Artificial Intelligence is redefining how we look at technology and use it, especially the mobile app industry. A lot of people have used this technology to improve the engagement level within the app, and increase the conversion rate for the business. We don’t have an Iron Man-like mobile app as of now but, we are constantly progressing towards making apps revolutionary, usable, and predictive. We are using predictive analytics’ engine, and other coding methods to enhance the mobile apps and make them more experiential.

There are many ways in which Artificial Intelligence has enhanced the mobile app industry. Here, we will take you through some of the ways in which the apps have been revolutionized and transformed with mobile apps.

1.     Personalization of Mobile Apps

Inspiring minds and influencing people can help enhance engagement. However, to make sure you are able to inspire the right minds, you ought to have insights that cater to their thoughts and help you understand them better. As a result, it is important for you to incorporate Artificial Intelligence into your apps.

This technology has transformed the way users use mobile apps, and engage with them. AI with deep-rooted learning techniques can easily understand what goes into a user’s mind, and mine the insights that help you offer better recommendations and a more personalized screen.

Netflix, which is a popular streaming platform, uses AI to help recommend programs to its viewers. This streaming platform tends to record the past views of the user along with their natural preferences. ML an integral part of AI, records these aspects, runs an algorithm to understand what the viewer likes most.

It then recommends programs based on their history and preferences. This personalization helps the user stay on the app for a longer time, and enables better engagement and conversion.

2.     Better Sales Forecasting

Want to know what will be in demand this season? For a long time, the one thing that most salespeople have been unable to define or properly manage is the demand. We are hardly aware of how the demand changes or evolves for the new year.

However, with Artificial Intelligence tied to your mobile app, you can easily understand the demand for a particular product. You will also be able to understand the demand for a new product you are going to launch. Let’s take a look at the how before we understand any further.

With sales, you are immediately turned to the number of the particular product that will be sold in a go. The forecasting for this particular number is quite difficult. Artificial Intelligence, in case of a known product, looks at past sales figures. It understands why the sale happened when it happened and how it converted into a sale.

Similarly, it will also look at demographic patterns for the sale and other aspects. Immediately, an Algorithm is built which helps forecast the sale for the product in the coming times. It will help understand the demand, which in turn will allow you to keep up with the inventory needs.

In the case of a new product, the trend of the product is observed for a period of a few days before deriving with finality the forecast for its demand.

3.     Retail Assortments

When you apply AI to retail, you will see new store layouts and a better understanding of the placement of the products. How? When you enter the store, there is a specific way in which you purchase. This is true for online stores as well. That’s why Artificial Intelligence can help you. it will help you understand the exact way in which users tend to shop online/offline, and will offer to design the layouts accordingly. for instance, if the shampoo is placed next to oil, there is a good chance that you might be able to convert both products, and gain more profits.

The idea is to understand the methods and develop an algorithm that will connect your customer’s purchase behavior with the way they complete the purchase. What gets them engaged with the store and how they route their shopping?

4.     Extends Customer Support

Artificial Intelligence can help small businesses and enhance your customer service. With Chatbots, you can easily connect with the users, with fewer resources and that too in real-time. bots will represent your customer service executives, and help people complete their needs.

For instance, if someone has a query, and your executives are running busy, then you can get the bot to engage the person for a while. In case these questions can be answered by the bot, you will not only be saving the resource’s time but also saving a lot of your money

In the case of small businesses, it is very time consuming and money intensive to hire resources who can understand your needs, and offer help to the customers immediately. However, you can avail of the bot service, which helps in connecting with the customers immediately and get you the much necessary support.

5.     Fraud Detection

For many companies, safety and security play an important role. If your customers don’t feel that you are safe enough, they may not even consider you for their transactions.

Security also needs to ensure that anytime a fraud is likely to occur, the system should detect, and immediately report. This is not possible without technology. That’s why you need to implement Artificial Intelligence, as it will detect fraud immediately, and help you connect with the customers and report the same.

Any fraud that happens in the transactions will be immediately reported, and you will be able to safeguard your business against fraudsters and make the place safe and secure. The algorithm will match with the customer’s transaction habits, and immediately report any haywire transaction.

6.     Real-time Decision Making

With the Internet of Things associated with Artificial Intelligence, you will be able to get real-time data from all the devices connected with your business. for instance, the businesses operating in the manufacturing industry would be able to understand the data that is needed from the shop floor and get it immediately through the connected smart sensors. Artificial Intelligence will be able to apply algorithms to this data and gather insights. all this happens in real-time, which helps businesses make real-time decisions essential for better business growth.

