Machine Learning For Mobile App Development Service

Almost, every service provider represents their business or services through online mediums. Mobile apps are the most common source. Today, the online systems world is dominating by various new technologies. Machine learning is one of them. There is hardly any business sector that is not using ML.

To benefit the tremendous part of the society- the customers as well as the owners; the developers are now using machine learning in mobile app development services. The main reason is that they need faster growth, accelerated revenue, low latency rates. To facilitate these benefits, experts are using ML for different sectors globally. 


What Figures say for Machine Learning Technology?

Because of this technology-

  • 38% of officials are using it for the Data Management Platform (DMP) for advertising- Data revealed by a report of The Relevancy Group.
  • The worth would reach $9 billion by the end of 2022- As per CAGR
  • By the next three years, the number of people investing in technology would doubles. 
  • Almost 2/5th sales and marketing companies of the United States are using it.
  • More than 3/4th companies have accelerated sales in the US.
  • 10% of sales of European banks go up 

Where Machine Learning Can Be Applied- The Important Areas

There are distinct areas where the ML is being applied to develop various different mobile software. Read the blog to locate your business type. 

Ecommerce Apps– The most important part of the mobile solutions world- e-commerce. Due to the easy availability of the Internet, users now prefer to get things shopped from online eCommerce solutions. Usage of Machine Learning with e-commerce solutions is helping the users to get the desired result quickly. As per the user’s preferences, this technology can recommend the products easily that further results in the enhanced user experience. This is also named as product recommendation. For example- 

  • Amazon- e-commerce giant is using machine learning that analyzes how the user is navigating, buying products, clicks on different types of products. This whole data is used by the ML to recommend additional products to the clients. 
  • Netflix- It offers the results after analyzing the data in three different ways.
    • The user’s preference list
    • The watched stuff in the past time
    • Trending Videos

The suggestions are according to the user’s likings and prompt you about it. 

Weather Apps– Another well-known source that is helping people to know the weather conditions of a specific place. By fetching the current location of the user, ML can help the users to know the current as well as future weather of a certain location. A lot of owners are using mixing up the technology with the services. 

How ML Can Help Food Delivery Applications or Restaurant Apps– One of the most used applications in the smartphones- food ordering apps. To stand out of the line, almost every food owner prefers to add some exciting features embedded with the new technology. Through personalized experience, it can easily help users as well as service providers. As online solutions can be linked with other social media options through which the owner can get an idea of the user’s likings. 

Likewise, examining the previous orders is another way that is used to show the best food items while searching. The inbuilt structure helps the customers by offering suggestions or results exactly as per the user’s need. It helps them in the way that the app is like talking to the users. Therefore, you can expect an advanced level of experience. 

How ML is Helping Finance Applications– First of all, the online solutions have replaced the manual works that have enhanced the productivity and automates repetitive jobs. 

Security is the main concern for firms dealing with finance-related tasks. Similarly, the online solution needs more secure ways to protect the transactions, etc. Generally, these types of systems require biometric data to secure it from unauthenticated users. It may include the usage of face or fingerprint.

The application without the use of Machine Learning can stop the known threats but the new technology deployed in finance systems resist hackers, viruses, etc and even can ban suspicious activities too. Therefore, reputable banking and financial companies are using the ML to detect the prior sale or purchase history, social media and to manage credit ratings, etc. The main features may include-

  • Estimating the shipping cost
  • To manage the Wallet
  • Business intelligence

These features enable service providers to predict future trends, bubbles, and financial crashes.

ML Embedded Application for Transportation Business– People involved in the transportation business are looking for developing mobile solutions for their business. This trend goes up after the implementation and success of Uber-like online options. Now, this technology is helping users. Let’s have a look, How? 

Whenever you book a vehicle through online solutions it shows the expected arrival timings as well as the expected journey timings after tracking the real-time location of the vehicle as well as the place of the customer. All become possible the technology. Therefore, ML made it possible to estimate the timings for any kind of business priorly. Google Maps is also using it. 

How Machine Learning Is Helping Healthcare Applications- Another major industry taking advantage of technologies to ease medical services. ML has efficiently combined the medical expert’s information and different treatment methods that improve reliability. For diagnosing the medical or healthcare issue, to personalize the medicine schedule, and to evaluate the amount of exercise done or calories burnt or taken in a day.

Our developers have developed various healthcare app solutions.  Recently, we are working on HealthApni– an online solution that helps people in entering the medical history of an individual securely. It has scrapped the usage or carrying of medical reports papers.

And Finally…

Algorithms of Machine Learning mobile app development has enhanced the UX, improved data security and accelerate the customer’s engagement in various services. This is the reason, numerous mobile solutions are working on this technology- Netflix, Snapchat, Google maps, etc. Do you have any query in your mind related to your business or this technology? Yes! Let’s discuss your business thoroughly, and make strategies for your online solution.