In 2019, mobile applications will become more personalized and user-oriented, they will have a simple design and a lot of artificial intelligence. The number of smartphone users by the end of 2019 will reach 2.5 billion, and the ever-growing number of applications in Google Play and the Apple App Store makes mobile development one of the most dynamic and competitive sectors.
In mobile development, the rules of the game change more often than updated smartphone software. Given the increased expectations of users to the functionality of the application, its security, and privacy, next year will make adjustments to the activities of mobile advertisers, publishers and application developers.
It is more important than ever for mobile developers to break through the white noise and capture the user’s attention while maintaining a positive experience of using the application. You can read about the most interesting applications here.
We left out the blockchain, crypt, and virtual reality, and identified universal mobile technologies that should be implemented in the application to make a profit in 2019.
The evolution of machine learning and artificial intelligence
Application revenue from the introduction of artificial intelligence (Artificial Intelligence, AI) in the world market is constantly growing and will exceed $ 100 million by 2025. According to Gartner research, the 200 largest companies in the world are actively implementing and relying on machine learning data.
Mobile applications can use artificial intelligence to understand the user’s behavior and provide him with more personalized recommendations. Machine learning based on data will automate tasks to eliminate the human factor and analyze a large array of data with minimal human involvement.
A great example of an AI-based mobile application is the Lark fitness app. This is a smart chatbot application that tracks physical activity and, using user-entered data about its daily routine and dietary habits, makes recommendations based on data. This data is obtained from world leading health and nutrition experts. Read about other useful applications on this site.
Machine learning is very useful in health care, logistics, IT, education – wherever there is a lot of unordered data. And the development of applications based on AI helps to release the support command of the application from the routine – after all, the chatbot can respond to all typical requests.
Another example is the AlphaGo game, which is based on the general principles of machine learning and was able to beat the world’s strongest go player. During the development of AlphaGo, the authors used only the most elementary theory of the game of go, the program reached a high level of the game, learning by itself at parties of professionals. The development team plans to apply the experience of AlphaGo to develop medical diagnostics.
Instant Android Apps
The idea of instant apps is finally gaining momentum. Thanks to this technology, users can access the application functionality without downloading it. For users, the benefit is obvious: the concept of “try before you buy” will allow them to save time on reading reviews, and try the features of the application themselves.
Google Play plans to save memory in smartphones in this way. But one of the problems is that instant applications work correctly with applications without heavy graphics. Heavy-duty games with great functionality can be difficult to experiment with instant applications.
Another hot topic of developer debate is how the introduction of instant applications will affect advertising monetization. They can increase the level of involvement at certain levels of the application, but negatively affect retention: if there is no need to install the application, the user rarely returns.
The low app access threshold and the “try before you install” approach ideally reduces accidental downloads and the number of users who have abandoned the app. So if you have an app with simple logic that weighs little, it’s worth testing Instant Apps.
Personalization vs GDPR
The IAB study showed that in different applications different times of peak user engagement, and therefore template advertising on them will not work. It is important for the advertiser to attract the user’s attention during his maximum involvement, giving him the opportunity to control the level of personalization.
Personalization in 2019 is as important as privacy. A Salesforce study shows that 65% of users believe that personalization increases their loyalty to the company. At the same time, users value data privacy.
This caused controversy in the online ecosystem: large companies like Google or Facebook were asking for personal information in order to “provide a better user experience.” But the GDPR rules now oblige to explain to users what data and why the company collects and give them the choice to refuse to collect cookies or allow the system to know itself better.
The developers are confident that GDPR will not harm personalization, and it will remain the current trend of 2019.
Need of Chatbots
It allows users to schedule and bulk-send interactive and engaging content, offers, and campaigns to Facebook Messenger contacts. The chatbots created via Monkey can be designed to make appointments, answer FAQs, track purchases, and use A.I. to match content to intent via keywords and interactions. For example: MobileMonkey is a Facebook messenger platform that lets you build chatbots on Facebook Messenger without writing any code.
The emergence of new ways to monetize
The volume of the mobile advertising market is estimated at $ 250 billion, so more and more developers are striving to monetize applications with advertising. But even applying all known monetization strategies, it’s unrealistic to get into 5% of the most highly profitable applications. Therefore, developers use unconventional ways to monetize applications.
Monetization of user data began to develop a couple of years ago and today is one of the fastest growing trends. Data monetization is the process of collecting and transferring non-personal user data to an intermediary. For applications with a DAU of 60,000 users, this option is an ideal passive income.
Monetization of data fully complies with the rules of the GDPR and Google Play Policy but requires the explicit consent of users before starting the data collection process.
UX: From hard to easy
Simplified UX helps users quickly navigate the app and find what they were looking for. The design of mobile applications must predict user behavior, be minimalistic, and take into account Swiping gestures in order to provide a holistic experience for application users. And with the development of Google Pay and Apple Pay, it is desirable to add the ability to pay with a virtual card.
Remember the sensational redesign of Snapchat: some time ago they changed their recognizable interface of the application and took more space for user content and advertising. The reaction of users to the new features of Snapchat was terrible: they claimed that the new Snapchat was more difficult to use, and then signed the petition to return the good old design. In the end, the team from Snapchat had to return everything as it was. Snapchat took a step back in terms of design but was able to retain user loyalty.
The game design also strives for maximum simplification. If we are talking about a small game, then a good design without distracting elements will look like this:
Enhanced Mobile Application Protection
Two years ago about 75% of mobile applications failed to pass even basic security tests. This means that in the process of creating an application, the developer usually does not test the application for potential vulnerabilities. Errors made during the application development process can directly affect the reputation and destroy the application after launch. The most common mobile security vulnerabilities are weak server-side controls and vulnerabilities in protocols and hardware.
By the end of 2019, security is expected to increase in Android and iOS applications, but alas, there are still a lot of low-quality applications in both application stores.
Don’t expect to get lucky —check the app for security gaps. A list of convenient application verification tools includes ZAP, Micro Focus, Kiuwan, and many others.
By the end of 2019, mobile applications will become even more personalized and user-centric. This is largely due to simplified application design, AI, and machine learning. It is necessary to remember about the security of the application for users: be sure to test it for vulnerabilities. Do not allow inattention or desire to save to eliminate all development efforts.
New ways of monetization with proper usage can give a real increase in the profitability of the application, which can be invested in its further growth and development of new chips.