority to become social businesses are sectors such as healthcare, education, housing, financial services to the needy, nutrition (Ostertag, 2018).
Success for social business is not governed based on profits made. Rather, social businesses are considered successful when they can create more impact through the positive changes, they have been able to bring in. The concept of social business in Bangladesh was started by Muhammad Yunus, who wanted to overcome the challenges and lacking capitalism. This is because capitalism is focused only on making profits and ignores every other side of the business (Todaria, 2017). However, some researches have shown that social business faces a tough time when managing investments. This is because it is quite difficult to convince investors on fact that they would not be receiving returns immediately after their investment (Tate and Bals, 2018). Social businesses are also distrusted most of the time. The public raises questions on their actual intentions most of the time. Remaining true to the mission of social businesses is also a challenge for them, as they must be strongly focused on benefitting society instead of maximizing profits (Peerally, 2019). It can be said that AI marketing can help these businesses to aware customers of their intentions. Thus, H 2 : There is a relationship between elements of AI marketing and Brand Awareness of Social Business.

Brand Awareness
Brand awareness is a term used in marketing that describes the level of customer recognition of products by their names. The creation of brand awareness is an important step in the promotion of a new product or stimulating an existing brand (Foroudi, 2019). The awareness of a particular brand might also involve the qualities of the product that differentiate it from the products of the rivals. Brands that offer products and services that can maintain a higher level of brand awareness are more likely to be able to generate higher sales. When consumers are provided with choices, they are more likely to choose the product that is known by everyone over one that is not remarkably familiar (Bilgin, 2018). However, it is also highly likely that brand awareness can limit the popularity of a particular product to a particular zone, and after that, there are no more options for moving forward and creating more awareness. It is also possible that consumers are unable to relate to a brand despite it being well-known. If consumers do not feel a connection with a brand, they are likely to switch to a different brand (Shabbir et al., 2017).
If businesses are successfully able to establish brand awareness, then they have a powerful marketing strategy, which then leads consumers to develop a preference towards the brand and its products. When companies are considering product differentiation, brand awareness plays an especially important role in that aspect (Molinillo et al., 2017). This will lead to better brand recognition which is an ingredient of brand awareness. Therefore, H 3 : There is a relationship between Brand Awareness and Brand Recognition of Social Business.

Brand Recognition
Brand recognition is the term that is used to explain consumers' ability in being able to identify a specific brand by its characteristics over the competitors' brands. Brand recognition is a concept that is used by businesses in their marketing and advertising campaigns. This concept is successful when consumers are easily able to recognize the brand through cues related to the brandeither visual or auditory (Rahman et al., 2020). These cues can include logos, packaging, slogans, etc. Most companies often conduct thorough market research to determine the success of their strategies for brand recognition. A huge amount of money and a lot of time are invested by companies for their brand recognition strategies to work out successfully. For the brand recognition strategies to work out perfectly, brands need to find a way through which they can make their consumers recall their brand. Brand recognition helps companies to build the trust of their consumers (Pidhurska, 2020). However, brand recognition can be quite expensive for companies as it involves a high amount of market research. Some businesses invest in this strategy and still fail to hold their consumers and therefore the expense of this strategy is not very profitable for them (Rhie, 2019). This can also be a challenge for businesses when they are trying to come up with a different product and trying to target a different customer segment. When a brand is already recognized by the consumers in a specific way, it is quite difficult to change that perspective of consumers (Kavita and Haran, 2019). Thus, H 4 : Brand Awareness mediates that there is a relationship between elements of Artificial Intelligence (AI) Marketing and Brand Recognition of Social Business (SB).

RESEARCH METHODOLOGY
There has been no previous research on this topic, therefore, the authors cannot compare the research method for this study with any other. The research approach used by this study will be a quantitative one. The conceptual model for this study shows the independent variable -AI marketing, which has three components, the mediating variable -brand awareness, and the dependent variable -brand recognition for SE (Figure 1).
The research method most appropriate for this study was to conduct a survey. In the survey research conducted by the authors, the questionnaire was given out to the respondents. It was required for the questionnaire to be suitably constructed to conduct a survey that is considered both reliable and valid (Klaus, 2020). The research also contains some testable hypotheses. This technique is known as an interactive technique, which is applicable when a study observes two or more variables. The respondents for the questionnaire were reached through social media (Ma and Sun, 2020). Thus, the authors have used a non-probability sampling technique.

Research Approach
The approach implemented by the authors for this research is a deductive one. The focus of this research is on a quantitative analysis, which required the authors to gather primary data with the help of survey questionnaires.

Target population
The target population for this study is infinite, and the respondents are all Bangladeshi. Amidst the infinite target population, different respondents came from different backgrounds. However, since the authors had a time constraint, the survey was conducted among the friends and known people of the authors. The questionnaires were distributed to the respondents through social media.

Sampling technique
The sampling technique used by the authors was the nonprobability convenience sampling technique. In this method, there   is the possibility of the choice of respondents to be unplanned, or even unfamiliar. This sampling technique was used by the authors because the data was gathered from a target population that was available to the authors. The author reached the respondents of the survey through social media platforms such as Facebook, Whatsapp, Instagram, etc.

Sampling size
The sampling size for this research is 403. This sample size is highly approved by other researchers.

Questionnaire
The authors had established a questionnaire as a tool for the collection of data. There were 5 questions to understand the profile of the respondents and 8 survey questions in the questionnaire. Each of the survey questions was based on the variables of the study. The questionnaire was designed to analyze the impact of AI marketing on brand recognition for SB. The responses for the questionnaire were put using a Likert Scale, starting with "Strongly Agree" and ending with "Strongly Disagree." The full questionnaire is available in the Appendix.

Respondents Profile Analysis
Respondents' nationality is required to be from Bangladesh.

Reliability Analysis
Cronbach alpha is a useful statistic to calculate the reliability of multiple-question Likert scale surveys. IBM SPSS, 26 th version was used to estimate the reliability of the conducted survey. To inspect the reliability coefficient, Cronbach's alpha reliability test was conducted. The Reliability analysis is significant to test and check the scales' internal consistency in the survey (Malhotra, 2009). By taking the total sample of the study, the reliability has been measured. The reliability test exposed the Cronbach alpha's value for the 5 variables of this study to range from a minimum of 0.626 to a maximum of 0.680. Even though it is better to have an alpha value of more than 0.07 (Pallant, 2013), however, Malhotra (2009) claims that the scales are still considered reliable if there are alpha values of 0.06 or above. As one of the questions was asked in an inverted manner, those answers for that question have been reversed coded as well to maintain consistency. Thus, all the scales are found to be reliable and internally constant for this study. The overall Cronbach Alpha score came to 0.678. The outcomes of the variables are presented in the Tables 2-4:

Hypothesis Testing (via SPSS)
Bivariate and multiple regression analyses have been applied for H 1 , H 2 , H 3 , and H 4 . Five main variables have been derived from the items under the 4 hypotheses of the conceptual framework.
In the following segments, the results of all the hypotheses tests are shown. This means that the more people will be aware of the SBs the better brand recognition these companies will have. The result shows a positive relationship as the significance score of 0.000, shows that the association is significant at P < 0.01.

H 4 : Brand Awareness mediates that there is a relationship between elements of AI) Marketing and Brand Recognition of Social Business (SB).
As recognition of the importance of mediation analysis has increased, researchers have developed advanced statistical and conceptual models to investigate mediated effects (MacKinnon, 2008). To test the mediating effect of Brand Awareness in this model multiple regression analysis was performed. Brand Awareness is a mediator that explains the underlying mechanism of the relationship between AI marketing techniques (IV) and Brand Recognition of SB (DV). A significant model emerged (F4, 398 = 25.699, P < 0.005). Adjusted R square = 0.297. The significant variables that emerged from the results are shown below. The results show that the effect of AI marketing techniques on Brand Recognition still exists, but in a smaller magnitude, Brand awareness partially mediates between AI marketing techniques and Brand Recognition.

