How Artificial Intelligence is Used to Drive Personalization in Mobile Apps

personalizationArtificial Intelligence (AI) is the talk of the town as more and more businesses are using it to achieve their business goals. We see AI being used in almost every industry now, from healthcare to banking and tourism. It’s no surprise that AI will continue to dominate the tech world, and transform the way businesses operate, as well as improving customer experience.


Why Is Personalization Important for Customers?

If you have a retail store that deals in luxuries, then the chances of your customers being wealthy are extremely high. Now, wouldn’t it be great if your users receive personal attention from their own stylist while they are browsing the store? This way they feel special and are more likely to make a purchase.

The same concept is followed in mobile apps where users receive attention from a personalized artificial intelligence attending to their individual needs. 

For instance, if you have an eCommerce app that sells both online and offline products, then it will be great if the mobile app highlights the offline products when users visit their local store or pop-up stalls. The chances of users purchasing your brand again will increase if they receive bespoke customer service and an overall rewarding experience, which is exactly what personalized artificial intelligence aims to do.


AI Apps Are Here to Save the Day!

Nowadays we see AI being used in almost every industry and mobile apps are no exception. Personalization is the key to success for brands which means that businesses need a way through which they can customize content based on their users’ preferences. This process of customization is done by deploying Machine Learning algorithms on Personalized Content Management Systems (PCMS).

In simple terms, a PCMS is a system that allows you to create content for users based on their interests and preferences. The Personalized Content Management System undertakes the task of creating personalized user profiles, where it identifies patterns from datasets and predicts which content will be relevant. Each time a user logs into your mobile app, the system decides which content to serve.

AI is being used by the biggest brands to accomplish tasks like product recommendations, predicting items to follow up with users, dynamic pricing, and so on. Let’s explore how.


Ways AI Apps Drive Personalization for Consumers

How can artificial intelligence make mobile app personalization smarter?

From artificially intelligent personal assistants like Siri, Cortana to smart speakers like Amazon Echo, AI has found its place everywhere in our daily lives. The reason why these devices are so intelligent is because of the data they possess about their users.

The same concept is followed for mobile apps where they need to build user profiles that enable them to learn more about their behavior. The app analyzes the user data and provides personalized recommendations as well as suggestions using machine learning. This makes it easier for users to access content that is relevant specifically to them, without having to search for it on their own.

Here are some prominent personalization use cases in mobile apps.


1) Content Recommendation

Content recommendation is a popular form of personalization used by publishers and other content providers to drive customer engagement. The objective is to show relevant content at the right time so that users have a great experience while using the mobile app.

For example, Flipkart uses AI to recommend products that are personalized for each user based on their previous purchase history.

Google also uses personalization to serve targeted ads in their mobile search results.

Some examples of AI-powered personalization can be seen in online streaming services like Netflix and Hulu, which use machine learning to show relevant titles while recommending new shows for users to watch.


2) User Behavior Analysis

Behavioral analysis is based on the actions users perform when they are in the mobile app. It can range anywhere from how much time a user spends in the mobile app, which pages s/he visited, etc.

If a user spends more time in the app then the company can provide more personalized recommendations to them. For instance, Twitter identifies users who spend a long time reading tweets and recommends similar accounts to follow.


3) Proactive Notifications

Proactive notifications are sent to a user based on their explicit or implicit behavior which anticipates their next action. This is beneficial for the company as well as the user, as it makes it easier for them to access content and complete tasks without any hassle.

For instance, chat apps like Hike and WhatsApp use proactive notifications to give users a heads up about new messages on the go. This results in more convenience and also reduces user input.


4) Personalized Push Notifications

A push notification is a message that appears on the home screen of a user’s mobile device. This can be seen as intrusive by some users, but it also comes with significant benefits such as increasing user retention and acquisition if used correctly.

For instance, Whatsapp uses personalization to send notifications about new features to users who haven’t tried them yet.


5) