How qualitative analysis helps food industries in understanding consumer behavior in the metaverse food world

How qualitative analysis helps food industries in understanding consumer behavior in the metaverse food world

Dr. Sima A. Hamadeh, Haigazian University, Beirut (Lebanon)

Consumer behavior is very complex and influenced by a wide range of factors that can be categorized into several key determinants, which often interact with each other (Hamadeh, 2021). These determinants help key stakeholders from several sectors such as researchers, marketers, and business people understand why consumers make certain food choices and lifestyle decisions (Hamadeh, 2017; Hamadeh, 2020; Hamadeh, 2021). Here are the main determinants of consumer food behavior explored and analyzed in qualitative studies:

  1. Cultural determinants: including beliefs, values, customs, traditions, and other sub-culture determinants such as religion, ethnicity, and geographic location.
  2. Social determinants: including family members, reference groups (friends, colleagues), a person’s role in society, and social status.  
  3. Psychological determinants: including consumers’ attitudes and perceptions about products and/or brands, motivation to make a purchase, learning from past experiences, and memory and cognitive processes to make decisions.
  4. Personal determinants: including age, life stage, occupation, lifestyle, personality, self-concept, and economic situation.
  5. Situational determinants: including purchase context (lighting, music, store’s layout), time pressure to make a choice, and physical surroundings in which a product is consumed.  
  6. Environmental determinants: including environmental and ethical concerns such as sustainability, and socially responsible products and/or services.
  7. Marketing mix determinants or the 4Ps: product attributes, price strategies, place convenience (availability and accessibility), promotion, and marketing.
  8. Online and digital determinants: including social media influence, e-commerce platforms, online reviews, and evaluation of alternatives.
  9. Crisis and ethical events: including natural disasters, economic crises, pandemics such as COVID-19, and how they significantly alter consumers’ priorities and attitudes of behaviors.

It’s important to note that consumers may weigh these factors differently, resulting in unique buying decisions (Hamadeh, 2021). Moreover, the fast evolution of technology and social media (SM) use is an imperative communication concept to investigate in food consumerism research (Hamadeh, 2020; Hamadeh, 2023) especially with the burgeoning of the virtual socio-business world, so-called the “metaverse world” (Cha, 2022; Hamadeh, 2023). Although, many efforts are made to study this digital evolution and social media platforms few explained by “how” and “how much” they are used to modify old and/or to develop new food behaviors, especially in the new virtual world of the metaverse (Hamadeh, 2023).

Between the physical and the metaverse food world

By definition, the new concept of the metaverse is a virtual, interconnected, and immersive digital world where people can interact and engage in various activities, including socializing, working, shopping, and playing. While it is more commonly associated with the fields of gaming, entertainment, and technology, it has the potential to impact various industries, including the food industry (Cha, 2022; Hamadeh, 2023).

In summary, the metaverse food world could be fascinating in several ways (Cha, 2022; Hamadeh, 2023) especially for the young generations (Cha, 2022; Hamadeh, 2022) and it comprises: virtual dining experiences; virtual culinary education (e.g., cooking classes); virtual food events and festivals hosted in the metaverse; menu testing with virtual tasting events organized by restaurants; virtual consumer education about the sustainability practices in the food supply chain; virtual kitchens and delivery experiences within the metaverse; food-related entertainment activities or competitions hosted by content creators and influencers engaging global audience; virtual food market places connecting farmers, artisans, producers, and consumers in the metaverse; virtual social gatherings and networking events centered around food and dining; and finally the food-related Non-Fungible Tokens (NFTs) that can represent unique virtual food items, recipes and culinary experiences within the metaverse where these digital assets can be bought, sold and traded among consumers.

It is noteworthy, that the integration of the metaverse into the food industry is still in its early stages, and the extent of its impact on consumer behavior will depend on several factors including technological advancements, users’ adoption, and regulatory considerations (Cha, 2022; Hamadeh, 2017; Hamadeh, 2022; Hamadeh, 2023; Ramadan, 2023). However, as the metaverse continues to evolve, it offers exciting opportunities for innovation and engagement within the food industry.

