Leveraging Artificial Intelligence in Marketing for Social Good An Ethical Perspective PMC

That is, “humans should always retain the power to decide which decisions to take” on their own or when to cede decision-making control (Floridi et al., 2018, p. 698). In general, freedom of choice and self-determination can be seen as intrinsic good or right contributing to individuals’ well-being (Burr et al., 2020). Human agency (i.e., autonomous decisions) and human oversight are focal requirements of autonomy in relation to AI applications (Morley et al., 2020). Second, the frequent occurrences of justice and fairness, non-maleficence, and privacy reflect a cautious view on potential risks of AI. Third, the more frequent references to non-maleficence as compared to beneficence imply the moral obligation to avoid any negative impact of AI and could imply a certain negativity bias. Fourth, the principle trust constitutes a critical ethical issue in AI governance.

First, utilities to be optimized are difficult to grasp and determine or differ across stakeholders (Butkus, 2020). Eventually, humans are in charge of determining to which ethical principles and human values AI applications and systems (and their utility functions) should be aligned. Besides, decisions about AI design approaches to equip AI applications and systems with ethical judgments competences have to be taken by humans. In the following section, we provide thoughts and ideas of how to align AI applications in marketing with ethical principles to promote social and environmental good. Artificial intelligence in marketing refers to the use of ML models and algorithms to quickly analyze marketing data and draw swift conclusions based on campaign details and customer behavior. The use of artificial intelligence enables marketing teams to focus on higher-level strategies, which can subsequently guide AI-driven campaigns.

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In fact, WhatsApp has highest open rate, making it the most effective channel for companies to connect with customers. Here is an example of how the Mom Store has deployed a WhatsApp Chatbot to assist their customers better. AI-powered fraud detection can detect and prevent fraud in e-commerce transactions, protecting both businesses and customers. By analysing customer data and transaction patterns, AI can detect suspicious behaviour and prevent fraudulent transactions.

Brands like KFC South Africa are using AI Image Generator technology solutions to instantly develop new campaign assets. Braze enables world-class customer engagement powered by flexible APIs, supported by enterprise-grade security and compliance. First, we expedite the information flow between disciplines by integrating insights from different fields of inquiry. Second, based on our synthesis of literature, we offer a conceptual framework to organize the outcomes of AI anthropomorphism in a tidy and concise manner.

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As long as such automation is not related to customers’ identity (Leung et al. 2018), it is easy to implement, cost-efficient, and scales up easily. Compared with the mechanical-based segmentation and the thinking-based targeting, positioning is more about speaking to customers’ hearts, typically as a positioning statement or slogan in promotional communication. Gali et al. (2017) find that tourism positioning slogans in top destinations tend to emphasize the affective component. AI segmentation is flexible, in that it can disaggregate the market into segments of one (i.e., each individual customer is a segment) and can aggregate scattered long tails into one segment. Wang et al. (2017) demonstrate that transfer learning can be used to model the tail of the distribution, by learning from the head of the distribution and transferring the learning to the data-poor tail.

Often, AI improves factors that are hard to measure, like customer experience or brand awareness. While these benefits can eventually lead to more revenue, it can be challenging to justify the cost of this investment. It bridges the gap between data and execution by instantly sifting through large data sets to identify trends and commonalities. The key to marketing and progress is to target the right consumers with the right message at the right time. AI tools can also provide insights by comparing old and new clients to teach you how to produce more regular customers.

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Thus, ethical challenges related to AI in marketing can emerge on the customer, company, and societal levels. AI marketing uses artificial intelligence technologies to make automated decisions based on data collection, data analysis, and additional observations of audience or economic trends that may impact marketing efforts. AI marketing tools use data and customer profiles to learn how to best communicate with customers, then serve them tailored messages at the right time without intervention from marketing team members, ensuring maximum efficiency.

Marketers also observe customers’ behaviors and choices, and their reactions to promotions to understand their preferences and the underlying reasons. Currently, surveys, experiments, interviews, panels, and sales data are still the major approaches for marketers to obtain data, even though the administration of these methods can be partially automated or facilitated by technology. Surveys and experimental methods tend to be more theory driven, while other methods tend to be more data driven.

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AI marketing is used for data analysis, media buying, content generation, personalization, and more. Lastly, we have image recognition software as an AI tool businesses can use to improve the customer experience. Image recognition has been around for a while, and you’ve probably experienced it on a platform like Facebook when a friend was automatically tagged in a photo you posted. For example, major retailer Macy’s launched Macy’s Image Search, an app that lets customers upload a photo of an item in order to find something similar within Macy’s inventory.

Using consumer data more effectively, for marketing campaigns, content generation and establishing quality leads ensures that organizations will achieve more accurate results, and integrate accurate predictions within their marketing strategies. The creation of hyper-personalized online experiences still remains a distant goal, often considered a pipe dream by many marketing teams. However, the momentum at which AI marketing is continually expanding brings new innovative opportunities to the table, enabling marketers to better understand customer behavior and experiences, and provide real-time solutions. AI marketing tools can help businesses improve their marketing strategies and optimize customer interactions. By leveraging the power of AI, businesses can gain valuable insights into customer behavior and preferences and create personalized experiences that drive engagement and loyalty.

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