DISCUSSION OF THE FINDINGS
According to Ray, (2019), AI marketing techniques and brand recognition have a relatively strong relationship as one variable has a positive impact on the other one. Using AI for marketing means that companies are making use of advanced technology and the features that come along with it, to improve their customer handling and their interaction with their consumers. Social businesses are the type of businesses that are not very well known to the people of Bangladesh (Gentsch, 2018). However, according to the survey conducted by the authors, it has been found that people are quite intrigued by the concept of social businesses. The authors have also found that people would be willing to purchase from Social businesses if they are aware of which brands, are Social businesses. Consumers are mainly interested in being engaged with social businesses because they operate with a good cause of helping the society, besides making a profit for themselves.
The findings from this study further suggest that brand awareness and brand recognition are two elements that help one another. If brands can successfully create awareness of their existence to their desired customer segment, they can easily create recognition as well by making sure that their consumers are having a positive experience with their brand. Social businesses require both brand awareness and brand recognition, especially in a country like Bangladesh, where most people have no idea about the existence of such businesses (Folmer et al., 2018). Our sample size mostly belonged to an educated population, however, still, the responses regarding them being aware of the Social business were mixed. AI marketing techniques can have a big contribution in improving brand recognition for such businesses. Therefore, the Social businesses in Bangladesh can make use of AI marketing techniques to improve their brand awareness which partially mediates brand recognition and can also have a direct effect on brand recognition. The authors have seen that the findings from this study supporting all the hypotheses.
Brand awareness and brand recognition are causally linked to one another. Brand recognition is an ingredient of brand awareness (Stone et al., 2020). Companies need to be able to create awareness for themselves. Once the awareness has been created, recognition follows. Companies can make use of several techniques to create brand awareness. One of the biggest contributors to the creation of brand recognition is the perspective of the consumers. If consumers create a positive image of the brand in their minds, they are likely to spread a positive word for the brand and recommend the brand to other potential consumers. This positive consumer perspective can increase brand recognition. If brand awareness and recognition can be increased this, in turn, will help these Social businesses to reach more customer segments and profit. This will motivate further people to invest in social businesses in this economy.
AI marketing and brand recognition share a strong correlation between one another as seen in the findings of this study. AI marketing makes use of advanced technology as marketing tools to help brands do the marketing for their products better. AI marketing not only helps brands come up with more advanced ways to improve their promotional activities and present themselves to the consumers, but it also helps brands improve their engagements with the consumers. If brands are being able to efficiently carry out AI marketing, they can easily improve their brand recognition (Gil et al., 2020). The findings from this study further suggest that there is a strong correlation between the independent and dependent variables. However, it should be noted that all the elements of AI marketing do have a strong relationship. Nevertheless, overall, it can be said that these two variables are positively correlated to one another and that AI marketing has the potential to create brand awareness and brand recognition for social business.

Implications to managers
The findings from this research will help the managers of Social businesses understand how AI can help them achieve brand recognition better. Managers can also use the recommendations made in this paper to improve certain areas of the businesses that are preventing the brand from being recognized by the masses. This study also highlights the advantages of the implementation of AI, which would help managers understand the importance and the benefits of the integration of AI. The findings from this study, therefore, prove that the implementation of AI in Social businesses can help them achieve brand recognition and thus, increase their reach to more customer segments.

Implications to the society
If Social businesses are more known to society, it will not only be an advantage for those companies but also the society. Since social businesses operate with the cause of benefitting society, people need to be aware of their existence (Campbell et al., 2020).
The more people know about these businesses; the more support they are likely to get. If consumers support social businesses by purchasing from them, they are also contributing to the benefit of society. The information from this paper will help consumers be aware of the existence of social businesses and how these businesses work with the cause of benefitting society overall.

CONCLUSION
This study shows the impact of AI marketing on brand awareness leading to brand recognition for Social businesses. The findings from this study might be helpful to marketers who are looking to incorporate AI in their operations to achieve brand recognition for Social businesses. However, companies need to take the positive sides and the drawbacks of the integration of AI into consideration before going ahead with it (Olson and Levy, 2018). The conceptual framework has shown that brand awareness is a moderating variable that helps in the achievement of brand recognition because of the implementation of AI marketing. It can therefore be concluded that AI can be a great help for social businesses if they are trying to achieve brand recognition.

Limitations of the Study
The biggest limitation of this study is the pandemic because of which, we could not reach out to respondents out of our known circle. Moreover, this small sample came mostly from a certain age, educational background and therefore, does not reflect the whole country. The findings and information of this research needed more in-depth analysis. Due to ethical considerations that the authors have strictly followed while conducting this study, they could not get access to several resources that could have been useful for a better understanding of this study.

Scope for Further Research
The main findings from this research have created ways for several other studies on this topic to be conducted. There have been no previous studies on this topic; therefore, other researchers who can find any gaps in the findings of this study can easily conduct research that covers all the gaps that were left by this research. This paper can be incredibly useful for the concerned businesses, consumers, society, and researchers as it contains detailed information regarding AI marketing, Social business, the importance of brand awareness, and brand recognition.