Customer Attraction, Interest, and Retention: Mobile Applications Thesis

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As with any other product, app developers and marketers need to employ the right strategies to engage potential customers and maximize the number of downloads. The AIDA model is an advertising tool, which demonstrates a consumer’s common decision-making funnel. First introduced in 1898 by Elmo Lewis, this framework has been used in various scenarios, particularly to assess the effectiveness of advertisements (Abdelkader & Rabie, 2019). The model serves as a tool to communicate with potential customers and decode the cues of their purchasing behavior. AIDA is an acronym standing for Attention, Interest, Desire, and Action, all of which are the primary cognitive stages one has to go through before making a purchase. The model functions on the assumption that the main aim of marketing is “to attract potential consumers’ attention, to increase the consumers’ interest and desire to do the last act” (Pashootanizadeh & Khalilian, 2018, p. 639). Therefore, an efficient ad worth the investment is the one that minimizes the time gap between the first stage (attention) and the last one (action).

To explore the factors influencing potential users’ engagement in the application’s “download funnel,” it is important to examine each of the cognitive phases of AIDA in detail. Attention refers to the awareness of a customer, which means that the product should be designed and promoted in a way that the customer easily becomes aware of it and its unique features (Stepaniuk, 2017). Thus, the purchasing funnel starts at a point where a person does not even know about a certain brand’s existence (Pashootanizadeh & Khalilian, 2018). For app developers and promoters, this means that they have to integrate attention-grabbing strategies into their marketing activities, including triggers such as social proof, unique selling proposition, and the influence of authority. Apart from relying exclusively on the benefit of the application itself, it is thus crucial to display the number of downloads it already has or the ranking it has in various categories.

Interest implies a potential customer’s effort to collect more information about the product or service they have recently found out about. Therefore, it is the task of marketers to ensure there is a concise message, which explains the application’s benefits (Pashootanizadeh & Khalilian, 2018). For example, the advertising team of the app can include a segment that shows how it solves a person’s problem. The task is to show the advantages through key features instead of relying on the technical characteristics and nuances only. The next stage is desire, which refers to “the extent of the individuals’ intentions and decisions to purchase the advertised products” (Abdelkader & Rabie, 2019, p. 1695). Stepaniuk (2017) notes the importance of this phase to demonstrate how the service or product will fulfill a person’s need. The primary challenge during the Desire stage is possible hesitations expressed by customers. Thus, it is crucial to deploy social proof triggers and emphasize the solution the app entails. The final phase is Action, which implies deliberate actions of marketers to finalize the cognitive process and ensure the purchase is made (Pashootanizadeh & Khalilian, 2018). In the context of app promotion, it is important to explicitly urge potential customers to download or remind them to take a specific action indirectly otherwise.

The focus of app developers and marketers should not be solely on attracting new users, but on continuing the “download funnel” to include retention. Thus, customer acquisition costs must remain lower than the profits generated by the existing consumer base. Through in-app e-commerce for already registered users, developers can ensure high re-engagement and re-install rates. To facilitate the best in-app customer experience, developers have to ensure that the product they launch is user-friendly, including its grid, menu, and browsing options. Zare et al. (2020) note that the data mining technique is an efficient tool to predict consumer behavior to then enhance the commercial model as well as consumers’ decision-making processes.

Maintaining high retention rates is an essential factor, which determines the success of any business, particularly an app that requires relatively low commitment. Concepts associated with retention and re-engagement include responsiveness, convenience, cultivation, customization, and serviceability, according to Kumaran (2020). Based on the ideology of relational exchanges, Das et al. (2018) emphasize that customer relationship management practices are integral to ensuring retention and satisfaction. Therefore, the key objective of a product owner or marketer must be to successfully adopt appropriate customer relationship management strategies to manage the consumer lifecycle efficiently.

References

Abdelkader, O. A., & Rabie, M. H. (2019). Exploring the general awareness of young users according to AIDA model applied to social networking ads. Journal of Theoretical and Applied Information Technology, 97(6), 1693-1703. Web.

Das, S., Mishra, M., & Mohanty, P. K. (2018). The impact of customer relationship management (CRM) practices on customer retention and the mediating effect of customer satisfaction. International Journal of Management Studies, 5(1), 95-103.

Kumaran, G. (2020). A study on customer retention in e-commerce business. Journal of Xi’an University of Architecture & Technology, 12(9), 575-579. Web.

Pashootanizadeh, M., & Khalilian, S. (2018). Application of the AIDA model: Measuring the effectiveness of television programs in encouraging teenagers to use public libraries. Information and Learning Science, 119(11), 635-651.

Stepaniuk, K. (2017). Blog content management in shaping pro recreational attitudes. Journal of Business Economics and Management, 18(1), 146-162.

Zare, M., Shakeri, H., & Mahmoudi, R. (2020). Ecommerce: An efficient digital marketing data mining framework to predict customer performance. Journal of the International Academy for Case Studies, 26(5). Web.

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