Interactive media usage among millennialconsumers

Marguerite Moore

College of Textiles, North Carolina State University, Raleigh, North Carolina, USA

AbstractPurpose – The purpose of this study is to determine a comprehensive model of millennial usage of interactive technologies in the current marketingenvironment based upon actual behavior.Design/methodology/approach – A data mining approach using decision tree analysis (DTA) generates two comparative models (i.e. millennialversus generation X and millennial versus baby boomers) of interactive media usage across 21 technology applications. A large national sample(n ¼ 3,289) sourced from the Kantar Retail IQ constitutes the data for the models.Findings – Millennial respondents indicate significantly higher usage of interactive media compared to both generation X and boomers across 14applications. Models indicate that millennials use interactive technologies for utilitarian/information gathering purposes as well as for entertainment.However, they are less likely to purchase online compared to their older counterparts.Research limitations/implications – Models provide evidence that both supports and extends previous research into interactive media from a usesand gratifications perspective. Findings suggest theoretical directions for research for economic versus emotional uses of interactive media.Practical implications – Findings suggest that while millennials are adept at using technology for research and interactive purposes they tend to buyin stores, presenting opportunities for multiple channel marketers and challenges for those who market online exclusively.Originality/value – The paper provides a realistic, comprehensive empirical model of interactive consumer behaviors across three prominent UScohorts within the current generational cycle.

Keywords Millennial generation, Cohort analysis, Interactive marketing, Decision trees, User studies, Individual behaviour, Marketing starategy

Paper type Research paper

An executive summary for managers and executive

readers can be found at the end of this article.

Introduction

The accelerated pace of technological change in markets over

the past 20 years is unprecedented. The generation of

consumers that is coming of age along with the proliferation

of technology into nearly every facet of daily life is commonly

referred to as The Millennial Generation including members

of the US population born between 1982 and 2000. In

addition, technology drives global homogeneity among

worldwide population within the Millennial age group,

generating cross-border cohorts who exhibit similar attitudes

and behaviors. Members of the Millennial Cohort pose

challenges for their Baby Boomer and Generation X

predecessors in terms of education, management and

marketing (Reisenwitz and Iyer, 2009). Though academics

and practitioners recognize the importance of technology in

the daily function of Millennial consumers (e.g. Kavounis,

2008; Tsao and Steffes-Hansen, 2008), and have made

progress into understanding the motivations for using these

technologies (e.g. Grant and O’Donohoe, 2007), empirical

investigation of interactive technology usage in today’s

dynamic marketing environment is lagging behind the rapid

adoption of these technologies.The purpose of this research is to determine a

comprehensive empirical model of interactive media usage

specifically among US Millennial consumers, to contribute to

an increasingly important knowledge base related to

technology driven marketing media. To achieve this end, an

inductive approach is employed that compares actual

interactive media usage among Millennial consumers to

their older counterparts: Generation X and Baby Boomers.

The research establishes a realistic model of interactive media

usage in the consumer decision process that provides direct

implications for practitioners who seek knowledge specific to

Millennial behaviors. Further, the research provides

important theoretical direction for understanding adoption

behaviors of interactive marketing technologies among the

three prominent cohorts currently driving US markets:

Millennial, Generation X and the Baby Boomers.

Literature

Consumer interactive media usage

A stream of marketing and more specifically, advertising

literature is evolving along with dissemination of the internet

as a tool for communication and commerce. Among this body

of work, a number of researchers focus upon various aspects

of interactive media and the young consumer’s acceptance or

avoidance of these media over the past five to ten years. This

stream of research focuses primarily upon the motivations and

outcomes of interactive media usage with the majority of

empirical investigation performed within the US using survey

designs with high-school and college student convenience

samples. With the exception of a single study (Reisenwitz and

The current issue and full text archive of this journal is available at

www.emeraldinsight.com/0736-3761.htm

Journal of Consumer Marketing

29/6 (2012) 436–444

q Emerald Group Publishing Limited [ISSN 0736-3761]

[DOI 10.1108/07363761211259241]

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Iyer, 2009) intergenerational research designs are absent from

this literature. The research can be broadly classified into twoareas: application of uses and gratifications theory, and the

role(s) of involvement, persuasion and information search inmotivating interactive behaviors. Across both of these areas,

consumer attitudes, intentions and behaviors in the context ofinteractive media or marketing channels are integrated into

research designs, with limited evidence related to actualbehaviors.

