Push and Pull Factors of the Internet Advertising

Push and Pull Factors of the Internet Advertising








MARKETING SAMPLE
1,598 Words
5 Pages

Push and Pull Factors of the Internet Advertising

Published 5, July 2014

Introduction

The effectiveness of the advertisement and promotion for Internet advertising is primarily important for long and short-term effectiveness of marketing strategy (Tellis, 2009; Hanssens, 2009). Still, the research so far conducted has focused on consumer packaged goods , raising questions as to whether the empirical generalization apply to the new internet business of the 21st century (Sharp & Wind, 2009).The growing usage of internet increases the number of audience for internet advertisement. The growing usage of the Internet increases the members of an audience for the Internet advertisements. Moreover, social media is the best platform for advertisers for the advertisement which gives consumers one click price comparison, 24/7 availability and the power to opt in and out permission based communication. Further, unlike the classic purchase funnel: the ‘seize control of the marketing process and actively “Pull” information helpful to them’, media fragmentation and choice profile ration invite consumer on a decision journey (McKinsey 2009, p.5).

In two ways, marketing activities are classified: traditional aggregate-level data on “push” mass media (e.g., broadcast included banner ads, print, TV, radio, magazines and newspaper) and customer-level data on what was “pulled” by the customer to enable purchase focused from web (e.g., web promotions like newsletter emails, coupons claimed). This combination enable firm to segregate consumers based on their receptiveness to push marketing, to profile them according to their pull behaviour and target them to enhance their business share. In case of Pull technologies, both customer and marketer needs to response. Because, marketer just put information on the internet in that case customers needs to pull information. Web sites, blogs, and Google are the good examples of pull technology (Yuan, 2006).
On the other hand, in push technologies, the customer is unable to control the content. There are pop-up pages on top of the content, which is already used by customer. To return to the previous contents, a customer needs to close or minimize the push window. Otherwise, he will be unable access the content of the original window. Subscription services, spam mail, and feedback requests are few of the examples of push technologies (Yuan, 2006).

Purpose

The purpose of the study is to establish research that fills knowledge gaps and evaluate the impact of online advertising on consumer behaviour. Kelly, Kerr, and Drennan (2010) argue that when it comes to advertising using social media websites, various opportunities for user avoidance exist due to the user’s expectations of a negative experience, irrelevance of advertisements to users, and uncertainty towards the advertising medium. This study enables the advertising expert to design various advertisements that reduce avoidance and increase the attraction ratio. The efficiency of enhanced online marketing techniques, along with the promotion of new ventures and strategic approaches provides customers an high access to information regarding the products and services. The customers then, adapt for the future measures such as Integrated Marketing Communication (IMC).

Hypothesis

H1: The presence of online advertisements will create intention to revisit the site without advertisements
H2: There is a positive relationship between advertising format and individual characteristics and that could impact intention and behaviour (motives and belief)


