Lifestyles and values likely to continue to spread in future interpreted from a cohort analysis of 400 measures x gender

Introduction

I previously presented an article entitled “Trends interpreted from a cohort analysis of 400 measures x gender on lifestyles and values” here in Knowledge Gallery. I conducted a cohort analysis using 2012 ~ 2023 data from “Profiler”, a fixed-point questionnaire with 15~79-year-old men and women participating in the consumer panel SCI^*1, and interpreted trends on the 5 lifestyles and values of wellness, cost performance, time performance, individual orientation, and diversity. I concluded this noting that it will become more important to “provide value that captures diversified lifestyle scenes, performance awareness, and emotions unique to each individual”.

Our focus in the previous article can be said to be changes that have already occurred and are apparent to date. It is also important to foresee changes that are likely to occur in future. I would thus like to explore “which lifestyles and values are likely to continue to spread in future” in this article.

Grouping 800 measures to identify typical patterns

In order to explore the lifestyles and values likely to continue to spread in future from the data of 400 measures × gender = 800 measures, I used an analytical method known as clustering since it would take time and effort to understand and organize each measure one by one. I first used clustering to group the three effect waveforms of “generation”, “aging”, and “era”, to extract several patterns. I next took an approach where I used forecasting to identify the patterns spreading from these, and understand “which specific lifestyle and value measures will apply”.

Fig 1 summarizes the results of clustering use the three effects of “generation”, “aging”, and “era” on each of the 800 measures.

Fig 1

On observation of the breakdown of the 7 patterns extracted, there were 2 patterns characterized only by the “generation” effect, 3 patterns characterized only by the “aging” effect, 2 patterns characterized by both the “generation” and “aging” effects, and no patterns characterized only by the “era” effect.

For example, patterns 3 to 5, which are characterized only by the “aging” effect, contain a large number of lifestyle and value measures endorsed by women. This indicates that women’s lifestyles and values tend to be influenced by changes in life stage due to aging, such as “socializing” and “family”.

Forecasting the future values of typical patterns

Next, I forecasted the 2024 ~ 2030 figures for the average applicability rates of lifestyle and value-related measures associated with each of the 7 patterns extracted to identify patterns that will continue to spread in future.

Fig 2

Fig 3 presents a summary of the forecasting results. “Increase/decrease” indicates whether the applicability rate of lifestyle and values-related measures associated with each of the patterns will increase or decrease in future.

Fig 3

On observation of increase/decrease in the seven patterns from 2024 onwards, pattern 1, which has a strong effect on older generations, and patterns 6, which has a strong effect on Post2nd baby boomers and young people, decreased, while pattern 2, which had a strong effect on young generations increased. Patterns 3~5, which had a strong effect on aging, and pattern 7, with a blend of young and old generations, remained steady.

Pattern 2 typifies “measures that rate higher the younger the generation” centered on Gen Z as lifestyles and values likely to continue to spread in future that are expected to increase. In other words, it could be said “lifestyles and values supported by Gen Z, who will lead society in future, will go on to be the standard in 10~20 years’ time”.

Lifestyles and values likely to continue to spread in future

Fig 4 shows the 59 measures that rated highly among Gen Z from the 69 measures on lifestyles and values likely to continue to spread in future associated with pattern 2, which were then categorized into 9 themes and counted.

Fig 4

The top five in terms of numbers of measures were time performance, internet/social media, interpersonal relationships, self-optimization, and trends/novelty accounting for 45 measures, or 76% of the 59 measures. The three items time performance, self-optimization≒individualist orientation, and diversity corresponded with the trends I have introduced in the past, indicating these are also likely to continue to spread in future.

From this point onwards, let’s take a look at several lifestyle and values measures that are likely to spread in future and deepen our understanding of them by linking them to emerging phenomenon.

I get much talked about topics from X (formerly Twitter), trending words etc.

Fig 5 is a graph that breaks down the measure “I get much talked about topics from X (formerly Twitter), trending words etc.” classified as internet/social media by gender into the 3 effects. A positive number indicates higher applicability than the average, while a negative number conversely indicates lower applicability than average. Among both men and women, the younger the generation, the more they gather information via social media and the internet.

Fig 5

In 2008 when Gen Z were first year junior high school students or were not yet born, the iPhone was also released in Japan, as were the Japanese versions of Twitter and Facebook. This is the embodiment of the characteristics of them as a digital native generation impacted by the advances of these technologies. It’s apparent Gen Z spends 3 times as much time on smartphones as they do on TV. Unlike TV, where the same footage is broadcasts on the same channels, social media plays information and videos customized/biased to the individual’s interests and preferences, diversifying values, leading to the diversification of lifestyles. As this trend intensifies in future, it is expected that consumers will become even harder to gain a grasp on.