Uses and gratifications theory (UGT) represents thepredominant approach to understanding interactive media

usage, particularly among young consumers. UGT assumesthat individuals select and use media in a goal-directed

manner to achieve a level of desired gratification, thereforedifferent types of media are perceived as unique by individuals

and must compete for their attention (Katz et al., 1974).UGT is popular among interactive media researchers due toits guidance in examining goal-directed behaviors which are

inherent in these dynamic technologies (Ruggiero, 2000).Grant (2005) and Grant and O’Donahoe (2007) investigate

young consumer’s behavior with online marketing practicesand mobile marketing communications, respectively. Both

studies, performed on Scottish student samples, underscorethe potential negative impact of interactive marketing efforts

on the younger consumer’s market perspective. The formerstudy finds that young consumers most often use the internet

for “mood enhancement” and “experiential learning”.Qualitative data from the same study indicates that students

find online advertising to be mundane and boring comparedto television advertising. The latter study, also performed on a

sample of 13-17 year olds, indicates further evidence thatyoung consumers use interactive media (i.e. mobile phones)

for entertainment and social stimulation as opposed tomarketing research to inform their purchases. More recently,Tsao and Steffes-Hansen (2008) using a UGT approach find

that US high school and middle school also tend to use theinternet for entertainment and technology exploration.

The literature also indicates that consumer involvement andthe role of persuasion impact adoption of interactive

technologies. Leug et al. (2006) find that involvement,accessibility and time spent in a given channel positively

impact ultimate channel choice in their comparative study oftraditional versus online channels among US teens. Sullivan

and Heitmeyer (2008) also report that retailer preferencepositively impacts Generation Y patronage intentions in their

study of traditional (i.e. non-interactive) retail channels. Froma marketing communications perspective, Tsao and Steffes-

Hansen (2008) report that teens who exhibit a preference for“cyber-communication” spend more time surfing the internet

than those who prefer human communication.Consistent with the tone of Grant (2005) and Grant and

O’Donohoe (2007), Henrie and Taylor (2009) report thatMillennial consumers (i.e. US college student sample) who

recognize that they are targets of persuasion tend to developnegative attitudes towards the persuader. Related researchalso suggests that “teen internet mavens”, or teens with

extensive internet experience and knowledge tend to influencefamily information search using marketing media sourced

from the Internet (Belch et al., 2005).In summary, the academic literature offers insights into

young consumers’ motivations for using interactive media,particularly the Internet medium. In addition to UGT driven

research, evidence that consumer involvement plays a positive

role in interactive media usage for information search is also

demonstrated. The research also underscores the skepticism

with which young consumers perceive persuasive marketingefforts from both traditional and technology driven

environments.

Generational cohort theory

Generational cohort theory (GCT) asserts that populations

can be grouped into generations based upon placement in thehistorical cycle which includes specific events that shape the

attitudes and behaviors of members within each cohort.

Though GCT is most commonly applied within the UScontext, global homogenization supported by technology

drives the development of cross border cohorts (Schewe andMeredith, 2004). GCT is commonly applied to market

analysis, given its efficiency and effectiveness in targeting

markets. The cohort analysis methodological approach hasbeen present in the literature for over thirty years (Reynolds

and Rentz, 1981; Reynolds and Rentz, 1981) and continues

to be strategically relevant in today’s data intensive marketenvironment. Different terminology and timeframes are used

to define and describe the generational cohorts. The

comprehensive framework of US generations purported byHowe and Strauss (1991) informs the design for this research.

The Millennial Generation includes population bornbetween 1982 and 2004 and includes approximately 78

million members. Due to its size and growing market power,

the Millennial Generation is currently the primary focus ofpopular media and marketers. The preceding group,

Generation X includes population born between 1961 and

1981 and is proportionately smaller than the MillennialGeneration and the older Baby Boomer Generation. For this

reason, Generation X is characterized as forgotten or ignored

by marketers. Howe and Strauss (1991) refer to Generation Xas the 13th generation. The Baby Boomer generation includes

population born between 1943 and 1960. The Baby Boom

generation includes approximately 80 million members and isso large that it youngest members are referred to as Generation

Jones. Boomers are known for being values driven and seekinstant gratification. In recent years, Boomers have been

challenged with decreasing real estate values and losses in

portfolio value forcing a new frugality among this group.The empirical research into interactive media usage

presented in the previous section primarily offers insight into

young consumers’ motivations for adopting these technologies.Indeed, researchers and marketers tend to assume that young

consumers will aggressively integrate technology into their daily

lives, yet the manner that they use the numerous tools availableto them remains underexplored and potentially misunderstood.

The research reported in this study, directly addresses thisknowledge gap using a comparative cohort analysis on a multi-

generational US sample.