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Literature Review

According to The Internet World Statistics, (2011) there are two billion (2,095,006,005) Internet users worldwide. Among them, majority of them are from to Asia and Europe. According to a report from the Internet and mobile association in India, there are about 38.5 million online users in India you mean, as you just said there were 2 billion (Suresh & Shashikala, 2011). However, almost one fourth of the population from developed countries use the Internet for various reasons and purposes. Wang et al., (2002) suggested that most of the goal-oriented users of the Internet are supported and motivated by the online advertising services, which have an impact on consumer behaviour. Hopkins, Raymond, and Mitra (2004) argue that online advertising influences attitude and purchase intentions, with respect to advertisement and brands, as the above mentioned characteristics enable narrative format and virtual presence of the products or services. In the United States, online advertisement earned $5.7 billion during second quarter of 2008 (IAB, 2008).
Many organizations have adapted to e-commerce in order to establish electronic storefronts for managing complex supply chain operations. Epstein (2004) argues that the key question is not the investment made by the organization in e-commerce but how to profit from such investments. There are various aspects related to the profitability of the organization adapting to online marketing. The costs related to search functions and transactions are considerably reduced to a certain extent for Small and Medium Enterprises (SME) in the developing countries. Due to the adaption of online marketing strategies, organizations are able to increase their efficiency and to reduce time and costs.
According to the report from Indian Online Retail Market Analysis (2012), a rapid increase in the online retailers exists in India. Along with the increase in Internet penetration, broadband availability, and use of smart phones, consumers have adapted to buying products using online services comfortably. The major reasons of/for attraction to online services are cash-on-delivery payments and discounts or offers provided by online marketers. The adaptations in the lifestyles of people in metropolitan cities also attracted the consumers to the online services. In India, the online service markets are highly influenced by the increase in the sales of the kids’ products and groceries. However, despite the increase in sales, the online retailing is not given much importance. There are around 80 million internet users in India wherein, the penetration rate is only 7% of the population (17% of urban population) when compared to other developed countries, whose penetration rate is of 36% (Bhinde et al., 2011). Moreover, the Internet is as a medium of online shopping amongst consumers that is relatively low (Shrivastava & Ujwal, 2011), which represents a growth potential for intentional marketers. Despite the huge potential of the Internet usage for online marketing in India, its user perceptions, attitude, acceptance, avoidance, and behaviour have received little attention from academics.

Attitude towards advertisements, particularly consumer distrust of advertising (Shavitt, Lowrey, & Haefner, 1998) and strong inclination towards advertising avoidance, has been well-researched (Speck & Elliott, 1997; Homer & Yoon, 1992; Homer, 2006; Dutta-Bergaman, 2006). Further, consumers strongly believe that advertising is more manipulative than informative (Mehta, 2000). Thus, due to technologies, support avoidance has become automatic, allowing consumers to decide how and when messages will be received (Schultz, 2006b). Further, Schultz suggested that due to oversaturation of advertising clutter, consumers’ upright shields to shut out and avoid the “push” of the advertising message from marketers. Thus, consumers “pull” the desired information from the Internet (Schultz, 2008). The push-pull model of marketing communication (See Figure 1) enables consumers to control the information flow, either deleting the message immediately or avoiding the advertisement completely, and this is particularly applicable to pop-up advertisements (Cho & Cheon, 2004; Ingram, 2006).

Rodgers & Thorson (2000) declared that there are various aspects that influence users towards the Internet advertisements. Intention of browsing depends whether (or not?) a user is goal oriented or casual. Stiff & Mongeau (2003) make the argument that in order to evaluate influence of the/an advertisement, Consumer-Related Factors (CRF) such as age, income, education, and gender are determined as(to be?) critical aspects. In order to understand the attitude of consumers, it is imperative to consider their feelings and beliefs towards advertising (Wellbacher, 2003). (Homer 2006; Mehta 2000; Dutta-Bergam 2006; Shavitt et al, 1998) also commented that the consumer’s feelings and beliefs should be considered towards internet marketing. Fill (2006) suggests that when an advertisement is appreciated, consumers are expected to have a positive perspective with/on the specific product or services. The Push and Pull model of the Internet marketing by describing the interactions of people with their media experience (Peter, 2003). In India, there are several studies that have focused on the buying behaviour of the Internet users (Sin & Tse, 2002) or their attitude and perception towards the Internet advertising (Schlosser et al, 1999) but not much on the belief factor from the push or pull marketing perspective (Sin & Tse, 2002; Schlosser et al, 1999, Shrivastava & Ujwal, 2011). The relationship between consumers and advertising strategy influence on the users’ perception of online advertisements is examined in the study.

Research Aims

The main aim of the study is to understand how one advertiser-controlled factor (advertising format, with particular reference to pop-up advertisements) and two sets of consumer-related factors (CRF: demographic variables and motives for using the The Internet is influenced by consumers’ perceptions on Internet advertising. The outcome will influence attitudes and avoidance intentions/behaviours with regard to The Internet advertising.

Research Objectives

The primary objectives of this study are,

  • To understand the impact of an advertising format (pop up advertisement) on the behaviour, attitude, perceptions, and avoidance intention of consumers.
  • To determine the impact of various consumer-related, the Internet-related, and traditional demographic factors on the behaviour and attitude of consumers.
  • To assess the impact of consumer-related factors (CRF) and advertising formats (ADF) on variables such as avoidance of the Internet advertisements, reasons for avoidance, beliefs, and attitudes.

Key deliverables

  • The present study will identify the most effective advertising format from an online retailing context
  • Recommend suitable advertising format for online retailing industry based on the Internet motives and demographic variables and its interlinking with type of advertising format.
  • This work will be used to recommend the effectiveness of internet based advertising strategies and streamline the interaction between interactive media and users.

Research Methodology

Based on the existing literature, the researcher has framed the research questions. In order to arrive at the solutions for the research questions, the researchers have to justify the research methodology. The researcher of this study adopts onion approach that has been developed by Saunders et al (2007). He has adopted many strategies, paradigms and data collection methods in this study. They are illustrated in the figure 1. The researcher in this study follows a realistic philosophy. The reality obtained from the outcomes of a study can be applicable for similar social constructs and the perceptions of the researcher will have no influence over these factors (Remenyi et al., 1998).Generally, the research approach would be divided into two types. They are: deductive approach and inductive approach. The researcher of this study has adopted deductive approach. The researcher collected and framed the research hypothesis and theories with the help of thorough literature review and adopted a top down analysis (Marcoulides, 1998).

Normally, the major and essential component of the research design is the selection of appropriate data collection method. The data collection method is of three types. They are: qualitative approach, quantitative approach and mixed approach. The research method used for this research is Quantitative research. Quantitative research refers to the systematic empirical investigation of social phenomena via statistical, mathematical or computational techniques (Saunders et al., 2009).
Various approaches such as surveys, laboratory experiments and observations in the field are used to collect primary data. The researcher has framed the questionnaire based on the critical success factors. He has used questionnaire as the data collection instrument in this study as it could be useful to obtain the responses of a larger population within short period of time (Creswell, 2003). The researcher has collected data by means of simple and reliable close ended questionnaires. Each respondent is provided with ten minutes so as to respond to the questionnaires. The researcher has used Likert Scale in this study so as to scale the responses uniformly. This Scale is found to rank the responses under five categories as “Strongly agree (5), Agree (4), Neutral (3), Disagree (2), and strongly disagree (1)”.
Questionnaire Survey will be carried out in New Delhi, India.. The sample populations chosen to take part in the survey will be university students from various colleges in the city. A major reason for choosing university students is the fact that the younger population are more prone to Internet usage. Hence, they are aware of the new technologies underpinning them. In addition, the fact that students have free access to the Internet within the university campus is also a major reason for their choosing them for the research study.
Initially, the researcher will feed the collected data into the excel sheet. Then he has exported the data into the SPSS (Statistical Analysis Software). The continuous data were analyzed with the help of the descriptive statistics (i.e., mean, standard deviation and percentage) so as to arrive at the conclusion.

Limitations

The current study has certain limitations. The chosen sample in the study is university students, who are the frequent users of the Internet. The Internet advertising is a growing concept and affects not only this one demographic. There are also, other areas of people who use the Internet. However, it was not possible to collect data from all kind of sector due to time constraints. Hence, the University students were alone chosen to represent all users of the Internet in India. The survey has not taken into account the opinions of individuals from other lifestyles, mainly due to financial and time restrictions.

Conclusion: The proposed study will be deductive, quantitative methodology, survey method using questionnaire. The data will be collected among students and analysis will be done using SPSS software.

Time schedule

This study will be carried out as shown in the table below: I have decided to submit my thesis wok according to above table. But, it is a rough estimate of what will be involved in submitting project work. This time line may be changed according to progress and feedback.

References

Bhinde, A., Sharma.K., Suneja, S., Agrawal, A. and Mishra, K. (2011). India goes Digital. Retrieved from http://www.avendus.com/Files/India_goes_Digital.pdf

Cho, C. & Cheon, J. (2004). Why Do People Avoid Advertising on the The Internet?. Journal of Advertising, 33(4), 89-97.

Creswell, J. W. (2003). Research Design: Qualitative, Quantitative and Mixed Method Approaches. California: Sage Publications.

Dutta-Bergman, M. J. (2006). The demographic and Psychographic Antecedents of Attitude Toward Advertising. Journal of Advertising Research, 46(1), 102-112.

Epstein, M. J. (2004). Implementing E-Commerce Strategies: A Guide to Corporate Success After the Dot.Com Bus. Westerport: Praeger Publishers.

Fill, C. (2006). Marketing Communications – Engagement, Strategies and Practice (4th ed.). UK: Pearson Education Limited, Essex.

Hanssens, D.M. (2009). Empirical Generalizations about Marketing Impact. Cambridge, MA. Marketing Science Institute, Editor, Relevant Knowledge Series.

Homer, P. M. (2006). Relationships among ad-induced affect, beliefs and attitudes: Another Look. Journal of Advertising, 35(1), 35.

Homer, P. M. & Yoon, S. G. (1992). Message Framing and the Interrealtionships among Ad-based feelings, Affect, and Cognition. Journal of Advertising. 21(1), 19.

Hopkins, C. D., Raymond, M. A. & Mitra, A. (2004). Consumer Responses to Perceived Telepresence in the Online Advertising Environment: The Moderating Role of Involvement. Marketing Theory, 4(1/2), 137-162.

Indian Online Retail Market Analysis (2012). Retrieved from http://www.rncos.com/Report/IM421.htm

Ingram, A. (2006). The Challenge of Ad Avoidance. Admap, 472.

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Marcoulides (1998). Valuing employees: a success strategy for fast growth firms and fast paced individuals. In P.D. Reynolds., W. D. Bygrave., P. Davidsson., W. B. Gartner., C. M. Mason. & P. P. McDougall (Eds.), Frontiers of Entrepreneurship Research (pp. 17-31). MA: Center for Entrepreneurship Research, Babson Park.

McKinsey (2009). The Crisis: A New Era in Management. McKinsey Quarterly. 1.

Mehta, A. (2000). Advertising Attitudes and Advertising effectiveness. Journal of Advertising Research. 40(3), 67-72.

Peter, Z. (2003). Lots of Reasons for Optimism with Online Newspaper Services. The International Journal of Newspaper and Technology.

Remenyi, D., William, B., Money, A. & Swartz, E. (1998). Doing Research in Business and Management. An Introduction to Process and Method. London: Sage

Rodgers, S., & Thorson, E. (2000). The Interactive Advertising Model: How Users Perceive and Process Online Ads. Journal of Interactive Advertising, 11, Retrieved from http://jiad.org/vol1/no1/rodgers/

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Shavitt, S., Lowrey, P. & Haefner, J. (1998). Public Attitudes Toward Advertising: More Favorable Than You Might Think. Journal of Advertising Research, 38(4), 7-22.

Shrivastava, A. & Ujwal. L. (2011). A Business intelligence Model for Indian Consumers‘ Behaviour with respect to Motivation. International Journal of Computing and ICT Research, 5(2), 11-31. Available at: http://www.ijcir.org/volume5-number2 /article2.pdf

Sin, L. & Tse, A. (2002). Profiling The Internet shoppers in Hong Kong: Demographic, psychographic, attitudinal and experiential factors. Journal of International Consumer Marketing, 15(1), 7-29.

Speck, P. S. & Elliott, T. (1997). Predictors of Advertising Avoidance in Print and Broadcast Media. Journal of Advertising, 26(3), 61-76.

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