Social Phenomena Analysis: The impact of Digital Insights and Generative AI

Our presence in the digital world not only helps us connect, express, and communicate but also creates a data reservoir reflective of our digital personas. These Digital Social Insights allow marketers to understand their customers better and build products, services, and campaigns that resonate with their audiences.

However, the volume of digital insights data can be overwhelming, impeding/obstructing their benefits. Gen AI remedies that by allowing organizations to analyze and apply social and digital insights for market research, effective modeling, and segmentation.

When clubbed with digital insights techniques like social listening, Gen AI can understand multiple languages and colloquial expressions commonly used in social media, helping produce original analysis and solve complex problems.

This blog examines the advantages of using Gen AI and Digital Social Insights for effective market research and segmentation. We do this through a real-life business use case where our digital insights experts studied and segmented the single households in the US and Colombia using GenAI and social listening.

Navigating analysis and optimization with Generative AI

Understanding any social phenomenon requires gleaning through various information sources, including official and syndicated data, articles, and academic papers.

Gen AI tools such as Humata AI and ResearchAlde allow for fast and easy collection and synthesis of this information. This allows organizations to extract relevant insights more efficiently. These tools even offer a chat option to ask specific questions and receive synthesized information in seconds.

Gen AI simplifies the use of Iceberg and Kano models. The iceberg model is a system thinking tool that helps people understand the underlying causes of a problem or event. The Kano model establishes the relationship between the fulfilment of certain customer requirements or qualities and the expected level of customer satisfaction.

Utilizing social media mentions and prior knowledge of the two models, Gen AI can provide detailed explanations of each of the layers of the Iceberg model and complete information about each category of the Kano model in a very short time.

While the Kano model, used mostly in product development and customer satisfaction analysis to prioritize features, may not always seem like the obvious choice to understand a social and cultural phenomenon, Gen AI can elevate its application through its analytical capabilities.

Leveraging Generative AI in Segmentation

Gen AI can offer multiple use cases for segmentation depending on the data quality. Imagine you wish to identify clusters within these conversations using social mentions as the input data. You can use ChatGPT to group these mentions based on specified characteristics for segmentation. This approach minimizes the need to review many mentions manually and helps reduce analyst bias during categorization.

Alternatively, ChatGPT can use academic articles or papers as input data to summarize the content, identify major themes or trends, and identify the segments across the research papers. It leverages the analytical capabilities of Gen AI to save significant time and resources during segmentations.

Use case: The rise of single-person households in the US and Colombia 

In recent decades, single-person households have risen as the highest-growing households in Colombia, with a +125% increase between the last censuses conducted in the country (2005 – 2018). Meanwhile, the United States has been growing since 1940 and currently ranks second with the highest participation (falling behind only for two-person households), representing 28% of households in the country.

We analyzed single-person households in both countries using Gen AI and Digital Social Insights. The process included gathering data from various government sources, modeling, and social listening. Our researchers studied the patterns emerging from the data to identify the similarities and differences between people in both regions, their expectations, lifestyles, mindsets, and new needs.

For this exercise, the first segmentation focused on finding the main trends across all academic research spanning this phenomenon. We then used the summarized information from each academic paper as input data for ChatGPT.

The AI tool analyzed Colombia's information, demographics, lifestyle and consumption habits, demographics, economy, and consumer behavior during the pandemic.

The second segmentation sought to cluster social media mentions about living alone in Colombia. We leveraged social listening platforms to identify and cluster group mentions. These clusters were then used as input data Chat GPT.

Gen AI can create clusters, identifying the main characteristics of each theme previously found in academic research. This allowed us to identify the features of each segment and understand demographics, behavior, reasons, and lifestyles.

In Colombia, the first segment is the Independent Achievers, who see their independence as their main goal; the Task Focused are those who see household cleaning and organization as their main responsibility; and finally, the Sentimentalists who, despite enjoying their freedom, seek family affection and support.

For the United States analysis, we performed segmentation by ethnicity on official demographic data and results of the academic research. The analysis identified the following segments and their perspective on living alone: 

• Hispanics or Latinos residing in states such as California and Florida enjoy having their own space and the support of their loved ones.
• Whites residing in the north of the country tend to focus on the advantages of living alone, especially in terms of mental health.
• Asians in states like California and New Jersey highly value their privacy, freedom, and peace of mind.
• African Americans residing in the southeast of the country feel proud of being able to live alone and enjoy their autonomy.

We directed ChatGPT to apply the Kano Model to the data for social media mentions collected through social listening. The findings revealed emotions, sentiments, and experiences that people living alone experience, categorized as Exciting, Desired, Must Be, Less is Better, and Indifferent.

Our study revealed that organizations looking to tap customers from single-person households must consider the following factors while conceptualizing products, services or marketing campaigns:

Creating lasting bonds: People living alone in both geographies experience contradictory feelings. While living alone represents a personal achievement and independence, it also causes financial uncertainty, personal insecurities, and loneliness. This can lead to stress and anxiety that affect positive expectations of personal fulfilment.

Brands must understand how to accompany this experience and be an ally, especially for those starting to live alone. They must create long-term bonds with consumers and break down the barriers between contradictions, guiding consumers towards self-realization.

Connection across culture: Our segmentation concluded that Colombia's 'Sentimentalist' segment shared its characteristics with the "Hispanic" or "Latino" segment in the United States regarding family and support. For both segments, independence and autonomy go hand-in-hand with family support.

This reflects the value of family in the culture and how it evolves and adapts to new lifestyles, showing new opportunities for companies to respond to new needs in multiple regions across cultures.

Prioritizing: The high cost of living in the United States tilted consumer preferences toward more affordable products and services. While Colombians, especially the "Sentimentalists" segment, seemed more interested in the food and beverage category since some foods awaken feelings of nostalgia and help them feel the warmth of their homes and the company of their loved ones.

For Americans living alone, the food and beverage category must bring them convenience; one of their biggest concerns is price and avoiding waste, as most portions in the market are large. This allows companies to introduce product packaging sizes suitable for single households.

Our research further revealed that people living alone in Colombia and the United States show high interest in products and services that simplify and reduce the time spent on household chores, such as pre-made meals or multitasking appliances.

They demand a wider range of products, especially in the food category, individual or small portions, long expiration dates, or convenient formats. Additionally, both countries prioritize financial security, which makes discounts, low prices, savings plans, or money management services highly attractive to them. 

Gen AI and digital insights

Leveraging Gen AI and digital insights for segmentation can revolutionize how organizations understand and engage with their customer base. By harnessing the analytical capabilities of Gen AI, businesses can identify and cater to the diverse needs and expectations of various customer segments more effectively.

The case study presented here, focusing on single-person households in Colombia and the United States, underscores the invaluable insights that Gen AI can provide, revealing similarities and differences across different regions and cultural backgrounds.

When combined with digital social insight techniques like social listening, Gen AI empowers organizations to efficiently navigate the complexities of today's diverse consumer landscape, create lasting bonds with consumers, adapt to cultural nuances, and prioritize specific products and services.

As we continue to explore the potential of Gen AI, it is evident that the future of segmentation is driven by data-driven insights, objectivity, and personalization, ultimately leading to greater success in the competitive market.