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What weighs on millennials’ minds … and wallets?

by Akrur Barua, Susan K. Hogan
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9 minute read 06 August 2018

What weighs on millennials’ minds … and wallets? Understanding how behavioral factors may be influencing millennials’ lifestyle choices

9 minute read 06 August 2018
  • Akrur Barua India
  • Susan K. Hogan United States
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  • Introduction
  • Technology and millennials: Attached at the hip for life
  • For millennials, product usage overshadows ownership
  • Still influenced by influences, but they also like to influence...
  • Debunking some millennial myths: Immediate gratification and...
  • The millennial dollar question: What to expect from millennials

Millennials’ spending habits draw a lot of attention. Their decisions appear to be driven by a host of biases created by both technological and social change. Some of these changes are common to every generation, and some are unique to millennials.

Introduction

Any analysis of US economic data today could be incomplete without exploring millennials. After all, this generation, comprising individuals born between 1980 and 1995 and numbering around 66 million, is a sizable part of the population and the labor market in the country. 1 As the years pass by, millennials’ influence on the economy will likely only increase as their earnings rise over their life cycle, even as their diversity will likely influence society as well.2 Many researchers and practitioners have been studying and tracking this sizable group.3 To build on this existing research and also better understand the possible underlying reasons and decision-making biases driving millennials’ choices, we draw from the behavioral science literature and combine it with current economic evidence about the generation’s consumption trends. Based on these economic and behavioral insights, we provide some predictions about millennials’ choices and behaviors to expect going forward.

Technology and millennials: Attached at the hip for life

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Young people are driving the popularity of online streaming content

Smartphones and tablets, gadgets that we find difficult to live without, had hit the market before the end of the first decade of the new millennium.4 Even before that, the internet was pervasive, serving as a platform for exchange of information and ideas. Consequently, millennials have been continually groomed in technology and technology-related innovations, such as gaming, streaming content, ridesharing, and social media, for the lion’s share of their existence. Therefore, it is not likely surprising that a survey by Pew revealed that young adults are driving the popularity of online streaming content, with 61 percent of respondents in the 18–29 years cohort indicating they use online streaming services as the primary way they watch television, compared to only 31 percent for cable or satellite subscription, which is quite disproportionate from that of the entire adult population (figure 1). 5 Similarly, a Deloitte survey found that not only do millennials and Gen Z—those born just after millennials and into the early 21st century6—favor more online streaming content than other generations, but are also engaging in content streaming more frequently than other cohorts.7 Further, these two generations also demonstrate a stronger tendency to use their smartphones for movie and television viewing, and gaming as compared to other cohorts.8

 

Along with greater utilization of technology for consumption of content and entertainment, millennials are also more likely to utilize technology as a purchase vehicle than older generations, as Deloitte’s 2017 holiday survey revealed. Specifically, Gen Z and millennials intended to spend 61 percent and 58 percent, respectively, of their holiday budgets making purchases via online channels rather than in other store formats (figure 2).9 Surveys such as these hint that younger cohorts are the key drivers of e-commerce growth, which accounted for close to 9.0 percent of total retail sales in 2017, up from just 3.4 percent 10 years back.10

This trend of utilization of technology and, in turn, technology-enabled spending is likely to continue for millennials (and young people, in general). After all, technology for millennials is perhaps viewed as a necessity—something their lives would be incomplete without—rather than something “nice to have.” The decision-making bias explaining this likely persistence of technology in millennials’ lives is known as the endowment effect, which suggests individuals have the tendency to overvalue something that they already possess.11 Additionally, this cognitive bias suggests that these individuals are likely to expend more effort or resource to retain these items in their life as opposed to expending the same effort toward something that is not currently a part of their life.12

For millennials, product usage overshadows ownership

Given their high utilization of shared services such as Uber and Airbnb, millennials have been considered key drivers of the sharing economy.13 As the name implies, a sharing economy provides shared services or collaborative consumption of products without asking of or imposing full ownership responsibility on any individual participant.14 This active participation in shared services extends beyond transportation and vacation homes, to consumption behavior, as evidenced by data from the National Technology Readiness Survey (NTRS), which indicates that people in the age group of 18–34 years make up 49 percent of on-demand consumers.15

