Essay: The effect of product appearance on consumer preference: mobile video games in the Apple App store

INTRODUCTION
The video gaming world is changing rapidly to new mobile devices. In 2014, Forbes declared a $25 billion in value (42% increase over 2013) and predictions show it could reach $40 billion within three year . Mobile applications (app) are one of the fastest-growing segments of downloadable software marketplaces. The Apple’s App Store have arisen and grown rapidly in a short extent of time. Since Apple’s App Store (henceforth, AppStore) released with only 500 apps and a dozen designers in July 2008, the market increased extremely and over 337,000 games are available in March 2015 . Over 235,000 games are accessible for free and approximately 102,000 games are paid apps.
The purpose of this study is to examine the effect of the apps characteristics on consumer preference, since this can give valued insights for new marketing strategies for the mobile game industry. In literature, product appearance is formulated in relation with consumer preference discussed completely. In fact, the appearance a product determines consumer’s first impression of the product and rapidly can connect product benefits. Adding to that, the appearance of a product will make consumer implications about numerous attributes (Creusen, M. & Schoormans, Jan P.L. 2005). Consumers purchase decisions are determined by price perceptions rather than by real prices. These perceptions are very subjective and vulnerable to contextual influences. Various pricings are used to effect consumers’ price perceptions, presumptuous that they will influence the consumer preference (Danziger, S. et al., Oct 2014).
While several reports forecast enormous growth potential for the mobile app market, little is identified about user intent to purchase paid apps. Value-for-money, app rating and free alternatives to paid apps were found to have a straight impact on the intent to purchase paid apps (Chin-Lung Hsu et al. Feb 2015). Besides paid apps, free apps are obtainable in bigger amounts. They can contain advertising as gainful alternative. People might not like in-app advertising; nevertheless the behavior makes it clear that consumers are eager to accept it in exchange for free games .
The influence of consumer reviews across apps in the same app category and suggests that companies’ online marketing strategies must be liable on product and consumer characteristics (Zhu, F. et al. Mar 2010). Research has been done on the influence of online reviews on mobile app sales for Android Google Play and Apple App store. The impact of online rating on app sales is larger under open environment (Google Play) than under closed environment. This suggests that consumer rely on rating more seriously when search cost is greater in the open environment (Liu C et al 2012).
With the release of smartphones, the global mobile app market has increased exponentially. Apple’s App Store and Google Play were utilized to investigate the common technological and gaming design structures of contemporary mobile games. Those are most popular with the gamers, and also to examine similarities, and differences among the tablet computer games and popular smartphone. The results demonstrate that popular mobile games enlarge player’s touch-based enjoyment (i.e., swiping, sliding or drawing) (Kim H. 2013). These features can have, in all likelihood, a relationship with consumer preference.
By previous described influence, there might be variances in app characteristics that can influence the consumer preference. For this reason, a major part of this research is focused to answer the main research question of this paper: What is the effect of different app characteristics in the Apple App store to the consumer preference for mobile video games? This needs to fill the gap in the existing literature. This gap is the relation of pricing, review rate, ranking and the size of the publisher in relation to the consumer preference. The outcome of these relationships can have valuable finding, which can be used to advise companies for developing effect new mobile game marketing strategies.
This research contributes for new marketing strategies for new games on the IOS platform, since the Apple App store reaches a bigger and different audience. Different aspects influencing the consumer preference and the gaming genre of the apps is by far the biggest group of apps downloaded today. The consumer preference will be researched by several four different variables with all own attributes. The different variables are researched separately, but never researched as being attributes. Therefor this can give valuable findings for developing a marketing strategy for introducing new video games on mobile devices for Apple App store.
The theoretical base of the topic will be clarified on the basis of the current literature. The hypotheses described here will be tested with a consumer survey and analyzed by using a conjoint analysis (CA). The consumer preference is reported and results are discussed.
RESEARCH BACKGROUND
There are a lot of motives for marketing companies to perpetrate themselves insights in the consumer preferences. As explained, the app characteristics have an effect in the direction of consumer preference. To assure the correct definition of the variables used in this research paper, the definition and a detailed explanation about the variables are described including the relation to one another.
