It is sometimes said that the golden rule of customer service is to make the customer feel valued. When customers feel important and appreciated, they are more likely to remain loyal to a particular business or brand. The same is true of the mobile industry: customer loyalty is paramount to the success of app developers, device manufacturers and network providers. But in a world where more than 6 billion people own smartphones, making each individual user feel both cherished and unique is a challenge.
In recent years, a primary focus within the industry has been on how to create the most individualized smartphone experience. According to research by customer engagement platform Twilio, 62% of consumers say they expect personalization and a brand will lose their loyalty without it. An additional 49% of consumers say they will become repeat buyers/users if personalization is offered. Personalization in the mobile industry is also evolving. More and more, the emphasis has shifted toward hyper-personalization, which differs from the former with regard to the use of real-time data, AI and predictive analytics as opposed to historical customer data to facilitate a totally tailored user experience.
The race toward delivering the most hyper-personalized smartphone experience is intensifying. Companies are increasingly exploring innovative ways they can engage with users on a greater personal level. For example, streaming services like Netflix have been pioneering in making personalization a customer norm. Netflix uses vast quantities of data and AI algorithms to ensure its viewing recommendations successfully match the thought processes of users. It is anticipated that content providers will achieve even more symbiotic user relationships in the future by personalizing the users experience of the product itself. Rather than relying on basic information such as viewing history or purchasing history, user-entered preferences and the time of day, content providers will explore advanced tools like facial recognition software that can decipher users’ emotions to make highly accurate recommendations. Another potential format would be responsive content, which reacts to users in real-time, potentially altering or fast-forwarding content to keep the viewer’s interest.
Granular user insight is already being effectively used by fintech apps to disrupt the financial services industry. In developing economies especially where there is less of an entrenched physical banking system, finance apps have been employing hyper-personalization techniques to great effect. For example, Fintech Magazine highlighted how Indian payment service provider Mobikwik experimented with customer segmentation based on due dates for utility bills with triggered reminders to help them pay the sum on time via the app. MobiKwik also reported it had doubled its user engagement and grew user retention by 20% after introducing an automated welcome campaign that guided users through key app features that would be useful to them.
Health & wellness apps are also at the forefront of using granular level data to accomplish hyper-personalization. For example, several leading apps are offering customized streaming workouts that take into account the most detailed health and fitness data of individual users. More diet focused apps can create nutritional profiles and tailor recipes that are based on everything from daily movement and lifestyle to hormone profiles and even a user’s current emotional state.
An interesting aspect of the global hyper-personalization drive is visible not just in the progress made by app developers. Device manufacturers are also instrumental in facilitating a customized smartphone experience because of the role they (and mobile operators) play in app discovery. In this area, partnerships between app developers and third-party discovery platforms have been critical (in the interests of full disclosure, I am the CEO of one such platform). Such partnerships have served to broaden an app’s reach, enhance brand awareness and grow customer satisfaction by providing personalized recommendations and real-time insights into user behavior, which help improve app functionality, security, and the overall user experience. Furthermore, OEMs and operators will continue shaping app discovery, for example, with application streaming. Still relatively novel, app streaming allows users to explore bigger and more complex applications without having to download all features. Instead, a basic version of the app could be downloaded with on-demand features installed when required.
The majority of leading brands are already employing aspects of hyper-personalization in their marketing strategies. We can expect major improvements in the hyper-personalization techniques used as data collection and processing becomes faster, in addition to big technological advances. All the signs point toward hyper-personalization ubiquity in the future, which means that is essential for brands to consider how they will stay ahead of their competitors and stand out from the crowd. Investing in the latest technology for customer data-driven decisions and recommendations is vital. As mentioned, a key way of doing this is to partner with third-party platforms that have already invested heavily in this area. Finally, be prepared to continually experiment with different approaches and to adapt accordingly. Not only will hyper-personalization be universal, but it will continuously evolve. Just as consumers’ lifestyles, including their smartphone habits and spending trends, change over time, so will the ways in which hyper-personalization is achieved. In short, what works today may not always work tomorrow. The one thing we can be certain of is that the future will be hyper-personalized.
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