While this sharing economy trend is not solely happening with millennials, this focus on product use over acquisition by many millennials may also provide some possible insight into why homeownership rates for householders below 35 years of age fell from 41.3 percent in 2001 to 35.3 percent in 2017, a greater trend decrease than that for the overall population.16 This homeownership data is consistent with mortgage data. According to the United States Federal Reserve’s Survey of Consumer Finances, the share of households headed by those below 35 years having mortgages fell from 37.2 percent in 2007 to 28.1 percent in 2016.17 In comparison, the decline in share for all households during this period was lesser: from 46.3 percent to 41.5 percent.18

It would be simplistic, however, to assume that the decrease in homeownership is purely due to an affinity for product benefits over acquisition. A key situational factor to consider is the effect of the Great Recession on young people, especially millennials. While the economic downturn contributed to this homeownership rate decline overall,19 the early timing of this experience in millennials’ life and the effect it had on them may have a lot to do with not only millennials’ ability to make big-ticket item and long-term commitment purchases, but also their willingness—or rather, aversion—toward making these purchases.20

A tale of two factors: Not able to make big-ticket purchases vs. simply not wanting to

The disproportionate impact of the Great Recession appears to have had a significant impact on many millennials’ economic ability to make big-ticket purchases such as homes or vehicles. As evidence, the peak of unemployment during the downturn for 16- to 24-year-olds (19.5 percent) and 25- to 34-year-olds (10.6 percent) was higher than that for the entire labor force (10.0 percent).21 While the labor market has revived since then, the recovery was relatively slower (or more volatile) for younger cohorts;22 incomes for younger cohorts were also impacted more by the Great Recession (figure 3).23

Growth in median incomes for young people have fallen behind that of others

Another characteristic of the millennial generation is the surge in student debt. More millennials have taken on student debt than previous generations. For example, during the 1995–1996 school year, the approximate midpoint of when Gen Xers were in college, 25.6 percent of all undergraduates in two- and four-year colleges had student loans.24 By the 2008–2009 school year, the percentage had grown to 46.6 percent and then further to 47.0 percent by 2014–2015 (the latest school year for which data is available).25 These figures were much higher at four-year institutions (figure 4). Not only are more students taking out student loans, but the size of the loans themselves is large (figure 4) and has been growing rapidly. Data available for school years between 2000–2001 and 2014–2015 reveals that the average size of student loans in real terms in public institutions (two-year and four-year programs) went up by 51.5 percent during this period; the corresponding rise for private nonprofit and private for-profit institutions was 46.3 percent and 6.0 percent, respectively.26 These two factors combined—relatively slower income growth and high student debt—often play into millennials’ ability to make big-ticket purchases.

Millennials bear the burden of higher student debt than other cohorts

Even for millennials who can make a big-ticket purchase such as a home, psychologically, the behavioral bias of loss aversion—that is, the greater propensity to avoid losses at the expense of missing out on similar or even slightly greater gains—may play a role in their decision-making.27 Thus, even though the US economy is currently on a healthy trajectory,28 it may be worth exploring further whether the Great Recession had a disproportionate impact on millennials—both economically and psychologically—due to its timing.

Still influenced by influences, but they also like to influence: Behold the “review economy”

Apart from being the generation influencing the rise of the sharing economy, millennials could also be thought of as the cause and impetus for the “review economy.” Be it a restaurant or a date, people nowadays are quick to check and offer reviews. And young people are trailblazers of this trend. For example, in their shopping decisions, 53 percent of 18–29-year-olds have always or almost always read online reviews before making a purchasing decision; the comparative figure for the entire adult population is lower (figure 5).29 This cognitive tendency to look toward the behavior of others to guide one’s own behavior is known as social proof.30 And while this “what are others doing” tendency is not a new phenomenon, the ease and transparency with which technology—something that millennials are using more often—provides this real-time data on how peers view (say) restaurants or movies further helps feed the social proof theory. The role of online reviews for social proof is a trend that is on the upswing and we expect it is not going away anytime soon.31

Being more in tune with technology can create a natural affinity for millennials and other young people to seek virtual sources for social proof. Also, it is much easier to check reviews such as “most popular” or “most highly rated.” These help millennials cut through the myriad options that present themselves for just about any decision. A wide variety of options may have the adverse effect of causing decision fatigue—or making decisions harder—due to a phenomenon known as choice overload.32 Thus, these review scores can help individuals avoid choice overload, by providing an easy, readily apparent solution, or the default option.33 In terms of what venues millennials look to for these reviews, evidence suggests, unsurprisingly, social media is the forum they increasingly seem to favor,34 with 47 percent millennial consumers using social media during their shopping journey compared to 19 percent non-millennials.35

Young adults check online reviews more than others before a first-time spending decision

Debunking some millennial myths: Immediate gratification and experience mongers

An often-stated characteristic of millennials’ spending behavior is “immediate gratification.”36 Such a pattern, if it exists, is closely associated with the concept of present bias, which refers to the tendency of focusing more on a payoff closer to the present time when considering two future events.37 For example, due to present bias, smokers overestimate their self-control in the future and hence, resolve to “quit tomorrow” rather than today.38 Similarly, present bias forces people to discount their future needs and hence, spend more than what is optimal in the short term; consequently, they end up saving less for the future.39

Overall, is it truly the case that millennials exhibit greater present bias in their spending decisions than other generations? While data on savings for millennials is not available, the Bureau of Labor Statistics offers insights on average income and expenditure by age group in its Survey of Consumer Expenditure (SCE).40 As it turns out, the ratio of average expenditure to income for 25–34-year-olds—the closest proxy for millennials—was still low in 2016 (latest available data) compared to that for previous generations of young people, for instance, in the 1990s (figure 6). Even though this ratio has picked up a bit since 2011, this is likely due to improved economic conditions after the Great Recession—the ratio for the entire population displays a similar trend—than any spurt in millennial present bias. The data also reveals that younger cohorts are spending more on health care, insurance, pensions as part of their total expenditure—which suggests millennials are saving for tomorrow, rather than just spending on today.41

Young people are not indulging in any present bias binge

Along the same lines, there has been a lot of attention to the idea that millennials are experience seekers; that is, their immediate gratification may come in the form of spending on “experiences” such as entertainment, eating out, and travel—goods and services consumed immediately, rather than, say, durable goods that last for a longer time.42 However, while millennials may state that they prefer experiences such as travel over expenditures such as paying off debt,43 the actual spending data from both SCE data and a 2017 Deloitte study in 2017 suggests that what they are saying they prefer is not what they are doing.44 Similarly, consumers who are 25–34 years old, for example, are actually not spending more on food away from home—a proxy for eating out—and entertainment relative to total expenditure than previous generations of young people (figure 7)—a pattern no different from the ones for 35–44-year-olds and 45–54-year-olds.45

The millennial dollar question: What to expect from millennials

From our analysis, it is evident that a mix of factors—technological, economic, situational, and behavioral—have shaped millennials’ minds and spending decisions. Table 1 provides an overview of some of the behavioral biases at play and implications and predictions for what to potentially expect from this generation moving forward.

Behavioral factors influencing millennial spending behavior, implications, and predictions

Even in a world molded by a never-ending stream of information and technological innovations, it is likely inevitable that some behavioral biases creep into millennial decision-making. Combined with economic factors, behavioral factors will likely continue to shape millennials’ economic and social choices such as spending, saving, debt leverage, and housing. In addition, their choices will likely continue to be influenced by their beliefs and value systems and the situational events that continue to shape our landscape, a topic that we have only scratched the surface of and one that deserves further attention and is worth keeping an eye on.

Acknowledgments

The authors would like to thank Dr. Patricia Buckley, Kimmerly Cordes, Preetha Devan, Jonathan Holdowsky, Timothy Murphy, Negina Rood, Shraddha Sachdev, Rithu Thomas, and Kevin Weier for their contributions to this article. 