I always check the latest trends, regardless of genre

Fig 6 is a graph on the measure “I always check the latest trends, regardless of genre” classified into trends/novelty. Among both men and women, the younger the generation, the more they are concerned about a broad range of trends.

Fig 6

Compared to the era where trends were born through mass media centering on TV, there are now an increased number of information touch points including the internet and social media, and the individual can now access an enormous amount of information, so each of us is now exposed to biased information and content in our limited time. The more the information we are exposed to diversifies in this way, the more it is likely we will be concerned that “trends are occurring in places we are unaware of”. This is deemed to be driven by the psychology of “not wanting to stand out” and “not wanting to get things wrong”, with information being weaponized.

In addition, women are more sensitive to trends the younger they are. Many 15 ~ 24-year-olds are single, and thus have a lot of free time to spend on themselves, so check trends on social media, and try to get on board if these things match their interests and preferences. As a result, trends often spread from young women.　In particular, trends related to food and beverages centering on sweets as well as fashion are likely to continue to spread from women in future as well.

I’m not good at talking with people for the first time

Fig 7 is a graph of the measure “I’m not good at talking with people for the first time”, classified into interpersonal relationships. Among both men and women, the younger the generation the more they struggle with talking to people for the first time.

Fig 7

With the digitization of online information and human behavior and relationships on social media, people may be becoming less comfortable talking with others they are meeting for the first time in real life. Unlike in times gone by where encounters outside of the community one belonged to in real life were limited, social media offers the benefits of enabling people to easily connect with many others who share the same interests and hobbies, although it does seem that a closed-minded psychology and behavior in which people avoid traditional close-knit communication is spreading. This closed-minded psychology and behavior is prone to being perceived as the result of the covid crisis, but since the “era” effect from 2012~2023 was virtually zero and flat, this may actually be a lifestyle/value that has been progressing over the long-term, that has been hidden by the covid crisis.

New values influenced by the internet and social media are also appearing. For example, it was just recently that the term “maru harassment” was coined, meaning that a sentence ending in a Japanese language full stop (“。”, pronounced “maru” in Japanese) could give an intimidating or cold impression, and suddenly became much talked about in 2024. In future, communication with “easy to connect with people” digitally and virtually is expected to increase further, and is likely to raise the bar with communication in real relationships.

My time is more important than time spent with family

Fig 8 is a graph of the measure “My time is more important than time spent with family”, categorized into self-optimization. Among both men and women, the younger the generation and the younger the age, the more people think their time is more important than time spent with family.

Fig 8

The reason why the younger the generation, the more they place importance on their own time is deemed due to changes in relationships between parent and child. In the Showa era (1925~1989), the mainstream family structure was one in which the father, the head of the family, went out to work, while the mother, a housewife, did the chores and child rearing, and parents educated their children from a higher position. At present, around 70% of families are dual-income households and are the norm, and parents spend less time with their children than in the past because they leave them in kindergartens and after-school care. The value of placing importance on one’s own “time alone” is thus deemed to have spread due to this lifestyle where family members spend a lot of time apart having taken root.

As the value of placing importance on this “time alone” spreads, the following lifestyles, which have already permeated society, are likely to take further hold:
・”Individual meals” where each family member eats a different menu arrangement at their own time since each family member has their own different lifestyle rhythm;
・Rather than everyone watching the same TV programs in the living room, each family member will enjoy different content on their smartphones, tablet devices, or game consoles;
・Following topics and trends and enjoying content on their smartphone at any time, including while walking; and
・”Stanning faves”, where each family member spends time and money on their own favorite celebrities

Conclusion

I have grouped the results of a cohort analysis on 400 measures × gender = 800 measures, and interpreted lifestyles and values likely to continue to spread in future centering on Gen Z to this point. The nature of our interpretation indicates a “diverse individualist orientation in which people use their smartphones to gather and share information online and on social media within limited amounts of time, while consuming products and services they feel are high performance” with spread even further. I would like to continue to explore these changes in lifestyle and values in future as well.

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[SCI® (nationwide consumer panel survey)]
Daily shopping data gathered continuously from 53,600 male and female consumers aged 15 ~ 79 nationwide. It provides information on consumers purchase status including “who, when, where, what, how many, and the price they purchased it for” for barcoded products like food, beverages, daily sundries, cosmetics, pharmaceuticals, and cigarettes.
SCI Shopper Index data is the tabulation of daily shopping amounts and shopping frequency based on receipt information collected by SCI when consumer goods are purchased.
*SCI is statistically processed, and does not disclose any information that could identify individual survey monitor panelists.

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