Methods

The research employs a reductionist data mining approach to

construct realistic models of interactive media usage among

Millennial consumers using a large national sample. Decisiontree analysis (DTA) is used to generate comparative models

between Millennials and Generation X and Baby Boomers,

respectively, to determine behaviors unique to thegenerational cohorts. Data for the study (n ¼ 3,289) are

provided by the Kantar Retail IQ database.

Interactive media usage among millennial consumers

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Decision tree analysis

Decision tree analysis provides a powerful tool for

investigating numerous relationships among quantitativedata in a simultaneous manner. DTA produces a

hierarchical model of effects that predict a single dependentvariable referred to as the target variable. Compared to

traditional statistical linear and discrete approaches, DTA isuseful for exploring relationships among diverse data due to

fewer operational constraints and thus greater modelingflexibility. The primary requirement of DTA is the availability

of very large datasets.Chi-square automatic interaction detector (CHAID) is

used to model interactive marketing usage among Millennial

consumers. The CHAID algorithm is required to model theeffects of binomial predictor variables on a single binomial

target variable. CHAID uses chi-squares to systematicallycompare variables and split them in groups, referred to as

nodes, based on significance testing. Tree configurationindicates hierarchical effects, with more significant effects

commonly occurring in earlier tree splits. Further, CHAID

allows variable to split in multiple nodes within the treeconfiguration. A priori model settings include: a maximum of

five levels for each tree, a minimum 25 cases per parent noteand ten cases per child node. Pearson chi-squares are used to

detect differences in the cases with alpha designated at 0.01for both splitting and merging. A Bonferroni adjustment is

also used in the model to further reduce the likelihood of

Type I error occurrence.CHAID facilitates cross-validation by performing both

training and testing models. The training model is firstgenerated to establish tree structure followed by the testing

model which is generated to ensure that the training modelstructure holds among the sample data. In cases that sample

sizes are limited, a larger portion of the data is used togenerate the initial training model and a smaller portion is

used to generate the subsequent testing model (SPSS, 2002).

For both models, 70 percent of the respective samples areused to generate the training models while the remaining 30

percent of respondents are used to generate the testingmodels. Given adequate structure consistency between the

initial and testing models, effects from the training model areinterpreted.

Measures

For both the Millennial versus Generation X model and the

Millennial versus Baby Boomer model the predictor variables

include 21 items which probe interactive marketing usage inthe context of clothing, shoes and accessories purchases and

recent interactive marketing usage not related to a specificpurchasing context (i.e. over the past six months) (Appendix).

All predictor variables are measured binomially, indicatingengagement or no engagement in the 21 focal interactive

marketing activities. The binomial target (i.e. dependent)

variable for each model is depicted by generational cohortmembership. Therefore, the 21 interactive marketing

behaviors are used to predict the target variable for cohortmembership, thereby profiling the unique behaviors of these

groups in terms of the measured independent variables.

Sample data

Total sample size consists of 3,289 respondents including:616 Millennial cases, 1,552 Generation X cases and 1,121

Baby Boomer cases. Data are accessed from the Kantar Retail

IQ database which uses a nationwide online consumer panel

as the sample frame. The Kantar panel includes

approximately one million households across the US,

recruited through different channels including web portals,

web communities, web aggregators and Internet advertising

firms. All respondents designate themselves as the primary

household shopper. The data for this study were collected

during June 2010 and focused upon consumers’ use of

interactive technologies in their everyday shopping behaviors

for clothing, shoes and accessories as well as their specific

behaviors over the past six months (Appendix).

Findings

Sample characteristics

Sample characteristics are evaluated for each cohort

including: gender, income, marital status, ethnicity,

household size, and home ownership. Frequencies are used

to analyze sample demographics. In cases that response rates

vary for the observed demographic variables, actual

percentages based upon the full sub-sample sizes are used

to calculate population proportions.Millennial respondents are predominantly female (85

percent) and report the highest frequency of annual

household incomes between $35K-$49,999K (16 percent)

and $50K-$79,999K (20 percent). The majority of

Millennials report that they are single (58 percent), followed

by married (39 percent). Though the Millennial sub-sample is

predominantly Caucasian (75 percent), the cohort sample is

the most ethnically diverse among the study with Hispanic

and Asian/Pacific Islander representing 11 percent each and

African Americans representing 6 percent of the group. The

majority household sizes for Millennial respondents include

one to two members (54 percent) with most Millennials

reporting that they rent (46 percent) or own (34 percent) their

home.Generation X respondents are also predominantly female

(82 percent) and report the highest incomes among the

cohorts: $50K-$79,999K (20 percent) and above $100K (23

percent). The Generation X subsample is also predominantly

Caucasian (84 percent) followed by African-American (6

percent), Hispanic (5 percent) and Asian (4 percent).

Generation X respondents report the highest incidence of

marriage among the cohorts (63 percent). The majority

household size among Generation X is the largest among the

cohorts with 47 percent reporting households with two or

three members. Generation X respondents report the second

highest level of home ownership (65 percent) behind

Boomers.Again, female respondents (81 percent) represent the

majority of the Baby Boomer sub-sample. Baby Boomers

report the second highest incomes, slightly behind Generation

X with 19 percent reporting household incomes between

$50K-$79,999K and 19 percent reporting incomes above

$100K. The Boomer sub-sample is the least ethnically diverse

among the sample with 89 percent of respondents reporting

that they are Caucasian, followed by African American (5

percent), Hispanic (4 percent) and Asian (1 percent).

Boomers report household sizes larger than Millennials, but

smaller than Generation X with 67 percent including two or

less members. Among the cohorts, Boomers indicate the

highest level of home ownership with 77 percent.

Interactive media usage among millennial consumers

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Decision trees

CHAID generated two distinct models that compare and

classify interactive marketing usage among Millennial

consumers with Generation X and Baby Boomers. Both

models indicate identical structure and similar risk estimates

between respective training and testing versions which

suggests the models generalize well across the data. Based

upon the consistency between the training and testing models,

interpretation of the decision trees proceeded.

Millennials versus Generation XThe CHAID model comparing Millennial behaviors to those of

Generation X indicated a four level structure with twelve total

nodes and six significant variable splits (Figure 1 and Table I).

The initial split is indicated by the variable “accessed social

network from my mobile device in the past six months”

(x2 ¼ 17.35, p , 0.000), followed by the second most

significant split “download retailer widget” (x2 ¼ 13.00,

p , 0.000) and the third most significant split “follow retailer

or brand on Twitter” (x2 ¼ 7.85, p , 0.005). The remaining

three splits in order of significance include: “purchased a

product online in the past six months” (x2 ¼ 7.71, p , 0.005),

“like a retailer or brand on Facebook” (x2 ¼ 7.19, p , 0.007)

and “spent time on a social networking over the past six

months” (x2 ¼ 6.92, p , 0.008).Interpretation of the chi-square statistics indicates that

Millennials were proportionately more likely to have accessed

a social networking site from their mobile device in the past

six months compared to Generation X. Among the sample

Figure 1 Comparative model of interactive marketing usage: Millennial versus Generation X

Table I Decision tree effects Millennial versus Generation X marketing usage

Split Variable Chi-square p-value Effect order

1 Accessed social networking site from mobile device in past six months 17.3579 0.0000 1

2 Follow retailer or brand on Twitter 7.8354 0.0051 3

3 Download retailer widget 13.0095 0.0003 2

4 Purchased a product online in past six months 7.7190 0.0055 4

5 “Like” a retailer/brand on Facebook 7.1914 0.0073 5

6 Spent time on a social networking site (e.g. Facebook, Twitter, blog, etc.) in past six months 6.9257 0.0085 6

Note: *Effects presented for training model (n ¼ 2,168)

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respondents who accessed a social network in the past six

months, Millennials were also more likely to report that they

regularly follow brands on Twitter. However, out of both

Millennial and Generation X respondents who follow Twitter,

Millennial consumers were less likely to have purchased a

product online in the past six months. Interestingly,

Millennial consumers who report that they did not purchase

online also indicate that they did not spend time on social

networking sites over the past six months.Among respondents who indicate (i.e. split one) that they

do not use a mobile device to engage in social networking, the

Millennials reported that they were more likely to download a

retailer widget compared to Generation X. Among the

respondents who downloaded a widget to connect to retailers,

Millennials were more likely to have “liked a retailer or brand

on Facebook”.

Millennials versus Baby BoomersThe decision tree that compares Millennials’ interactive

marketing behaviors with those of Baby Boomers indicated a

five level structure, with 16 total nodes and eight significant

predictors (Figure 2 and Table II). Overall model effects

indicate more pronounced differences between the Millennial

Generation and the Baby Boomers compared to the differences

indicated in the Millennial versus Generation X model. The

initial split for the model is indicated by “downloaded utility

‘app’ in the past six months” (x2 ¼ 60.12, p , 0.000) followed

by “sign-up or receive e-mail or text” (x2 ¼ 40.30, p , 0.000).

The third most significant predictor for the model is

“downloaded game or entertainment app to mobile device in

past six months” (x2 ¼ 17.56, p , 0.000), followed by “read or

post on retailer blog” (x2 ¼ 15.98, p , 0.000) and “purchased

a product online in past six months” (x2 ¼ 15.64, p , 0.000).

The last three significant predictors include: “accessed retailer

website from mobile device in past six months” (x2 ¼ 10.35,

p , 0.001), “downloaded and used coupons for an online

purchase in the past six months” (x2 ¼ 8.36, p , 0.003) and

“purchased a product online in past six months” (x2 ¼ 8.23,

p , 0.004).The initial split that differentiates Millennial and Boomer

interactive behaviors is whether respondents downloaded a

utility application to their mobile device over the past six

months. Millennials were highly more likely to have

downloaded a utility application compared to the older

Boomers. Among all respondents who downloaded a utility

Figure 2 Comparative model of interactive marketing usage: Millennial versus Boomers

Interactive media usage among millennial consumers

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application, Millennials were also more likely to have signed

up for retailer e-mail over the past six months. Among thosewho signed up for retailer e-mail, the Millennial respondentswere less likely to purchase a product online compared to the

Boomers. Further, among the respondents who did notpurchase online, Millennials were far more likely to have reador posted on a retailer blog in the past six months.

Respondents who indicate that they did not sign-up forretailer e-mail in the past six months, further split into three

additional levels. The Millennials among this group indicatethat they downloaded gaming or entertainment applications at

a significantly higher rate than Boomers. Among those who didnot download gaming applications, the Boomers were morelikely to have purchased a product online in the past six months

(i.e. split seven). However, among those who purchased online,the Millennial respondents were more likely to have used anonline coupon for their purchases (i.e. split eight).

Respondents who indicate that they did not download autility application in the initial model split indicated a second

significant level (i.e. split three). Among this group,Millennials indicated a higher incidence of accessing retailerwebsites from their mobile device in the past six months. This

variable represented the terminal node for this portion of thedecision tree.

Conclusions and discussion

The DTA suggests several patterns of behavior among

Millennial consumer use of interactive media thatunderscores the cohorts’ distinct manner with which theyappear to integrate these tools into their daily lives. Not

unexpectedly, the model that contrasts usage betweenMillennials and Boomers indicates more marked differencesin both the variety of significant variables as well as in the

magnitude of effect sizes. The differences between Millennialbehaviors and Generation X were less pronounced compared

to the former contrast.Compared to Generation X, Millennials are more active at

integrating technologies into their daily lives for marketing

purposes. Millennials use their mobile device and traditionalinternet means to connect to retailers or brands. They engage

in social networking using their mobile device, but do notreport regular social networking to the degree that GenerationX respondents report. The model also suggests a clear

indication that Millennials do not use the Internet to purchaseproducts compared to Generation X, despite their noted

frequent use of interactive technologies to connect withretailers and brands.

According to the DTA model that contrasts usage betweenMillennials and Boomers, the differences are more distinct(i.e. stronger effects) and more extensive (i.e. more significantvariables or tree depth). The two groups are significantlydifferent across seven different variables, with the “purchasedproduct online in past six months” variable splitting twicewithin the DTA hierarchy. For all significant variables, withthe exception of purchasing online, Millennial respondentsdemonstrate significantly higher integration of interactivemedia. Using both mobile devices and traditional internettools, Millennials accessed online resources for bothutilitarian and entertainment purposes. They also indicatesignificantly higher interactive connections with retailers orbrands through their blogging activities and couponingbehaviors. Again, Millennials were less likely to purchase aproduct online compared to the Boomer respondents.

From a general perspective, both models indicate significantusage of interactive media among Millennials for a variety ofreasons: information seeking, entertainment focused, increasedutility and deal focused. However, despite this activityMillennial consumers do not purchase products online to acomparable degree of the older generations considered in thestudy. The findings suggest implications for both practice andfuture research (for practical implications see managerialimplications and applications). The study’s design is groundedin actual behavioral data and is exploratory in this sense.However, interpretation of the findings through the uses andgratifications perspective indicates partial agreement with pastresearch using this approach. Consistent with Grant (2005)and Tsao and Steffes-Hansen (2008), the models suggest thatUS Millennials actively use interactive technology forentertainment as well as technology exploration (i.e.downloading applications). Contrary to Grant’s study ofyoung Scots (Grant, 2005) the results suggest that USMillennials actively engage in marketing research over using avariety of means: blogs, e-mail, mobile connections, utilitiesand various applications.

The findings also suggest that as expected Millennials aresuperiorly adept at using these technologies in their daily lifecompared to the older generations. The comparison betweenMillennials and Generation X indicates that members of theolder cohort are more likely to engage in social networkingfrom a non-mobile connection while Milllennials are morelikely to access social networks from their mobile phone.Given the variety and speed with which Millennials use thepotential portfolio of interactive tools, this generation appearsto control the technology in a manner that is integrated intotheir daily lives from both utilitarian and entertainment

Table II Decision tree effects Millennial versus Boomers interactive marketing usage

Split Variable Chi-square p-value Effect order

1 Downloaded utility “app” in past six months 60.1298 0.0000 1

2 Sign-up or receive e-mail from retailer in past six months 40.3015 0.0000 2

3 Accessed retailer website from mobile device in past six months 10.3520 0.0013 6

4 Purchased a product online in past six months 15.6454 0.0001 5

5 Downloaded game or entertainment app to mobile device in past six months 17.5625 0.0000 3

6 Read or post on retailer blog 15.9833 0.0001 4

7 Purchased a product online in past six months 8.2361 0.0041 8

8 Downloaded and used coupons for an online purchase in past six months 8.3660 0.0038 7

Note: *Effects presented for training model (n ¼ 1,737)

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perspectives. However, a substantial question remains

regarding the Millennial consumer’s resistance to online

purchasing. Potential limitations related to this finding are

noted in the Limitations and Future Research section.

Managerial implications and applications

Results suggest that older Millennials (i.e. born between 1982and 1992) use interactive technologies for multiple purposes: to

connect with retailers or brands online, to download coupons

online, to source entertainment and utility applications, etc.

Further, Millennial consumers also report active usage ofmobile devices to carry out these behaviors. However, these

consumers do not buy products online at rates comparable to

the older generations. The lack of willingness to purchase online

does not appear to have arisen from accessibility or incomelimitations given the sample data characteristics.

A major distinction among Millennials is the propensity to

download applications particularly “utility apps” to connectto retailers or brands. Marketers including retailers and

manufacturers should incorporate practical uses of technology

into their interactive marketing media when targeting

Millennials. Firms who undertake these efforts must alsoensure that they deliver value in terms of information and

time to the dubious Millennial consumer. This approach may

not prove as useful for the older cohorts, particularly the

Boomer Generation who does not use these technologies asefficiently as the younger cohort.

Millennial consumers in the study do not purchase

products online compared to the older cohorts. They useinteractive media to gather information on the go (i.e. using

their mobile device) including promotional media. This

finding suggests an opportunity for brands who market in

multiple channels to connect with Millennials and stimulateretail patronage using interactive promotional tactics. Based

on previous research, marketers should be cognizant of the

potential to irritate the Millennial consumer with too much

contact or potentially inflated promotional promises (Henrieand Taylor, 2009). The same principles apply to firms who

market online exclusively, however this model is further

challenged to convert Millennials to online purchasers.Analysts and academics commonly assume that Millennials

inter-mix function and entertainment using interactive

technology. The models suggest that Millennials use their

technology in directed, brief sessions. The research indicates ahigher incidence of social networking on a home computer

among Generation X respondents, with Millennials preferring

to use their mobile device for this purpose. Therefore, efforts

to integrate business with pleasure may actually irritate ratherthan attract the Millennial consumer. When approaching this

consumer, marketers must have clear messages, effective

technology and follow through on their claims.

Limitations and future research

The purpose of this study is to determine the actualinteractive behaviors of Millennial consumers in a

comparative multi-generational format grounded in robust

national data. Research tradeoffs were consciously undertaken

to pursue the study’s purpose. Limitations are primarilyrelated the study’s design including use of secondary data and

the DTA method. Though the sample data are accessed from

a reputable and reliable source, the questionnaire design was

not determined by the researcher and as such covered only

those questions important to the firm. Fortunately, the

interactive technology questions were extensive in the scope ofapplications that they covered. Further, the six items that

evaluated general interactive behaviors (Appendix), as

opposed to actions taken in the past six weeks, wereanchored to the context of clothing, shoes and accessories

purchasing. Findings could be markedly different for different

product categories such as consumer electronics or services.The age range of the Millennial Cohort within the sample

includes respondents born between 1982 and 1992 due to aminimum age requirement of eighteen for participating in the

survey. Therefore, younger Millennials are not included in the

analysis and may use interactive technologies differently fromolder Millennials. Previous generational analyses note

intergenerational differences between younger and older

portions of large cohorts such as the Boomers withGeneration Jones. As rapid diffusion of these technologies

continues, marketing research will be critical to understand

the nuances with which this large consumer group adopts anduses these tools.