Cover image by: Kevin Weier

Endnotes
    1. Pew Research Center, The generations defined, accessed January 26, 2017; Richard Fry, Millennials are the largest generation in the US labor force, Pew Research Center, April 11, 2018. View in article

    2. Patricia Buckley, Peter Viechnicki, and Akrur Barua, A new understanding of millennials: Generational differences reexamined, Deloitte University Press, October 16, 2015; Albert Ando and Franco Modigliani, “The ‘life-cycle’ hypothesis of saving: Aggregate implications and tests,” American Economic Review 53, no. 1 (1963): pp. 55–84; US Census Bureau, “Millennials outnumber baby boomers and are far more diverse, Census Bureau reports,” June 25, 2015. The Census Bureau here uses a more expansive definition of millennials to refer to those born between 1982 and 2000. View in article

    3. Kelly Monahan, Jeff Schwartz, and Tiffany Schleeter, Decoding millennials in the gig economy: Six trends to watch in alternative work, Deloitte Insights, May 1, 2018; Deloitte, The Deloitte Millennial Survey 2018: Millennials disappointed in business, unprepared for Industry 4.0, 2018.

      View in article

    4. Lee J Miller, “Ten years of iPhones have made Apple the world’s number one company,” Bloomberg, September 11, 2017. View in article

    5. Lee Rainie, About 6 in 10 young adults in the US primarily use online streaming to watch TV, Pew Research Center, September 13, 2017. View in article

    6. Mikey Burton, “Move over millennials, here comes generation Z,” New York Times, September 18, 2015. View in article

    7. Kevin Westcott et al., Digital media trends survey: A new world of choice for digital consumers, Deloitte Insights, March 19, 2018. View in article

    8. Ibid. View in article

    9. Rod Sides, 2017 Deloitte holiday retail survey: Retail in transition, Deloitte Insights, October 23, 2017. View in article

    10. United States Census Bureau, sourced from Haver Analytics, May 2018; Deloitte, Deloitte forecast: Retail holiday sales to increase 4 to 4.5 percent, September 20, 2017. View in article

    11. Daniel Kahneman and Jack L. Knetsch, “Anomalies: The endowment effect, loss aversion, and status quo bias,” Journal of Economic Perspectives 5, no. 1 (1991): pp. 193–206, DOI: 10.1257/jep.5.1.193; Daniel Kahneman, Thinking, Fast and Slow (Farrar Straus & Giroux, 2011). View in article

    12. Ibid. View in article

    13. H. O. Maycotte, “Millennials are driving the sharing economy—and so is big data,” Forbes, May 5, 2015; Goldman Sachs, Millennials: Coming of age, sourced on November 22, 2017. View in article

    14. Myriam Ertz, Fabien Durif, and Manon Arcand, "Collaborative consumption: Conceptual snapshot at a buzzword," Journal of Entrepreneurship Education, 2016. View in article

    15. Charles Kolby and Kelly Bell, “The on-demand economy is growing, and not just for the young and wealthy,” Harvard Business Review, April 14, 2016. View in article

    16. US Census Bureau, sourced from Haver Analytics in May 2018; Dr. Patricia Buckley and Akrur Barua, The US housing market recovery: The past is not prologue, Deloitte University Press, November 16, 2016. View in article

    17. United States Federal Reserve, Survey of Consumer Finances, sourced from Haver Analytics in May 2018. View in article

    18. Ibid. View in article

    19. Buckley and Barua, The US housing market recovery. View in article

    20. Ibid.; Dr. Patricia Buckley and Akrur Barua, Are we headed for a poorer United States? Growing wealth inequality by age puts younger households behind, Deloitte Insights, March 12, 2018. View in article

    21. Haver Analytics, sourced in May 2018. View in article

    22. Ibid. View in article

    23. Bureau of Labor Statistics, Current Population Survey, sourced from Haver Analytics in May 2018. View in article

    24. National Center for Education Statistics, “Percent of undergraduates receiving aid and average amount awarded in 1995–96 per student, by type and source of aid and selected student characteristics,” Digest of Education Statistics, 1997. View in article

    25. National Center for Education Statistics, “Full-time, first-time degree/certificate-seeking undergraduate students enrolled in degree-granting postsecondary institutions, by participation and average amount in financial aid programs, and control and level of institution: 2000–01 through 2012–13,” Digest of Education Statistics, 2014. View in article

    26. Ibid. View in article

    27. Daniel Kahneman and Amos Tversky, "Advances in prospect theory: Cumulative representation of uncertainty," Journal of Risk and Uncertainty 5, no. 4, (1992): pp. 297–323. View in article

    28. Dr. Daniel Bachman and Rumki Majumdar, United States economic forecast: 4th quarter 2017, Deloitte Insights, December 12, 2017. View in article

