مدل ارتباطات بازاریابی سلسله مراتبی هم افزایی رسانه های آنلاین و آفلاین
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|4142||2009||12 صفحه PDF||سفارش دهید||7840 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Interactive Marketing, Volume 23, Issue 4, November 2009, Pages 288–299
We propose a new hierarchical model of online and offline advertising. This model incorporates within-media synergies and cross-media synergies and allows higher-order interactions among various media. We derive the optimal spending on each medium and the optimal total budget. We also develop three hypotheses on the effects of within- and across-media synergies on both the total budget and its allocation. We estimate media effectiveness as well as the within- and cross-media synergies of offline (television, print, and radio) and online (banners and search) ads using market data for a car brand. We show that both types of synergies —within-media (i.e., intra-offline) and cross-media (online-offline)— exist. We show how within- and cross-media synergies boost the total media budget and online spending due to synergies of the online media with various offline media.
Online and interactive marketing communication spending continues to grow rapidly (e.g., Shankar and Hollinger 2007). In 2007, U.S. companies spent $10.4 and $7.7 billion on search marketing and display advertising, respectively, and together with other forms of online advertising such as email marketing, the total online media outlay was $24.4 billion (Advertising Age 2007). This amount represents approximately 8% of the total media spending, which includes all other offline media (e.g., television, radio, print). Online media spending is expected to more than double in 5 years (i.e., $60 billion by 2012) and to consume 18% of the total media expenditures (Advertising Age, 2007 and Shankar and Hollinger, 2007). Indeed, new media comprising online, mobile, and social media are emerging as the growth area for advertising for manufacturers and retailers (Ailawadi et al. 2009). The surge in online marketing spending and large offline media expenditures raises important questions for managers. How much should managers allocate to online media given their spending in all other media? Do online media interact with offline media to influence marketing outcomes such as brand consideration and brand sales? If so, how? Previous studies on marketing resource allocation reveal important insights on the effects of within-media synergies on the overall budget and its allocation (e.g., Naik, 2007, Naik and Raman, 2003, Shankar, 1997, Shankar, 2008 and Prasad and Sethi, 2009). Of particular interest is synergy, which emerges when the combined effect of two media exceeds their individual effects on the outcome measure (Naik 2007). Naik and Raman (2003) show that, when within-media synergy exists, managers should increase the total media budget and allocate more than fair share to the less effective medium. That is, managers should spend disproportionately more on the less effective medium because it reinforces the more effective medium. However, they examined only vehicles within-offline media, which could potentially have synergies with online media. That is, there could be across online–offline media synergy in addition to within-offline media synergies. For example, online media may enhance not just the effectiveness of offline media such as television or print, but also the synergy between those offline media components, television and print. To understand this phenomenon and test it empirically, we develop a hierarchical marketing communications model of online and offline media synergies. The model captures within-media synergies and across-media synergies and allows for higher-order interactions among various media. We analytically derive the normative spending rules for the model and develop hypotheses on the effects of within- and cross-media synergies on both the total budget and its allocation. We test the hypotheses from the theoretical model using data from a car company, which advertises on both the online and offline media to keep its brand in consumers' consideration set. The company evaluates the consideration outcomes using offline visits to dealer showrooms and online visits to configure cars on their website. We establish that both types of synergies, namely, within-media (i.e., intra-offline) and cross-media (online–offline) synergies exist. In other words, we show that online advertising amplifies the effectiveness and synergies of offline media (television, print, newspapers, and magazines) in increasing the online car configurator visits. To our knowledge, our study is the first one to document this substantive finding, providing evidence to support the hierarchical model of online–offline advertising. From a managerial standpoint, we address the important issue of the sources of growth in online media spending. The current use of online media is driven by managers' beliefs that it costs less than offline media (Barwise and Farley 2005). Its continued use, however, depends on demonstrating its effectiveness in achieving measurable goals such as awareness, consideration, or sales. Consequently, advocates of online advertising may exaggerate its effectiveness or understate the effectiveness of offline media (e.g., statements such as people zip television ads or direct mailings contain junk). Although online spending can grow by adopting such a competitive orientation to secure resources at the expense of the offline media, we identify alternate sources of growth: within- and cross-media synergies. Our results show how within- and cross-media synergies increase the brand's total media budget. Thus, by eschewing competitive orientation, online spending can grow solely due to the collaborative orientation, which involves building synergies with various offline media. Our proposed model extends Naik and Raman (2003) by distinguishing between two types (within-media and cross-media) of synergies and advancing new theoretical results. In particular, unlike Naik and Raman (2003), our model includes three-way and higher-order interactions among different media types. We organize the rest of the paper as follows. We first review the extant literature to develop the theoretical basis for the hierarchical model. We next formulate the hierarchical model of online–offline advertising and derive the new propositions and hypotheses. Subsequently, we describe the data, estimate the proposed model and empirically validate the hypotheses. Finally, we discuss the managerial implications and conclude by summarizing the contributions.
نتیجه گیری انگلیسی
We analyzed the effects of offline media (e.g., television, radio, print), online (e.g., banner and search ads), and direct mail on both online (e.g., car configurator visits) and offline (e.g., dealer visits) consideration metrics for a compact car brand. We focused on detecting within- and cross-media synergies, which together generate higher-order media interactions. Based on our empirical results and normative analyses, we summarize the takeaways from this study. First, the proposed hierarchical synergy model explicitly incorporates within- and cross-media synergies, providing a framework to investigate more complex natures of media synergy effects. Second, offline–online synergies exist and can be quantified. To estimate both the media effectiveness as well as within- and cross-media synergies using market data, managers can apply the proposed model and estimation approach. Third, we provide normative insights on how the overall media budget and its allocation changes in the presence of higher-order synergies. Finally, our findings indicate that collaborative orientation begets growth in online advertising because it reinforces not only the effectiveness, but also within-media synergies amongst various offline media. Our research limitations provide opportunities for future research. We did not include allocation to other marketing mix variables and media vehicles. We need more research on the role of N-media inputs such as billboards, placement, public relations, and salesforce (e.g., Albers et al., 2008 and Shankar, 1997). The proposed framework could be extended to incorporate the hierarchy of buying stages (e.g., awareness, consideration, and sales) and the dynamics of carryover effects. Finally, synergies could be explored within and across new media such as mobile media (Shankar and Balasubramanian 2009) and social media (Winer 2009).