How To Enhance Mobile Apps Using Machine Learning?

Machine learning is reshaping the whole business world today. It is making devices and applications smarter than humans, allowing them to make decisions on their own and provide a better experience.

It is expected that in the coming three years, the number of businesses investing in Machine Learning will get doubled (about 64%). Machine learning, on a global scale, makes mobile platforms easier to use, improves the customer experience, maintains customer loyalty and helps create consistent omnichannel experiences.

According to Allied Market Research, it is predicted that Machine Learning as a service market will reach $5,537 million in 2023 while growing at a CAGR of 39.0% from 2017–2023.

In this blog, we will look at some ways using which you can enhance your mobile apps via machine learning.

1) Advanced search functionality

The machine learning solutions allow its users to optimize the search in the application, offer better and more contextual results, and make the search more intuitive and less burdensome for the clients.

It is because the machine learning algorithms actually learn from customer queries and prioritize the results that interest a particular person. Moreover, Cognitive technology also helps to group DIY videos, frequently asked questions, articles, documents, and scripts into a knowledge graph in order to provide smarter self-service and immediate responses.

Modern applications allow you to gather all available information about your customers, such as search histories and typical actions. You can use this data along with behavioral data and search requests to rank products and services and ultimately show the best matching search results. Furthermore, you can update your application with spelling and voice search corrections.

2) More personalized experience

You can benefit from the continuous learning process with machine learning. Its algorithms can analyze multiple sources of information, from social media to credit ratings and top recommendations on customer devices.

Moreover, machine learning helps you classify and structure your potential customers, find an individual approach for each group of customers and adopt the tone of your content. In short, machine learning allows you to provide your users with the most relevant and engaging content and convey the impression that your application is really talking to them.

It classifies the users based on their own interests, collect this info and then decide on your app’s appearance. Furthermore, you can use machine learning for knowing the following:

-> Who your potential customers are

-> What your customers want

-> What they can afford

-> What they are searching for to buy your products

-> What preferences, pain areas and hobbies they posses

In fact, there are is a large number of marketers who are applying machine learning in all possible and imaginable ways. For example, Uber app comes under “transportation category” which uses ML to provide an estimated time of arrival, traffic conditions and cost to riders, offer real-time info in the maps to driver and more.

3) Relevant Ads

Showing the right ads to the right audience is the crucial part of advertising. As advertising is increasingly personalized, machine learning technology helps companies target personalized ads and messages more accurately. According to The Relevance Group(http://www.relevancygroup.com/shop/the-science-behind-customer-engagement), 38% of executives are already using machine learning as part of their data management platform for advertising.

Moreover, you can prevent customers from getting tired by pressing an item they just bought and probably do not need in the near future. Machine learning helps you generate ads based on data about each customer’s unique interests and purchasing trends.

It allows you to predict how a particular customer will react to a specific promotion so that you can show specific ads only to customers who are most likely to be interested in the product or service displayed. This saves time and money and improves the reputation of your brand.

For an instance, Coca-Cola follows closely how its products are represented on social networks. The company uses image recognition technology to identify when people have posted images of their products or their competitors on Instagram, Facebook, and Twitter.

4) Predicts user behavior

Machine learning helps marketers in understanding their user’s behavior patterns and preferences by analyzing different kinds of data viz. gender, age, search requests, location, the frequency of app usage and so on when they use any app utilizing ML.

However, you need this data as you can use it to keep different groups of clients interested in your application and improve the effectiveness of your application and your marketing efforts. Let’s suppose you discover that there are more women under 40 who use your application than men. According to this knowledge, you can take measures to attract a male audience or direct your marketing campaign to women.

Machine learning also helps create individualized recommendations that increase the client’s commitment and the time spent on their application. Let’s take a look at Amazon’s suggestion mechanism, for example. While customers browse, an automatic learning algorithm learns on the fly about their likes and dislikes.

5) More user engagement

Machine learning apps are found to be more engaging than other apps available on the store. The machine learning tools empower you to offer a range of endearing features, full customer support and give a reason to use these apps daily.

It provides sufficient support as it can easily analyze data and make real-time decisions. For assisting its customers, it provides friendly and intelligent digital assistants like AI chatbots, conversational UXs(voice assistants) for good communication.

Besides these chatty AI assistants, there are riddle bots which sends clues and knotty riddles if you get stuck while solving complicated puzzles. Snapchat is another good example which uses machine learning and augmented reality to allow its users to revamp their pictures with amazing filters.

Moreover, Machine Intelligence allows you to improve your application with a built-in translator since machine learning supports voice translation in real time.

6) Improved security

Being an effective marketing tool, machine learning can also optimize and ensure the authentication of the application. The recognition of video, audio, and voice make it possible for customers to authenticate using their biometric data, such as the face or fingerprint. Machine learning also helps you determine access rights for your customers. It is a smart decision for any type of mobile application.

Applications such as BioID and ZoOm Login make use of machine learning to allow customers to easily log in to other websites and applications with ultra-secure face authentication and selfie style. BioID even offers periocular eye recognition for partially visible faces.

Beyond the quick and secure login, there are more applications for machine learning. With automatic learning, you can count on continuous monitoring of the application without the need for constant monitoring, machine learning algorithms detect and prohibit suspicious activities. While traditional applications can only withstand known threats, machine learning systems can protect their clients from previously unidentified malware attacks in real time.

Much renowned banking and financial companies are also leveraging machine learning algorithms to inspect clients’ past transactions, social networking activities, and loan history and to determine credit ratings. In fact, ML opens up access to various impressive features viz. wallet management, shipping cost estimation, logistics optimization, BI etc. that allow brands to efficiently forecast any financial crashes or bubbles.

Conclusion:

So far we have seen how you can refine your mobile app development using Machine learning. In fact, machine learning technology can enhance your mobile application with an efficient personalization engine, state-of-the-art search mechanisms, fast and secure authentication and protection against fraud. Hence it is advisable to you to strengthen your business with a mobile application based on machine learning if you want to differentiate yourself from your competitors.

How To Enhance Mobile Apps Using Machine Learning? was originally published in Hacker Noon on Medium, where people are continuing the conversation by highlighting and responding to this story.