Qualitative analysis in the metaverse food world

Scientific evidence shows that qualitative analysis of consumer behavior is a valuable tool for academia, food industries, and businesses to gain a deep understanding of their target audience, improve products and services, and develop more effective marketing strategies in the physical world (Hamadeh, 2021). Similarly, this is how qualitative analysis can assist food industries in the metaverse context (Cha, 2022; Hamadeh, 2023; Ramadan, 2023):

For instance, qualitative analysis can involve conducting User Experience (UX) Research within the metaverse to observe how users navigate virtual food spaces, interact with food-related content, and make purchasing decisions. Indeed, understanding the UX helps food industries design virtual environments that are more appealing and user-friendly.

Also, hosting focus groups and interviews with metaverse users can provide valuable insights into their preferences, expectations, and motivations when it comes to food-related interactions. This information can guide the development of virtual food products, services, and experiences.

Qualitative research can analyse user-generated content and conversations within the metaverse, which can reveal trends, sentiments, and emerging preferences related to food matters. This can help food industries identify popular food items, culinary trends, and user-generated recipes that can be incorporated into their virtual offerings.

In addition, qualitative analysis can involve observing user behavior in virtual food spaces. This can include tracking which virtual restaurants or food vendors users visit most frequently, the types of virtual food items they purchase, and the social interactions they engage in while dining in the metaverse.

Moreover, conducting virtual ethnographic studies allows researchers to immerse themselves in the metaverse and gain a deep understanding of how people incorporate food-related activities into their virtual lives. This can uncover cultural nuances and social norms specific to the metaverse environment.

By soliciting feedback from metaverse users through surveys, comment sections, or virtual suggestion boxes, food industries can continuously improve their virtual offerings. Qualitative analysis of this collected information can identify areas for enhancement and innovation.

Creating personas based on qualitative research findings will help food industries to segment their virtual audience effectively. These personas can inform marketing strategies and product or service development tailored to different user groups.

When conducting qualitative research to analyze conversations, reviews, and user-generated content, food industries can identify emerging trends and adapt their virtual offerings accordingly. This agility can help them stay ahead of the curve in the rapidly evolving metaverse.

Qualitative analysis can also uncover insights into the emotional connections users have with virtual food experiences. Understanding the emotional aspects of virtual dining can guide food industries in creating more memorable and engaging experiences.

In conclusion, consumer behavior in the metaverse food world is likely to mirror many aspects of consumer behavior in the physical world while also incorporating unique and novel elements made possible by the virtual environment (user-generated content, UX research, etc.). As the metaverse continues to develop, it will be fascinating to observe how these trends evolve and shape the way people interact with food in digital spaces. Therefore, the use of qualitative analysis in the metaverse world would enable food industries to gain a nuanced understanding of consumer behavior, preferences, and expectations (Cha, 2022; Ramadan, 2023). This insight can be used to tailor virtual food offerings, enhance user experiences, and stay competitive in the evolving digital landscape of the metaverse.

References

Cha, S. (2022).Metaverse and the evolution of food and retail industry. Korean Journal of Food and Health Convergence, 8(2): 1-6. https://doi.org/10.13106/kjfhc.2022.vol8.no2.1.

Hamadeh, S. (2017).Digital food marketing: What we know, what we should know? British Journal of marketing Studies, 5(8): 12-26. 

Hamadeh, S.(2020). The new encyclopedia of nutrition: A reality after COVID-19. Advances in Nutrition and Food Science, 2020(7), Article ANAFS-198.

Hamadeh, S. (2021). E-Food commerce, nutrition economics and consumer behavior: Before and after COVID-19. British Journal of marketing Studies, 9(1): 30-36. 

Hamadeh, S. (2022).How Gen Z can improve community literacy about the 17SDGs? A realistic approach to construct a futuristic change-maker paradigm. Green Technology, Resilience and Sustainability Journal, 2(2): 1-11.https://doi.org/10.1007/s44173-022-00002-2.

Hamadeh, S.(2023). Are artificial intelligence and co-active life coaching the future designers of nutrition and fitness matters? Journal of Autonomous Intelligence, 6(2): 1-11. https://doi.org/10.32629/jai.v6i2.608  

Ramadan, Z. (2023). Marketing in the metaverse era: toward an integrative channel approach. Virtual Reality Journal, 27: 1905-1918.

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