Articles

Machine Learning Concept in Mobile App Development

by Ashish Goyal Digital Marketing Analyst
No one likes a cookie cutter App nowadays. The Apps that are capable of personalizing the user pattern are selling like hot cakes and guess what they have 23% higher shelf life. If you are yet to unwrap what makes these apps capable to offer personalization of such scale, welcome to the world of Machine learning.

Machine learning gets its roots from Artificial Intelligence and that is what makes a Mobile App intelligent enough to learn. Mobile App Development landscape has been brewing with a lot of innovative ideas but the communion of Machine learning and Mobile App has proved to be a fantabulous idea.

Powered by Machine Learning algorithms that learn from the user engagement styles, these apps make optimal decisions to engage users. Hire App developers who have hands-on experience to make your App achieve the degree of intelligence that gets transformed directly into revenues. Machine learning has received a lot of traction from both users and developers and we are about to witness a massive growth of its use in future-proof Apps.

Every app produces a lot of data. By data, we mean frequency of App usage, timings of App usage and what kinds of searches or operations are done using the App. A Machine learning algorithm works in the background and identifies the patterns in this user-generated data.

Let us take the example of a food ordering App. The user tends to order desserts and cakes. The machine learning algorithm identifies the order frequency and likewise places desserts on top of the menu. It ensures that the user does not have to find his choicest desserts again and again in the exhaustive menu.

How can you use Machine Learning in Your Apps?

Apps and Machine Learning have a common objective. Both are intended to improve the user experience so the course of both coming together was natural. Let us dive deep to know how we can use the Machine learning to make users feel special:

Advantage of Personalization

Have you browsed the Amazon Mobile App? The App somehow seems to know what your likes are. This has been made possible by Machine Learning powered recommendation engine. The recommendation engine is a brilliant tool for eCommerce stores to enhance the sales by offering a suggestion based on the user’s interests. Today when an enterprise goes for Mobile App development, AI has become a part of the package as it increases the chances of cracking a deal by 37%.

Faster search

A millennial App must be special, smart and fast. All you need to achieve all this is machine learning. Machine learning algorithms allow a user to set filters that are smart enough to narrow down the searches. As the filters are set right as per user’s pattern, the searches become fast and users love that speed. Such scale of advanced feature ensures the user’s experience better buying journey as the time spent on finding the right product is shortened.

Increase the downloads

A smart App that recommends, offers precise predictions of sales and trends and optimizes the product search garners a lot of attention in the market. As more users experience the advantage of using an AI-powered App, the download count is bound to increase. Today entrepreneurs hire web developers who can build Apps and websites that are driven by Machine learning algorithms and focus on enriching user experience.

Keep user interested

A user may continue to use the App only if it keeps the user interested in its services. The eCommerce Apps can take a huge advantage of Machine Learning by identifying the buying and interaction pattern of the users. Let us talk about an apparel e-commerce store App. The users browser and add a certain item in the cart but abandoned the cart. The Machine learning algorithm identifies the shopping patterns and tendency to buy during sales and works on the deals and offers the buyer a lucrative deal using a push notification that encourages him to buy from the cart.

Such kind of features keep the users engaged and ensure the App retains higher shelf life.

Face and Audio Recognition

Siri and Crotona are just a few examples of NLP, the subset of machine learning. The other machine learning algorithms can identify Face and audio to add to the security aspects of the App. Working in a real-time process, such Apps are proving advantageous to the users by the perspective of security and ease of use. Simple voice recordings are helping buyers find the right products on eBay’s latest App. Enterprises hire developers for Mobile App development that renders the advantage of personalization and intelligence to the same.

Fraud controls

Machine learning is an answer to the frauds that happen on Apps where the credit card details or personal details of the user are stored. The machine learning algorithms are designed in a way where they can identify any malicious attack on the user data. As the machine learning algorithm is self-progressive it learns every time it encounters something new and ensures the soft spot is covered forever.

Personal Apps

Around 250,000 Fitness Apps are available on the App Store and Play Store. Very few of them are powered by Machine learning and the ones which are the most popular ones. When you go for a mobile app development for fitness with machine learning, you are offering the users an element of personalization that makes them feel the App is their personal coach to fitness.

Customer service

Machine learning has delivered a major advantage in the customer service industry. Apps powered by bots are trending the most as they offer 24/7 customer service in a smart and efficient manner. With machine learning, the chatbot is involved in a continuous learning process that makes it easy for enterprises garner more traction.

To Wrap

Machine learning is an ideal way to future proof the mobile Apps. With an innovative bent, the developers can work efficiently to deliver an App that has a swift learning curve and that helps an enterprise grow.


About Ashish Goyal Innovator   Digital Marketing Analyst

22 connections, 2 recommendations, 65 honor points.
Joined APSense since, October 24th, 2018, From Jaipur, India.

Created on Nov 22nd 2018 05:29. Viewed 184 times.

Comments

No comment, be the first to comment.
Please sign in before you comment.