9: Question demographics, rethink user segments that matter

In a predigital world, most media sectors knew very little about their consumers and lacked any ability to develop cross-title (this person watches Law & Order and Seinfeld) or cross-media (this person reads the New York Times and watches Unsolved Mysteries) profiles of use. Nielsen (and similar measurement services) could construct a sample-based estimate of the number of viewers/users and a few very basic other characteristics (demographics such as age, gender, and income) that were important to advertisers. Movie theaters could tell you how many tickets were sold, similar for albums and books sold. But there was no capacity to know messier things about those consumers: why did they watch, do they watch/go to cinema a lot, did they play the album they bought again and again, was the experience fulfilling, disappointing, or fine, what other titles did they watch and find fulfilling. Similarly, newspapers may have known the names and addresses of subscribers, but knew little of what they read within the pages and what parts offered the value that compelled the regular payment.

In the absence of the knowledge we needed, we built lore on the information we had. But that lore needs tested, and lore that worked in scarcity may not prove effective in abundance. One example: demographics need to prove their relevance to understanding patterns of media consumption. Their previous use doesn’t warrant continued use; they need to earn their conceptual regard.

The persistence of turning to demographic categories as the source of meaningful patterns and insight leads us to leave unconsidered other bases that may more effectively lead to understanding. This isn’t to suggest that demographics used to be informative and now they aren’t; rather, perhaps demographics were never all that informative: they were just the best we could do with the available data.

We can now better trace cross-title and cross-media consumption and develop profiles of media use that provide the foundation for far more effective strategy and understanding especially in mid and micro media. Demarcations such as heavy-to-light use, strong-to-low passion (for media generally and specifically), and preference for general or specific media are all factors that may more reliably help us explain and understand media use and the different profiles of use that make up the heterogeneous field of contemporary media use (see 10). Of course there are some observable demographic tendencies: heavier consumption of sports among men and drama among women; patterns that generally correspond to age. But in a world of fragmented media use we mustn’t let assumptions about these tendencies prevent us from investigating more reliable ways of understanding user motivation, categorizing users, and developing strategies for reaching them.

Generations that matter
Many have existed in a period of ‘digital change’ their entire lives, but even a quarter-century in, we lack a sense of stabilizing norms because of the recency of great change in how media can be used and its steady evolution. We have tended to associate differences with younger versus older people, but a better approach is to recognize that people develop habits of media use based on the media and technology available at different life stages.

A lot of talk about ‘generations’ is quasi-sociological marketing babble. Maybe it is helpful to imagine a new generation every 10 years if you are selling things, but there are more meaningful ways to segment a population if we are thinking about media and technology use, namely, to base the distinctions on relevant inflection points.

We can categorize media technology generations on the basis of age when profound changes in technological tools and capabilities become typical in use (typically years after they are introduced). Quasi-sociological ‘generation’ distinctions (Boomer, GenX, Millennial, Z) are not as informative as considering life stage when disruptive technology is introduced and becomes widely adopted. Technology generations capture inflection points based on life stage at time of technology adoption to organize cohorts. [To be clear, there is variation among those in any birth year in terms of willingness and ability to adopt available technology and every technology has a different adoption profile. In all cases, ‘generation’ is a blunt categorization that risks category errors tied to other variables (income, education) but it can be a useful general heuristic, especially if the generations are categorized on factors directly relevant to the distinction being explored. Variability isn’t just in demographics but in life factors like retirement age and whether employed in careers that required adoption of many digital tools].

The oldest media technology generation are those among the legacy entrenched who are distinguished by living most of their lives and having established media habits before digital transitions began; roughly those born before 1955 (currently aged 70+). For most in this cohort, use remains grounded in legacy practices. The legacy context remains ‘normal’ even if they become fluent and extensive digital media users. Preliminary interviews suggest they are more likely to consume ‘mass media’ content than those younger, though may access it by internet (read news distributed digitally (apps and online mostly), use streaming and AVOD).

The next generation encompasses adapters: Those born between 1955 and 1990 who had established media practices before digital disruption. Given the broad age span, adapters range from an older cohort (~b.1955–1980, currently aged 45–70) that had completed schooling and established work and adult life before disruption. The younger cohort (b. 1980–1990, currently 35–45) reached adulthood before smartphones/social media/YouTube but often integrated these technologies and the media world they made accessible before establishing adulthood norms. As a result, they have more digital and less legacy norms in their routines and diets but still have useful memory of predigital practices.          

Those born from 1990 are digital first; they grew up alongside steady change in media choice and control. Those born 1990–2000 (currently aged 25–35) had the experience of being digital-first pioneers and were the first to experience major shifts in media and interpersonal experience: the mobility of use enabled by smartphones; the micro entertainment of YouTube; and were teens/young adults in social media 1.0.

Now in their late 20s – mid 30s, our interviews revealed significant changes in their use of social media from teen/young adult years around age 25. Our pilot interviews included a few born 2000–2015 that indicated use still characteristic of a pre-adult phase of life. Not only is the digital-first experience defined by the availability of mobile devices and social media, but also by limited experience with the scarcity of the predigital age. Considerable fracture into micro media had begun by the time they consumed media. Although kids’ media is often widely shared across an age cohort, the digital-first generation entered teen years as the bottleneck of scarcity broke open, allowing them much greater range of inputs during these identity defining years. 

Those born from 2015 mark the beginning of a digital only technology generation. This is not to say they will never use analog media – they will have books, maybe some will be ‘into vinyl.’ But the point is this generation will never have known the constraint of analog technologies and crucially, will never know a norm of mass media and the features of least-objectionable content.

When we investigate and build strategies for media use in the digital era, we must be cognizant of the process of change that will continue as analog experiences and norms disappear – especially those tied to mass reach. Of course technology generations are not determinative, a lot depends on satisfaction with those engrained habits: generation does not predict but is moderated by temperamental features such as inclination to try new things (plasticity), personality traits such as curiosity, tolerance for friction, and factors that force adoption (workplace requirements) – or so I would hypothesize.

We must also be careful not to confuse the behavior of young people (those under ~ age 25) as persistent and characteristic of lifelong use rather than characteristic of life stage. Young people may adopt and use new technologies and services differently because they lack established habits and rituals, but some of that difference of use ties to life stage (greater leisure; incomplete brain development; stage of self discovery ) – or so I would hypothesize.

Consequently, we should not assume young adult behaviors will persist but investigate how and to what extent maturity, life stage demands, and other factors lead to patterned negotiation of predigital norms with early digital native behaviors. Current 25–35-year-olds we interviewed (those born from ~1990 who entered teen years with many digital technologies and services available) indicate a shedding of some aspects of their ‘digital native’ behavior to become more characteristic of previous norms. They also adapt other behaviors. Many in this group evolved their YouTube use to consume content that looks like ‘TV shows’ to my middle-age eyes, but still, this content is more specific in its topicality and sensibility than what is characteristic of television/cable. This technology generation barely knew the scarcity that led to ‘good enough’ media consumption. Their persistent use patterns suggest they are never going to be channeled into such engagement; this is why mass audience reach has become so difficult.

There may be cases where demographic features illustrate patterns, but we must also look closer and recognize the variables that also differentiate within those categories. Demographic characteristics were not well correlated with key patterns in our interviews. Rather, key motives cut across age, gender, education, and income when considering a depth of evidence about what people do with media and why they do it. Where demographics did enter in was in individuals’ awareness of the existence of media and content that they’d value and their facility – mostly in relation to technological capacity – to access it.