How Can Machine Learning Revamp Your Mobile App?

In the past few years, Machine Learning has rapidly changed our lives with its efficient applications. Thi technology has given an uplift to the entire mobile industry. Making devices and mobile apps as intelligent as humans, machine learning is a crucial component of digitization efforts by businesses around the world.

The use of machine learning has led to the charge of developing, building, and using mobile applications. Embedding mobile applications with machine learning demonstrate immense benefits. And thus, many companies are investing heavily in machine learning to leverage their perk.

What stats speak? According to the latest mobile app survey, by 2023, the global machine learning as a service market is projected to reach $ 5,537 million.”

The implementation of Machine learning makes mobile apps smarter, thus offering a better user experience. There are countless examples of ML we see in everyday life. 

If you have ever watched a movie recommended by Netflix or listen to a Spotify song in "Discover Weekly,” then you’ve already had a taste of what machine learning can do to mobile apps, knowingly or unknowingly.

In this write-up, I will present different ways in which machine learning revolutionizes mobile applications. So, without wasting any more time, let’s get started!

Machine Learning: A Brief Introduction

Machine-learning (ML) is an interactive technology that utilizes the functionality of Artificial Intelligence and cognitive computing through a variety of algorithms. These algorithms are used to find patterns in vast amounts of data. 

Here, data includes a lot of things - numbers, words, pictures, clicks, etc.

Besides, Machine Learning offers secure authentication and protection from any kind of fraud. That's why most mobile app development companies in India are using ML algorithms in their mobile applications.

It powers many of the services that we use in our daily lives, for example:

  • Recommendation systems such as Netflix, YouTube, and Spotify
  • Search engines like Google and Baidu
  • Social media feeds such as Facebook and Twitter
  • Voice assistants such as Siri and Alexa. 

The Importance of Machine Learning in Mobile Apps

Machine learning offers attractive benefits for developing mobile applications. As per the recent survey, it is forecasted that businesses investing in machine learning will double (about 64%) in the coming years

Machine learning makes mobile applications more user-friendly, enhances the consumer experience, and maintains users’ loyalty globally. A report by Statista says that machine learning apps attracted $ 29 billion during March 2019.

What Does Machine Learning Offer in Mobile Applications?

Now, let’s have a sneak-peak into the role of Machine Learning in mobile apps and how it is transforming the app development.

1. Personalized Experience

There were days when any business's fate was decided by how well it met the needs and demands of its consumers. But now things have changed drastically. Today, market success is defined by the company's ability to predict customer needs and fulfill before the customer asks.

Machine learning can be the most helpful tool in this situation. With the use of ML algorithms and artificial intelligence, you can easily differentiate your customers based on their preferences and interests. This is where machine learning companies in India are coming to the front.

After using this information, recommendations can be popped properly on consumers' devices. In addition, you can get the user information and learn about it by using Machine language.

  • Who is your audience?
  • What do they need?
  • What are their preferences and pain points?
  • What words are they using to search your products?

After getting the above-mentioned information from users, you can use it to design marketing strategies for promoting products. The ML algorithm helps to find an individual approach that allows targeting each user from different groups.

Moreover, Machine Learning offers creative and alluring content making your mobile application more interactive. And because of this, AI in app development is a preferred choice by most of the people.

Machine learning provides creative and engaging content that makes your mobile app more interactive. Because of this, AI is the preferred choice by all app owners in app development.

2. Advanced Search

What do businesses need today? Today, companies are aiming to engage more and more users. It is necessary to attract customers, but retaining them is also crucial. And that can be accomplished if companies provide them with what they require. 

While companies work hard to engage their customers, users face difficult times in selecting the right product. If the searching process for the products is made simple, it can help engage more customers.

Moreover, a machine learning solution helps optimize search in the app and gives better results making search more intuitive. ML algorithms based on customer queries show refined results that mean the most to an individual.

Another significant advantage of using machine learning in mobile apps is that it uses "Cognitive Technology." It helps to group articles, DIY videos, FAQs, documents, and scripts into knowledge graphs that cater to smart self-service and instant answers.

3. More User Engagement

The ML algorithm helps determine your target users' interests, and it provides relevant advertising that brings the right information to your users at the right time. Apart from these, machine learning tools offer a variety of features that help to engage more users.

Compared to all apps available in the store, mobile applications that have been enhanced using machine learning are found to generate more user engagement. It can offer a broader range of functionalities, including real-time customer support. It inspires more people to use this app on an everyday basis.

Snapchat is a great example that has masterly used machine learning and augmented reality by enabling its users to change and redesign images through filters.

4. Relevant Ads

Did you know that 50% of enterprises are implementing machine learning to refine marketing issues? ML has made advertising more targeted with personalized and accurate messaging.

The Relevancy Group released a report stating that 38% of executives are using ML as part of their overall strategy for a Data Management Platform for advertising.

Machine learning lets companies stop pushing products and services that have recently been purchased by their customers. By drawing on individual customer's specific purchase patterns and interests, businesses can create targeted advertisements with the help of machine learning.

Predicting customer behavior is a tremendous benefit that can direct promotions through a series of specific communications where the probability of a sales conversion is at its highest.

5. Improved Security  

App authentication via video, audio, and voice recognition is a core functionality offered by machine learning. It enables users to authenticate app access through fingerprint and facial recognition technologies. 

Along with this, machine learning also streamlines user flow through simple log-in processes that are secure. Malware attacks for online retailers in Asia, Europe, and North America increased by 45% last year, resulting in a loss of US $ 3.3 billion.

Machine learning prohibits suspicious activities through early detection. Therefore, there is no need to continuously monitor or control the app against such unknown malware attacks.

Major banks and financial institutions worldwide are also leveraging machine learning technology to analyze transactions, lending patterns, and social media interactions for credit ratings.

6. Predicts User Behavior

Customer retention is critical for any business to succeed. To increase business profits, you need to follow practices to engage more users and retain them. To do this, companies need to analyze and predict user behavior. This ensures that you provide your users with what they need.

Machine learning makes it easy to understand user interests. That's why machine learning plays an essential role in app development. Machine learning applications help marketers understand users' preferences and patterns of behavior by analyzing different data types. It helps in locating user information which includes: 

  • Age
  • Gender
  • Location
  • Search requests
  • Frequency of app usage

But how useful is this data? Knowing more about your users and their preferences help in engaging more users. It improves the effectiveness of your mobile application and thus the marketing of your product. ML keeps track of users' liking, which increases user engagement and time spent on your mobile apps.

Do you know that about 80 percent of TV shows watched on Netflix are suggested by their recommendation system? It has helped Netflix save nearly $ 1 billion. Netflix uses machine learning and algorithms to discover shows that users initially selected at any point in time.

Top Mobile Applications that Use Machine Learning

 Just take a look at some of the best apps that have used Machine Learning to their advantage:

  • Snapchat
  • Netflix
  • Google Maps
  • Tinder
  • Uber
  • Spotify
  • Paypal

These are some of the most popular mobile apps that are using Machine learning algorithms. This technology is well-suited for any mobile business app that requires predictions and has a requisite data set.

Wrapping- up

Machine learning empowers mobile applications with sufficient customization features to make it highly efficient and worthwhile.

Thus, many companies lean towards machine learning technology to boost sales and growth of their firms and provide the best experience to users. 

Therefore, it will be an excellent idea to use Machine learning for your next mobile app development project. On this note, you can hire mobile app developers in India to build high applications with the alluring interface. They will surely help you to make your mobile apps stand out amongst the rest.

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Tags: dsc_ai_marketing, dsc_ml, dsc_tagged, learning, machine


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