Machine Learning Is Transforming Mobile App Experience In 2020 

by Guest Author on April 25, 2020

in Guest Posts

According to the Grand View Research, the cognitive research market is expected to exceed $12 billion by 2022. 

Machine learning is an incredibly growing concept today. Basically, it is a branch of artificial intelligence. Now, it is being used  in mobile app development to a greater extent.

Actually, machine learning can improve mobile app user experience in many ways. From finding the optimal route for the office, to find the desired product and schedule an appointment to the doctor easily. Besides, it can help us in many more ways. It can make human life better and can offer us various ground breaking applications and software solutions.

  • Advance Searches

With the help of mobile apps integrated with machine learning, you can optimize the searches and offer better and more contextual results. It helps in making searching more intuitive and stress-free for app users. Machine Learning analyzes the customer’s queries and prioritizes the results that matter most to an individual person.

Modern apps built by machine learning experts, allow you to collect information about your customers such as search histories and typical actions. You can also use this data to rank products and services and show the best matching search results. You can also integrate voice search and spelling corrections in your app.

Certainly this is why Forbes said – Marketing and sales departments prioritize AI and machine learning higher than any other department in enterprises today (40%)

  •  Envisage user behavior

With the help of machine learning applications, you can understand users’ preferences and behavior pattern by studying different kinds of data such as age, gender, location, search request, the frequency of app usage, and so on. This data helps you in enhancing the effectiveness of your app and marketing efforts. 

  • Personalize experience

As per Global Market Insights, the wearable artificial intelligence market will reach $180 billion by 2025. Machine Learning can examine various sources of information such as social media activity for credit ratings, and pop recommendations right onto customer devices. It can help you to classify the users on the basis of their interests and collect user’s information. It can help you finding the answer of following questions:

  • Who your customers are?
  • What do they want?
  • What can they afford?
  • What are their hobbies and preferences?
  • What words are they using to talk about your products?

By collecting all this information, Machine Learning can help you in classifying and finding an individual approach & personalize information for each group. Machine Learning helps you in providing your users with the most relevant content and conveys the impression that your app is really beneficial to them.

  • Relevant Ads

Have you ever thought about what is the most difficult part of advertising?

The answer is: showing the right ads to the right person. While companies are striving to beat each other and reach a larger number of consumers, personalization is the only way to win the battle. Owing to this technology advertising has become more personalized, it helps companies in displaying messages more accurately.

Besides, it helps you to predict how an individual customer responds to the given promotions so you can show specific ads only to customers, who are interested in the displayed product and service. This saves time, money, and improves your brand reputation.

  • Improved Security

Indeed, it is the most secure way for app authentication through the audio, video, and voice recognition makes it possible for the customers to authenticate using their biometric data such as face or fingerprint.

Instead of fast and secure login, there are more applications for Machine Learning like you can count on ongoing app monitoring with no need of constant control, generally, apps can resist only known threats but Machine Learning systems can protect your customers from unidentified malware attacks in real time.

Banking and financial companies are also utilizing Machine Learning to inspect customer’s previous transactions, social media activities and borrowing history to determine the credit card ratings. Machine Learning provides various features like Image recognition, Shipping cost estimation, Product tagging automation, Wallet Management, and many more.

Important point developers must consider while developing app with machine learning:

  1. The more data provided to the machine learning algorithm, and more accurate are the predictions. It means software engineers should avoid subsampling and use all available data.
  2. It is important to consider the business model and production capabilities of the client while developing Machine Learning algorithms.
  3.  Take help from the data scientist to choose the right method and parameters for the best results. Improper data collection can change the prediction capabilities.
  4. Understanding the data features and improvement also have a high impact on succeeding learning processes and predictability.
  5. The success of the project is dependent on the appropriate Machine Learning method. Simpler the model, easier the learning process, and more accurate the predictions.

Now we know the advantages and ways to utilize Machine Learning but at this point, we are at the very beginning of the Machine Learning environment and to fully understand and unlock new potentials, it takes some more time.

Conclusion 

Machine Learning is the technology which is used in the app development process to provide the amazing user experience, various other technologies are also available like Artificial Intelligence, Blockchain, Beacons, and many more. You must choose the best app development technology according to your business requirement and it is the most difficult decision. Only the experienced mobile app development company can help you choose the best technology. 

Thank You!

Guest article written by: Shifa Martin

Comments & Leave a Comment

comments

{ 0 comments… add one now }

 

Leave a Comment

CommentLuv badge

Previous post:

Next post: