Add Human Touch to AI and Machine Learning Mobile Applications

According to the outcomes as of September 2017, the quantity of applications in Google play store is 3.3 million and as of the Apple store is 2.2 million. Gigantic numbers I simply should state. The application store has turned into an untidy and packed spot simply like the nearby prepares. The challenge is higher than the most noteworthy which has driven the designers to build up the most elite things. Regardless of building up the best things, it can't locate the normal degree of focused group of spectators and get achievement in the market. This makes showcasing the application incredibly basic. The gleaming and glittery part is that we have an application for every single classification we name and despite what might be expected, we have more than anticipated applications for a similar class leaving us in a problem which one to utilize and which one to hurl off. On account of the AI and AI the advertisers are up to date of the continuous information to follow the group of spectators and their need and grow precisely what they need and what they will worship.

AI and machine learning helps in the curation of the data and using it in the most effective manner, whether it be on the part of the developers or the marketers. Well, the issue that exists and hinders the most is the availability of excessive data which makes it really complex as to which one to rely on and which one not to. AI has been literally the revolution in the mobile application development sector just like the internet was a revolution, just like mobile devices was a revolution back in the date. From the end of developers, they invest an ample amount of time in accumulating and processing data and from the end of the users, they also invest lots of time in getting the data they are actually in need of. This time, energy and effort can be saved with AI and machine learning. Now, this is from both the ends users and marketers.

1) Simplifying Piles of Data

Executives get stuck with a bundle of data faffing around to get the answers as to what is the age group of the users interested in the app? Who are the users generating the most revenue for the app? Which is the area these users are coming from? What should be the game plan to keep these interested users engaged? Features and functionality that can convert mere users into regular revenue generating customers? Generating this information will eat up lots of time, which actually should be invested in doing strategic planning.

2) Uplift User Experience

User experience till now was the way the user feels while using the app, the features, functions, ease, and smoothness. It's the journey of the user of the user with the app designed by the app development company. All those micro-moments that you get that put a smile on your face and its all because of the app. This will be possible when an app gets personalized according to the personal choice and preferences. Say for example you are a music lover, wouldn’t it be great if the app tracks the genre of songs you like and avail you with a list of songs of your type. You will be delighted and never want to abandon the app. AI and machine learning help the developers and marketers to make informed decisions and customize everything based on the users personal choice specifically home page of the app, the landing page of the app, user flow, in-app events and many more.

3) Competitive Advantage

With AI and AI, advertisers get the client understanding which causes them get to the pertinent clients at the right planning with exact message arriving on their gadget at their agreeable timings. Indeed, if your opposition isn't up to date of the equivalent, they may contact them at wrong planning or with an inappropriate message or may be to an inappropriate client on an entirety. Thus, you will get an upper hand with AI and AI.