    29. Aaron Smith and Monica Anderson, “Online reviews,” Pew Research Center, December 19, 2016. View in article

    30. Dorie Clark, “What you need to stand out in a noisy world,” Harvard Business Review, January 6, 2017; Lu Chen, “How to create customer loyalty with millennials,” Forbes, June 26, 2017. View in article

    31. Alison Kenney Paul and Susan K Hogan, On the couch: Understanding consumer shopping behavior,” Deloitte University Press, 2015; Susan K. Hogan, Rod Sides, and Stacy Kemp, Today’s relationship dance: What can digital dating teach us about long-term customer loyalty?, Deloitte University Press, January 23, 2017. View in article

    32. S. S. Iyengar and M. Lepper, “When choice is demotivating: Can one desire too much of a good thing?” Journal of Personality and Social Psychology 79, no. 6 (2000): pp. 995–1006. View in article

    33. Eric J. Johnson and Daniel Goldstein, “Do defaults save lives?,” Science 302, no. 5649 (2003): pp. 1338–9, DOI: 10.1126/science.1091721; Alain Samson, “A simple change that could help everyone drink less,” Psychology Today, February 25, 2014. View in article

    34. Kasey Lobaugh, Jeff Simpson, and Lokesh Ohri, Navigating the new digital divide: Capitalizing on digital influence in retail, Deloitte Digital, May 13, 2015. View in article

    35. Pew Research Center, Social Media Fact Sheet, January 12, 2017. View in article

    36. Aime Williams, “Best of money: Why millennials go on holiday instead of saving,” Financial Times, February 12, 2016; Kathleen Elkins, “Here’s how millennials spend their money, compared to their parents,” CNBC, June 30, 2017. View in article

    37. Ted O’ Donoghue and Mathew Rabin, “Doing it now or later,” American Economic Review 18, no. 1 (1999): pp. 103–24. View in article

    38. Ibid. View in article

    39. Ibid; Derek Thompson, “The two biases that keep people from saving money,” Atlantic, July 17, 2016. View in article

    40. Survey of Consumer Expenditure, Bureau of Labor Statistics, sourced from Haver Analytics in May 2018. View in article

    41. Ibid; Akrur Barua and Dr. Daniel Bachman, The consumer rush to “experience”: Truth or fallacy?, Deloitte Insights, August 18, 2017. View in article

    42. Sarah Halzack, “Shoppers are choosing experiences over stuff, and that’s bad news for retailers,” Washington Post, January 8, 2016. View in article

    43. Talia Avakian, “Most millennials put travel above buying a home or paying off debt,” Food & Wine, June 22, 2017. View in article

    44. Barua and Bachman, The consumer rush to “experience”. View in article

    45. Survey of Consumer Expenditure, Bureau of Labor Statistics, sourced from Haver Analytics in May 2018; Barua and Bachman, The consumer rush to “experience”. View in article

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Akrur Barua

Akrur Barua

Associate Vice President | Deloitte Services India Pvt. Ltd.

Akrur Barua is an economist with the Research & Insights team. As a regular contributor to several Deloitte Insights publications, he often writes on emerging economies and macroeconomic trends that have global implications like monetary policy, real estate cycles, household leverage, and trade. He also studies the US economy, especially demographics, labor market, and consumers.

  • abarua@deloitte.com
  • +1 678 299 9766
Susan K. Hogan

Susan K. Hogan

Research & Eminence Director | Chief Executive Program

Susan is a senior manager with Deloitte Services, LP, and is the Research & Eminence Director for Deloitte’s Chief Executive Program. Susan has more than twenty years of marketing research, relationship management, and education and training experience and deep experience analyzing and synthesizing data from multiple sources to provide insights and actionable recommendations. She also has a proven ability to gather, understand, and satisfy customer needs and cultivate ongoing relationships. Prior to joining Deloitte, Dr. Hogan was a member of the marketing faculty at Emory University’s Goizueta Business School, where she taught Consumer Behavior and Non-Profit consulting at both the undergraduate and graduate levels. Prior to earning her PhD at The Wharton School, Susan was in sales and marketing for IBM, where she called on both corporate and channel customers.

  • suhogan@deloitte.com
  • +1 404 205 3054

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