Premonitions and Déjà Vu - Full Introduction Journal of Advertising

Journal of Advertising

IMC research from 2005 to present

Guest Editor: Gayle Kerr, Queensland University of Technology

In its earliest days, IMC was a premonition. A way that marketing communication could change because the mass media paradigm had been broken. Schultz (1999, p. 337) described IMC as “the natural evolution of traditional mass-media advertising which has been changed, adjusted and redefined as the result of new technologies”. Born in the early days of the database and on the premise of measurability, early researchers conceived IMC as a tool for ensuring the tactical integration of messages across marketing communication disciplines such as advertising, public relations, direct marketing and sales promotion.

By 2000, IMC was recast from a marketing communication tool to a strategic business process. The inside-out approach, which put the customer at the focus, could not be strategically integrated without breaking down the organizational silos and involving all stakeholders such as employees and investors. This changed the subsequent definitions of IMC and led to a focus of research around key IMC concepts such as synergy and IMC as a measurable business process. Many of which were featured in the first ever Special Issue on IMC in the Journal of Advertising in 2005.

Now in the era of big data, IMC has again been changed, adjusted and redefined by technologies. Digital makes integration possible, as it is interactive and ongoing. It has empowered and personalized consumer-centric communication, amplified dialogue across media and platforms, made measurement easy and instant, and connected organizational silos and stakeholders. So these must be the halcyon days of IMC? Well, in some ways, it is nirvana. In other ways, it’s déjà vu.

IMC or whatever we are going to call it

“Advertising or whatever we are going to call it” (Schultz 2016) has changed dramatically since the early days of IMC. In fact, in their editorial introduction to the recent Special Issue of Big Data in Advertising, Malthouse and Li (2017, p. 227) wrote, “we adopt a broad definition of advertising that includes all types of brand communication, paid and nonpaid, as well as brand and consumer-initiated”. Their notion of an interactive dialogue, with and between brands and consumers, amplified across many different, measureable touch points is akin to IMC. Building on this and importantly for IMC research, they identify four categories of brand touch points and note that big data allows the linking of these touch points to financial outcomes.

Another way to recast IMC comes from Keller (2016), who broadened the focus of IMC to include paid, owned and earned media. Keller used the literature to develop a conceptual framework where marketers could achieve synergy by choosing, ‘”a variety of different communication options which may share some common meaning and content, but which may also offer different, complementary advantages or be designed with other communication options in mind” (p. 290). The seven IMC Choice Criteria are coverage, cost, contribution, commonality, complementarity, cross-effects and conformability. These criteria, although not empirically tested and largely focusing on paid and owned media, provide a process for IMC selection. Keller also urges the inclusion of earned media and integration of brand contact points as a research priority for IMC.

Even today, more than 20 years after its inception, IMC is still considered under researched (Ots and Nyilasy 2015). There has not been a large body of IMC research published in the Journal of Advertising (or even elsewhere). And most of that has been propagated by special issues which grow academic interest and output. This is not to say there has not been research which has explored the premise of IMC. But rather it has been positioned according to digital platforms or even dimensions of IMC such as cross-media synergy or touch points. As a result, much IMC research is not acknowledged as IMC (or whatever we are going to call it). This was raised as an issue by Kliatchko and Schultz (2014) who in interviewing CMOs reported that “Most clearly espoused an IMC approach, but they just didn’t use this terminology. Instead terms such as ‘fusion’, ‘insight-driven’ and ‘holistic’ replaced IMC” (2014, p. 387).

Premonitions of a measurable strategic business process

The earliest definitions of IMC described the “added value” of integration and the resultant “maximum communications impact” (AAAA 1989). This was echoed in the Special Issue on IMC, when Tom Duncan (2005, p. 6) wrote, “Companies and agencies should recognize the value of investing in IMC. This is because IMC is an ongoing, interactive, cross-functional process of brand communication planning, execution, and evaluation designed to strengthen the relationships that build brands and increase brand equity”. IMC was always about adding value and impact through organizational planning and processes. While this was good in principle, research sought to measure its practice. Process measures and even analytics were developed to prove the value of IMC as a strategic business process.

One of the earliest examples comes from Reid (2005). Expanding upon Duncan and Moriarty’s (1997) mini audit, Reid investigated how the IMC process might be evaluated in organizations and developed an organizational audit. In applying this tool to 169 companies, Reid demonstrated that about 16% of brand outcomes including customer satisfaction, brand advantage, sales performance and marketing orientation could be explained by IMC.

Building on Reid’s work, Luxton, Reid and Mavondo (2015) conceptualized and empirically tested IMC as a process capability - “a market-relating deployment mechanism that enables the optimization of communication approaches to superior communication effectiveness, which has other downstream benefits eg brand and financial performance” (p. 37). Their study demonstrated that IMC capability has a significant direct effect on a brand’s market-based performance and financial performance by developing and implementing more effective IMC campaigns.

Like Luxton et al, Liu, Burns and Hou (2017) present a process which is driven by and responsive to customer data, in particular customers’ perceptions of the brand. They assembled a framework using natural language processing and derived latent Dirichlet allocation (LDA) as a generative statistical model to analyse sentiment on 1.7 million tweets for 20 brands across 5 industries. They found that almost half of the tweets were negative and only 17% positive. Unhappy customers were almost three times more likely to tweet about their grievances than happy customers. Consumer-centricity, one of the founding ideals of IMC, can be powered by big data to help better understand consumer concerns, respond quicker and develop more relevant IMC strategies. Liu, Burns and Hou (2017, p. 236) suggest that, “social media marketing has grown to rival traditional promotion techniques and has become a viable component of integrated marketing communication”.

Déjà vu: Revisiting tactical integration

Synergy was always the promise of IMC. The earliest work on synergy focused on tactical or message integration, investigating the multiplied effect of using different marketing communication disciplines. Cross-discipline synergy, the original premise of IMC, was first demonstrated by Stammerjohn, Wood, Change and Thorson (2005, p. 56) who conceptualized a test of synergy as “a positive response to a campaign that is greater than the sum of separate expected responses based on the use of each communication tool”. They compared the individual and combined impact of advertising and publicity on attitude towards the advertisements and the brand.

Extending this work, Kim, Yoon and Lee (2010) investigated different combinations of advertising and publicity in terms of exposure sequence, publicity valence and product attribute consistency, and their impact on attitudes to the brand. Their work not only provided confirmation of synergy, but also demonstrated a counter-synergy effect, where inconsistent or even antagonistic messages generate greater negative impact than a single negative message alone.

Although not presented as an IMC paper, Jin, Suh and Donavan (2008) adopted an alternative facilitative-inhibition framework to examine the synergistic effects of advertising and publicity and empirically prove the IMC premise. They showed that people who received publicity recalled the brands both more frequently and earlier than those who were exposed to advertising only.  However, in addition to this facilitative or synergistic effect, the combination of publicity and advertising also supressed retrieval and inhibited the memory of other non-publicized brands. Therefore, the integration of brand messages has a second effect, not only increasing recall of the publicized brand, but also inhibiting the recall of other brands that were not publicized. Jin et al (2008, p. 53) suggest that the inhibition effect is a by-product of synergy because “strengthening a brand memory results in inhibiting memory of other related brands as far as the free recall paradigm is concerned”.

Research has provided evidence of synergy and counter-synergy; facilitation and inhibition. Yet all of this work is focused on the disciplines of advertising and publicity, which were the original tools of IMC. Subsequent work explored synergy cross-media and even cross-platform. In particular, it has explored the notion of fit or congruence or tactical integration, which signifies the similarity or consistency between two concepts, activities or even messages (Voorveld and Valkenburg 2015). Therefore, in the new digital world there is an element of déjà vu, where again we start investigating IMC with tactical integration.

Voorveld and Valkenburg (2015), for example, investigated the fit of advertising executions across the campaign (including same key visual, colour and slogan) in generating cross media effects. They found that cross-media campaigns have the best fit on the presence of logo, key visual, same colors and slogan. Interestingly though, campaigns with a higher fit were recognized and recalled less than incongruent campaigns, which attracted greater attention. However, the evaluation of the ad was more positive when the fit was high, because congruent information is more liked as it confirms our expectations. They suggest that “when consumers see ads in multiple media that use the same visual or verbal elements of retrieval cues, there is probably less need to pay attention because the ads are consistent with the existing brand schema and associations, resulting in lower memory“ (2015, p. 194).

The idea of fit or tactical integration was also investigated by Angell, Gorton, Sauer and White (2016) who applied it to our multitasking world. While previous research has suggested that media multitasking leads to worse recall and recognition (Voorveld et al. 2011, Bellman et al. 2014), Angell et al. (2016) found that in situations where there is congruence between the primary and second screen activities and where secondary screen activities have a higher level of social accountability attached to them, then advertising recall and recognition of advertising increases. They offer the example of a secondary activity (eg texting about a football game) which is both congruent with the primary activity (eg watching the game on TV) and represents an active display of social accountability (social activities instigated and therefore traceable to the individual). They conclude that the fit between multitasking activities is a determinant of advertising effectiveness. “Not all media multitasking detrimentally affects advertising effectiveness. Under the right conditions, multitasking can have a very positive effect on advertising outcomes” (2016, p. 206).

This was confirmed and expanded upon by Seijn, Voorveld and Smit (2017) who investigated multitasking in multiple ways. Multiscreening with separate tasks on multiple screen was compared with multiscreening on a split screen to try and simulate different viewing options. The results show that advertising is most effective when people used a single screen. However, the best multitasking option occurred when people multitasked with related tasks. People who engaged in related multiscreening had better brand memory of the advertising and more positive brand attitudes than people who engage in unrelated multiscreening. Attention, and subsequent program involvement, was a key factor.

In conclusion, IMC has found new ways to identify and understand consumers, new processes and platforms to align the organization inside and out and new, instant benchmarks of measurability. The result is that sometimes the research is not called IMC, and sometimes it revisits the tactical and platform orientations of the earliest days of IMC research. Once again, the natural evolution of advertising, and indeed even the strategic business process of IMC, has been changed, readjusted and redefined by technology. It must be déjà vu.


American Association of Advertising Agencies (1989), “Definition of IMC” accessed from

Angell, Robert, Gorton, Matthew, Sauer, Johannes, Bottomley, Paul and John White (2016), “Don’t distract me when I’m media multitasking: Toward a theory for raising advertising recall and recognition,” Journal of Advertising, 45 (2), 198-210.

Bellman, Steven, Kemp, Anna, Haddad, Hanadi and Duane Varan (2014), “The effectiveness of advergames compared to television commercials and interactive commercials featuring advergames,” Computers in Human Behavior, 32 (March 2014), 276-283.

Duncan, Tom (2005), “IMC in Industry: More talk than walk,” Journal of Advertising, 34 (4), 5-9.

Jin, Hyun Seung, Suh, Jaebeom and Todd Donavan (2008), “Salient Effects of Publicity in Advertising brand recall and recognition,” Journal of Advertising, 37 (1), 45-57.

Kim, Jooyoung, Yoon, Hye Jin and Sun Young Lee (2010), “Integrating advertising and publicity: A theoretical examination of the effects of exposure sequence, publicity valence and product attribute consistency,” Journal of Advertising, 39 (1), 97-113.

Keller, Kevin (2016), “Unlocking the power of integrated marketing communications: How integrated is your program?” Journal of Advertising, 45 (3), 286-301.

Kliatchko, Jerry and Don E. Schultz (2014), “Twenty years of IMC: A study of CEO and CMO perspectives in the Asia-Pacific region,” International Journal of Advertising, 33 (2), 373-390.

Liu, Xia, Burns, Alvin and Yingjian Hou (2017), “An investigation of brand-related user-generated content on Twitter,” Journal of Advertising, 46 (2), 236-247.

Luxton, Sandra, Reid, Mike and Mavondo, Felix (2015), “Integrated Marketing Communication Capability and Brand Performance,” Journal of Advertising, 44 (1), 37-46.

Malthouse, Edward and Li, Hairong (2017), “Opportunities for and Pitfalls of using big data in advertising research,” Journal of Advertising, 46 (2), 227-235.

Ots, Mart and Gergely Nyilasy (2015), “Integrated Marketing Communications (IMC): Why Does It Fail?: An Analysis of Practitioner Mental Models Exposes Barriers of IMC Implementation,” Journal of Advertising Research, 55 (2), 132-145.

Reid, Mike (2005), “Performance auditing of integrated marketing communication actions and outcomes,” Journal of Advertising, 34 (4), 41-54.

Schultz, Don E. (2016), “Advertising or whatever we are going to call it,” Journal of Advertising, 45 (3), 276-285.

Schultz, Don E and Beth Barnes (1999), “Strategic brand communication campaigns”, 5th ed. NTC Business Books: New York.

Segijn, Claire, Voorveld, Hilda and Smit, Edith (2017), “How Related Multiscreening Could Positively Affect Advertising Outcomes,” Journal of Advertising, DOI:10.1080/00913367.2017.1372233

Stammerjohn, Claire, Wood, Charles, Chang, Yuhmiin and Esther Thorson (2005), “An empirical investigation of the interaction between publicity, advertising and previous brand attitudes and knowledge,” Journal of Advertising, 34 (4), 55-67.

Voorveld Hilda, Neijens, Peter, and Edith Smit (2011), “The relation between actual and perceived interactivity: what makes the Web sites of top global brands truly interactive?” Journal of Advertising, 40 (2), 77-92.

Voorveld, Hilda and Sanne Valkenburg (2015), “The Fit Factor: The role of fit between ads in understanding cross-media synergy,” Journal of Advertising, 44(3), 185-195.