Over the past few years, the rapid growth of software technologies and tools has seen the proliferation of machine learning (ML) apps. Any enterprise mobile app developer will admit that there is nothing comparable to the buzz surrounding the real, tangible value of machine learning in mobile app development, and its promising potential in changing the entire app development ecosystem.
Today, Machine Learning experts and Data Scientists are the intermediaries between huge data volumes and business users. With the latter trying to extract meaningful intelligence out of this data, the ML experts are tasked with the role of creating AI apps and ML applications to facilitate this process.
So, what does this mean to mobile app developers and business owners? How can they incorporate ML into the development projects? How can machine learning be used in everyday life?
In this article, we will try to answer all these questions. And while at it, we are also going to look at the future of machine learning application in the mobile app development industry.
But First, What Is Machine Learning?
Simply put, Machine Learning is a computer science field that teaches computer systems “deep learning” by feeding them with data, with the expectation that they will make accurate predictions in the future.
Does AI Have Something in Common with ML?
No, it doesn’t. However, artificial intelligence (AI) is the younger cousin of ML, and its true power lies in its self-teaching algorithms. When exposed to huge data volumes, ML can study and learn all data patterns, and produce improved results.
The growing adoption of ML in the business world and development projects reflects the effectiveness of its algorithms, frameworks, and techniques in solving complex problems quickly.
True to this, a recent article published by Forbes estimates that one in ten businesses use an AI app in one way or another. This increasing adoption is largely driven by factors including the growth of next-gen computing architecture, open data, and deep neural networks.
In terms of growth, ML has made inroads in different verticals including automobile, assembling, finance, retail, etc. In fact, a study published by Statista predicts that The annual global revenue from ML enterprise software applications will grow at a CAGR rate of 52.59%, to reach $31.2B by 2025. Click To Tweet
Benefits of ML and AI in Mobile App Development
With every other enterprise looking to apply mobile apps to their business model, the overload in the machine learning services has never been more apparent. As a result, companies have had to deal with the dilemma of choosing the best mobile app developers to create solutions that help them retain customers and attract new ones.
Moreover, the ever-shifting customer’s loyalty and soaring expectations mean that they have to build and deploy more-customer-centric solutions if they are to remain competitive.
In this regard, business owners and app developers are quickly realizing that adopting mobile machine learning technology empowers them to build intelligent apps that can sense the customer’s pulse and provide a hassle-free customer experience.
Below, we have listed the benefits of machine learning for business owners and mobile developers.
Improves Customer Experience
Good customer experience is a valuable intangible asset for any enterprise. Without it, your business simply won’t survive in today’s competitive business environment.
In this regard, it is super-important for business owners to adopt creative ideas for mobile apps to ensure that customer queries are met. Chatbots are transformational customer experience components for any organization looking to improve efficiency as well as drive innovation for mobile devices, desktop, and B2C and B2B businesses.
By using ML-based Chatbots your business can provide 24/7 customer support without the need for a manual agent. Additionally, Chatbot develops themselves using users’ inputs, saving you tons of time & money in terms of the training costs.
Improves Security Level
Besides being an effective customer experience tool, ML also helps streamline and secure app authentication. Thanks to features like audio and image recognition, with the help of machine learning mobile applications, enterprises can easily use biometric data as security authentications.
Lloyds Bank has been using biometrics for safe login to their mobile banking app. It’s not only about security but about ease of use and user-friendliness.
Delivering More Relevant and Targeted Ads
By now, any business owner knows that the only way to remain competitive in this consumption-oriented environment is to personalize every aspect of their marketing. Unfortunately, most ‘late-tech-adopters/ are still using analogue marketing methods, and the idea of using technology is alien to them.
On the flip side, a recent report by The Relevancy group shows that 38% of marketing executives are already using mobile machine learning in their Data Management Platforms for advertising.
With the help of ML applications, businesses are able to consolidate customer data intelligently and generate ads that resonate with their customers and cater to their whims and fantasies. This is more effective compared to bombarding customers with products and services that they aren’t interested in.
Machine Learning Application Areas
Now, let’s take a look at some of the industries that have benefited the most from using technology.
One of the major beneficiaries of ML is the E-commerce industry. In particular, ML apps make product search in an E-commerce store super-easy by learning the user behavior through their search history. It also makes it trend forecasting and analytics easier, as well help detect and prevent fraud. Good examples of successful E-commerce apps that utilize ML include Amazon and eBay. eBay uses ML to provide shoppers with relevant and good deals. Predicting what the shopper wants based on their search history helps them increase sales and make the whole shopping experience better.
Using face recognition ML, skin neurons are able to easily detect skin diseases in patients. For example, the National Human Genome Research Institute has been using the tech to identify DiGeorge Syndrome. They detect and analyze facial features to see if the child is predisposed to having the disease. And using face recognition, the medical professionals can also prevent any mishappenings that may arise from the medications.
The finance industry is another area that has massively benefited from the ability of machine learning apps to predict future trends and analysis. In particular, ML apps help easily pick trends in customer’s transaction history and social media activities to develop a list of portfolio recommendations, as well as a credit rating.
The Future of Machine Learning in Mobile App Development
If the information above is anything to go by, the future of ML is undoubtedly bright. If you are a prospective mobile app developer or a business owner, you should be prepared to be at the forefront of developing ML-related solutions.
On top of making it possible to develop intuitive ML apps with minimum lines of code and on-device processing, many other compelling indicators showing that ML is the technology of the future.
For instance, by the end of 2020, it is forecasted that 97% of all mobile users will be using ML and AI-related voice searches. During the same period, ML startups funding will reach more than $2 billion, which is 3 times more compared to NLP.
The future of technical app development and business around that will heavily rely on ML and AI solutions. The technology’s ability to predict outcomes allows business owners and app developers to efficiently plan projects, develop, handle problems, and create customer-centric mobile applications that DO succeed. As such, apps that use machine learning will continue revolutionizing our lifestyle and make life easy, and enterprises looking to stay competitive should go for them without stretching time.
Let’s Develop ML-Based Mobile Apps Together
Have a great idea for an ML-based mobile app? Or already using a mobile application but want to elevate it with machine learning? Get help from our ML consultants and data scientists. Contact us at email@example.com.