The sample data are heavier in female and Caucasianrespondents. Potential gender differences may affect use of

interactive technologies and thus the outcomes of the study’s

usage models. This sample characteristic should beconsidered when interpreting the results, particularly from a

practical perspective. Brands that market exclusively to males

should carefully interpret the study’s results for theirrespective business contexts. Additionally gender differences

may also impact future theoretical work in this area.When using decision tree analysis (DTA), replication of tree

structure over multiple samples bolster the ability to

generalize findings. Though cross-validation analyses suggeststable model structure for both comparisons among the

sample data, replication of the tree structure using new

datasets would be ideal. Likewise, though the sample size isconsiderably larger than those used for traditional statistical

models, extremely large sample sizes provide additional power

for CHAID which considers each case in its algorithm.Though the data are recent (i.e. June 2010), given the rapid

pace of change in interactive capabilities, the applicability of

the research directly to markets is potentially short-lived.Therefore, research should continue to evolve along with this

phenomenon from practical and theoretical standpoints.Consumer integration of interactive technology will

continue to be an important focus for academic and

marketing researchers in the foreseeable future. From anacademic perspective, the study suggests further work from

the uses and gratifications perspective by examining media

use through economic/utilitarian versus social/entertainmentpurposes. From a practical perspective, actionable research in

this particular area is promising due to the availability of rich

secondary data sets that reflect a range of actual behavior.Therefore, replication studies for interactive technology and

usage are needed to build direct practical knowledge which

can also lead to theoretical knowledge through identificationof behavioral patterns.

References

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Interactive media usage among millennial consumers

Marguerite Moore

Journal of Consumer Marketing

Volume 29 · Number 6 · 2012 · 436–444

442

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Appendix

Measure items *

Thinking specifically about specifically about clothing, shoes

and accessories retailers which of the following ways do you

shop?. Sign-up for e-mail or text.. Follow a retailer or brand on Twitter.. Like a retailer or brand on Facebook.. Read or post on retailer blog.. Download retailer widget.. Searched for coupons or promotional codes online.

Which of the following activities, if any, have you engaged in

the past six months?. Downloaded a retailer or shopping “app” to my mobile

device.. Downloaded a game or entertainment “app” to my mobile

device.. Downloaded a utility “app” to by mobile device.. Downloaded a social networking “app” to my mobile

device.. Downloaded coupons to my mobile device.. Researched product from my mobile device while

shopping in store.. Researched product online before making a purchase in

store.. Signed-up to receive e-mails from a retailer.. Purchased a product online.. Downloaded and used coupons for an in store purchase.. Downloaded and used coupons for an online purchase.. Spent time on a social networking site (Facebook, Twitter,

blog, etc.).. Engaged in social networking conversations online

(posting, chatting, etc.).. Accessed social networking site on my mobile device.. Accessed retailer website on my mobile device.

*Response categories for all items: yes/no.

Corresponding author

Marguerite Moore can be contacted at: Marguerite_moore@

ncsu.edu

Executive summary and implications formanagers and executives

This summary has been provided to allow managers and executivesa rapid appreciation of the content of this article. Those with aparticular interest in the topic covered may then read the article in

toto to take advantage of the more comprehensive description of theresearch undertaken and its results to get the full benefits of thematerial present.

Over the last two decades or so, technology has continued to

advance at an unparalleled rate. This means that consumers

in the US born between 1982 and 2000 are surrounded by

technology in most aspects of their everyday lives.

Furthermore, the ubiquitous nature of technology has

produced “global homogeneity” for this so-called Millenial

Generation. One significant consequence is the emergence of

cross-national cohorts of individuals whose attitudes and

behaviors are comparable.The pervasive role of technology in the lives of Millenial

consumers is widely acknowledged in academic circles. Some

understanding of what factors motivate usage of these

technologies has also occurred. However, empirical research

into the use of interactive technologies among this consumer

cohort remains limited considering the rate of adoption.Interactive media and its significance among younger

consumers has attracted the attention of researchers

exploring the internet’s use for communication and business

purposes. But the approaches adopted thus far have

concentrated more on attitudes and intentions rather than

actual usage behavior.

Interactive media usage among millennial consumers

Marguerite Moore

Journal of Consumer Marketing

Volume 29 · Number 6 · 2012 · 436–444

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It is the opinion of several scholars that users and gratificationtheory (UGT) provides an established framework forunderstanding how young consumers use interactive media.That selection and usage of media is goal-driven is a keypremise of UGT, which also purports that a level of gratificationis the desired end-result. Individuals regard different mediatypes as unique and thus rivals for their attention.

Previous work involving Scottish students indicated that“entertainment and social stimulation” motivated their use ofmobile phones. By comparison, information seeking to informbuying decisions inspired minimal interest. A conclusion ofthis and other studies was that marketing appeals usinginteractive media may not prove effective.

Adoption of interactive technologies is also influenced byconsumer involvement and persuasion, the literature reports.For instance, evidence shows that internet surfing occurs morefrequently among adolescents who prefer “cybercommunication” than those who mainly interact face-face-face.

There is also evidence that internet-savvy teens stronglyinfluence family use of marketing media accessed online. Suchconsumers are also seemingly unresponsive to persuasionattempts and are negative towards those responsible for them.

A typical marketing strategy is to group consumers intodifferent age cohorts. It is widely accepted that the attitudesand behaviors of members within each generation are shapedby significant events which they experience as they grow up.Generational cohort theory (GCT) thus incorporatesknowledge of these unique characteristics to targetconsumer groups more effectively.

The population born between around 1982 and 2004 arelabeled as Millenials, a generation which interests marketersdue to its size and growing market influence. Generation Xconsumers represent the preceding era and this cohort ismuch smaller then Millenials or Baby Boomers, identified asthose born between 1943 and 1960. This generation isrenowned for being “values driven” and enticed by instantgratification. But harsh economic realities have necessitated amore frugal attitude among these consumers in recent years.

In the present study, Moore aims to acquire knowledge ofways in which younger consumers use the interactivetechnologies available to them. Her analysis involvescomparing Millenial consumers with both Generation X andBaby Boomers. Various factors are considered to exploreinteractive marketing usage in relation to the purchase ofclothing, shoes and accessories. Recent usage not linked to aparticular marketing context is likewise addressed.

A nationwide consumer panel was used to obtain secondarydata pertaining to 3,289 of US consumers, all identifyingthemselves as the main shopper for their household. The totalsample consisted of 616 Millenials, 1,552 Generation X and1,121 Baby Boomers. Demographic information wasrecorded for each cohort and data examination showed that:. females accounted for at least 80 percent in all three

cohorts;. ethnic diversity was greatest in the Millenial sample and

least among Baby Boomers;. Generation X consumers generally reported the highest

incomes, with Baby Boomers second largest; and. home ownership was most evident among Baby Boomers,

followed by Generation X then Millenials.

Moore uses decision tree analysis (DTA) as it is a proven

means of scrutinizing relationships in diverse data. It reveals

distinct ways in which Millenial consumers routinely engage

with interactive media. When measured against the other

generational cohorts, analysis exposed more pronounced

differences to Baby Boomers than with Generation X

consumers.In comparison with the Generation X population,

Millenials are more inclined to:. habitually use interactive technologies for marketing

purposes;. connect with retailers and brands using both mobile

devices and conventional internet methods; and. use their mobile device for social networking but engage in

the activity less.

Millenials indicate a markedly greater integration of

interactive media than Baby Boomers in all but one aspect:. deploying mobile device and traditional online tools;. using internet resources for functional and entertainment

reasons; and. interactive links with brands or retailers via blogs and

couponing activities.

Despite their considerably greater engagement with

interactive media, Millenials indicated a much lower

inclination to make online purchases than either or the two

older cohorts.The author believes that scope thus exists for brands to use

“interactive promotional tactics” as a means to gain their

custom. Marketing which cover multiple channels will have a

greater chance of success since the current work indicates that

Millenial consumers prefer to access interactive media via

their mobiles phones. In contrast, non-mobile connections to

social networking sites are more favored by older consumers.Evidence shows that both functional and entertainment

reasons prompt Millenials to use of interactive technology. It

is crucial that marketers who target this cohort recognize this

and integrate “practical uses of technology” into the

interactive media used. Providing value in respect of

information and time could help lessen the skepticism that

currently prevails. Moore additionally advises against overkill,

pointing to other research showing how too much contact and

exaggerated promises can alienate the Millenial consumer.

Clear communication, efficient technology and delivering on

promises are therefore imperative.Minimum age requirements meant that Millenials aged below

18 were not included in this study. Future research might

therefore investigate potential differences in usage between such

consumers and older members of their generational cohort.

The author also acknowledges the sample bias towards female

and Caucasian subjects and warns against generalizing results to

a wider population without further study. And although data

used was recent, marketers and practitioners are made aware

that the applicability of findings could be transient due to the

ongoing rapid evolvement of interactive media.

(A precis of the article “Interactive media usage among millennial

consumers”. Supplied by Marketing Consultants for Emerald.)

Interactive media usage among millennial consumers

Marguerite Moore

Journal of Consumer Marketing

Volume 29 · Number 6 · 2012 · 436–444

444

To purchase reprints of this article please e-mail: reprints@emeraldinsight.com

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