7.     Improved Search Experience

With fewer keywords and better keyword analysis, the online stores and businesses should be able to offer key search results that match the needs of the user. For instance, if the user types a wrong spelling, even then the search engine within the app should be able to detect the right spelling and offer the results accordingly.

For this purpose, you need AI which will study all the wrong keywords and ways in which the user searches for a particular product. When you are more than aware of the search methods, it becomes easy for you to create an algorithm that will enhance the search results.

The idea is to make sure that the user is not disengaged from the app, and the app provides them with the results they are looking forward to, despite the keywords they enter.

Summing Up

Artificial Intelligence will ramp up the mobile apps and will ensure better user engagement within the mobile apps. With businesses incorporating AI within mobile apps, it will surely be a good start for them, as it will enhance user experience and will result in more conversions.

The idea is to understand how exactly AI fits into your organization, and how you can use it to fulfill your needs. Once the requirement analysis is done and you have an algorithm ready, get started with incorporating AI into your mobile app, and see how your app grows.

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Google  News is going bilingual. The company announced this morning a new feature that will allow users to update their Google News settings to support two languages instead of one, in an effort to better serve the more than 60% of people worldwide who speak and read news across two or more languages.

The change means you won’t have to constantly toggle between two languages in order to keep up with news that’s being covered elsewhere. This is particularly important for those who have moved to a different country, but want to keep up with their news from back home, as well as in places where it’s common for people to speak multiple languages.

Google cites the ability to read both English and Hindi news at the same time as a key example.

The update won’t impact your other personalization preferences, Google notes — it will just pull in more stories that match the topics and interests you care about.

The changes follow a larger revamp of the Google News product and destination website that’s been underway for over a year. At Google’s developer conference in 2018, the company announced its plans to leverage AI technology to help select which stories were shown first and how the news selection would be customized to each user, while not trapping them in so-called “filter bubbles” where they don’t have access to fact checks or the other side’s opinion.

That AI-powered version of the Google News app rolled out last spring. 

More recently, Google revamped the Google News tab on the desktop to organize articles in a card-style layout, which was meant to improve readability and better highlight the publisher sources.

Today’s new bilingual feature, however, is aimed at the Google News mobile app user base.

Google says the feature is available now across 141 countries and 41 languages on the Google News app for both iOS and Android. (On the desktop, you still have to pick just one language, we found.)

The company notes that being able to read news in other languages can also help people widen their perspective on issues.

“There’s still lots more to do to help connect people with quality and trustworthy news on the issues they care about, but we hope today’s update will make it easier to connect with different cultures and perspectives from the comfort of your device,” Google says.

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 All too often, we search for an app and end up finding what looks to be the best fit for our needs. But that is until one sees the long list of permissions the application thinks it needs to function. Some developers tend to call for permissions for functionality that their app clearly does not need, like an expense tracker needing the RECORD_AUDIO permission, indicating a high possibility of a nefarious motive.

Google does realize that many such applications plague the Google Play Store. While the technologically adept users may keep a close eye on the permissions they grant to any app, the normal user usually just presses on “Accept” till they reach their end result. It then becomes Google’s “responsibility” to figure out a solution that protects the users from such intrusive applications while devising a solution that scales across the entirety of the Google Play Store and all future uploads.

Google’s approach to fighting this problem involves the application of machine learning to scale its solution. Google begins by analyzing privacy and security signals for each app in Google Play, and then compares that app to its functional peers i.e. other apps with similar features. Functional peers help set the baseline of behavior expected out of that group and apps belonging to this group that exceed the boundary of expected behaviors are then easier to identify. For example, a coloring book app does not need to have access to a user’s precise location, and this need can be established by analyzing other coloring book apps. Similarly, a navigation app does need precise location, and looking at other navigation apps would illustrate that the need for location permissions is within expected and accepted behavior.

Google utilizes machine learning to create these peer groups, letting it look beyond other methods like manual curation and fixed categories, methods that have their own drawbacks. Google’s approach uses “deep learning of vector embeddings to identify peer groups of apps with similar functionality”. This uses app metadata such as text descriptions and user metrics like number of installs. Once the peer groups are established, anomalous behaviors are identified  for potentially harmful signals related to privacy and security from each app’s requested permissions and behaviors. The correlation between different peer groups and their security signals helps different teams at Google decide which apps to promote and determine which apps deserve a more careful look.

The results are also used to help app developers improve the privacy and security of their own apps, though Google did not expand on how exactly this is done, or how exactly it segregates apps that have an honest oversight in its security from apps that have malafide intentions. Perhaps this part of the process is done after manual inspection of these apps by Google’s security and privacy experts, but we are left to draw Google’s word on this.

Nonetheless, it is good to see Google tackling the issues of permission at the store level as well, with a solution that works best for the scale of the Android ecosystem.

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