Game sales revenue is the motivation for game companies. Top-ranked paid app for iPhone (smartphone) generates 150 times more downloads compared to the paid app ranked at 200. Likewise, the top paid app on iPad (tablet) generates 120 times more downloads compared to the paid app ranked at 200 (Garg. 2013).
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The hypotheses to test will relate to the pricing, review rate, ranking and size of the publisher and the moderating effect of price sensitivity.
Pricing
A few pricing methods being used today. There are four big different types of pricing methods examined in this research. There are paid apps, free with ads, free with subscription, free with in app purchases or entirely free with no earnings. Paid apps offering a free version are called ‘freemium’. In general, a combination of the words ‘free’ and ‘premium’, is a business model by which a service or a product is offered free of charge, but a premium is charged for advanced features, functionality, or related products and services (Hayes 2008 p.195). It has become the dominant business model among Internet start-ups and smartphone app developers. Users get basic features at no cost and can access richer functionality for a subscription fee. Networks like Linkedin, shared files in Dropbox, or searched for a mate on Facebook are all examples of successful freemium based companies (Vineet. K, 2014). Another business model is to offer the app for free and integrate advertisements. A popular way to make a free app generate profit is by including advertisements in the app. These are small ads displayed on small displays of smartphone. Within the apps the ads are displayed in forms of banners or as a pop-up (Gupta, S. March 2013). Apps with subscription are free to use if personal details are provided. In-app purchases are payments that can be done within the free apps. App demand increases with the in-app purchase option wherein a user can complete transactions within the app. (Ghose,A. et al. Jun 2014). Currently the mobile game apps having which are top grossing are all apps with in-app purchases . For that reason I propose that the following hypothesis is related to the consumer preference:
H1: There is a positive relationship between free apps with ads and consumer preference for mobile video games in the App store.
Review rate
Consumer characteristics influence of online consumer reviews on product sales, researched using data from the video game industry. The findings indicate that online reviews are more influential for less popular games and games whose players have greater Internet experience. Therefore online reviews influence the purchase decision (Zhu and Zhang 2010). The amount of people who joined in rating inherently provides information about popularity of the product (Chen and Xie, J. 2008). With these perceptions, the following hypothesis is described:
H2: There is a positive relationship between high review rate and consumer preference for mobile video games in the App store.
Effect of review rate will be stronger for lower ranked games on consumer preference.
Ranking
Another interesting unique independent variable is ranking. Past purchases of other consumers, as summarized by bestseller lists, affect consumer demands. The information available to consumers about the past sales ranks of the products sold in a large electronic market has a direct and causal effect on current sales. Indicate that popularity begets popularity by showing that information about the past popularity of products is an important determinant of future popularity. The demand for the most popular item is different from the demand for the other popular items. Intuitively this is so, but the question of how a product’s bestseller rank affects future demand for that product appears to have eluded researchers (Carare, O. Aug 2012). Therefore, I suggest the following hypothesis with regard to the consumer preference:
H3: There is a positive relationship between a higher ranking and consumer preference for mobile video games.
Another interesting independent variable is the size of publisher. Blockbuster PC games are mostly developed by big publishers. The results consistently show that blockbuster video games are more likely to be released by on of the major publishers for popular hardware platforms (Cox, J. 2014). Taking into account that the size of the publisher has influences on consumers, I propose the following hypothesis:
H4: There is a positive relationship between a big publisher and consumer preference for mobile video games in the App store.
Attractiveness
As a moderating effect on these (in) dependent variables and the dependent variable f consumer preference, attractiveness is chosen. Findings for the music industry indicate that advertising-based models have the potential to attract consumers who would otherwise refrain from commercial downloading, that they cannot threaten the dominance of download models like iTunes, and that current market prices for subscription services are unattractive to most consumers (Papies, D. et al. 2011).
H5: The attractiveness moderates the relationship positively between the presentation of apps and the consumer preference.
The relationship between, the independents variables app characteristics and the dependent variable consumer preference and the moderating effect of attractiveness is explained and visualized in a conceptual model (figure 1).
H1
H2+
H3+
H4+
Figure 1 Conceptual model
Within the presentation of the app each independent variable includes attributes. Pricing includes: paid apps, free with ads, free with subscription or free with in app purchases. The review rate varies between one and five stars. The ranking is the number of total downloads compared to all other apps. The developer indicates whenever a small, medium or big size developer made the app. The attractiveness of the options presented by each survey question moderates the relationship between the product appearance and the consumer preference positively.
RESEARCH DESIGN
The research design will consist of a survey and the results will be investigated performing conjoint analyses (CA). For investigating the relationship of these app appearances (attributes) to the consumer preferences, a conjoint analysis is suitable. Conjoint analysis is frequently employed for such measurement (Halme,M et al. 2014).
Comparing the independent variables described above is done in four levels that are combined in the conjoint analysis. They are as follows:
Pricing method: Paid, free with ads, free with subscription, free with in app purchases
Price: less, ‘ 0.99, ‘ 1.99, ‘ 4.99, More
Review rate: 1 star, 2 stars, 3 stars, 4 stars, 5 stars
Publisher: small, moderate, big
The effect of these attributes influencing the dependent aspect, which is the consumer preference of an app.
Multi item scales are used during the conjoint analysis. (source Malhotra)
Assignment of participant’s conditions
‘ Random Apple users.
To construct the validity of the research a few methods are done. Pre-test measures are done by a few participants to guarantee the quality of the research hand confirm validity. Manipulations checks are done to identify if participants are aware of the app features of games in the App store.
The Apps store is overall well known under IOS users. The outcome of the relationship between app game features and consumer preference gives a good generalization view of what actually happens. The survey and conjoint analysis wil be mostly adapted to students using IOS devices. This research contains external validity for all consumers in this specific group.
REFERENCES
Carare, O. (Aug 2012). The impact of bestseller rank on demand: evidence from the app market. International Economic Review. Vol. 53 Issue 3, p717-742.
Chen, Y., Xie J. (2008). Online consumer reviews: Word-of-Mouth a new element of marketing communications mix. Management Science, 54(3), 477-491
Cox, J. (2014). What Makes a Blockbuster Video Game? An Empirical Analysis of US Sales Data, Managerial and Decision Economics 35 pp. 189-198
Creusen, M.,Schoormans, Jan P.L. (Jan 2005) The Different Roles of Product Appearance in Consumer Choice. Journal of Product Innovation Management.Vol. 22 Issue 1, p63-81.
Danziger, S. Hadar, L, Morwitz, V. (Oct 2014) Retailer Pricing Strategy and Consumer Choice under Price Uncertainty. Journal of Consumer Research. Vol. 41 Issue 3, p761-774. 14p.
Garg.R, Telang. R, (2013). Inferring app demand from publicity available data. McCombs School of Business, The University of Texas at Austin.
Ghose,A. Sang.P.H, (Jun 2014) Estimating demand for mobile applications in the new economy. Management Science, Vol. 60 Issue 6, p1470-1488.
Gupta, S. (Mar 2013) For Mobile Devices, Think Apps, Not Ads. Harvard Business Review. Vol. 91 Issue 3, p70-75.
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Hayes, T. 2008. Jump Point: How Network culture is revolutionizing Business McGraw-hill.
Hsu, C.L.; Lin,J. C.C (Feb 2015). What drives purchase intention for paid mobile apps’? An expectation confirmation model with perceived value. Electronic Commerce Research and Applications, vol. 14, 1, 46-57
Kim, H. (2013). Mobile Media Technology and Popular Mobile Games in Contemporary Society. International Journal of Mobile Marketing, 8, 2, 42-54, Mobile Marketing Association
Kumar, V. (May 2014). Making ”Freemium” work. Harvard Business Review., Vol. 92 Issue 5, p27-29. 3p. 1 Color Photograph, 1 Illustration, 1 Chart, 1 Graph. Database: Business Source Premier
Liu, Z., Au Y.A., Seok. C.H. (2012). An Empirical Study of the Freemium Strategy for Mobile Apps. Information Systems and Cyber Security, University of Texas at San Antonio, TX, United States.
Papies, D., Eggers, F., & Wl??mert, N. (2011). Music for free? how free ad-funded downloads affect consumer choice. Journal of the Academy of Marketing Science, 39(5), 777-794
Zhu, F., and Zhang, X. 2010. “Impact of Online Consumer Reviews on Sales: The Moderating Role of Product and Consumer Characteristics,” Journal of Marketing (74:2), pp. 133-148.
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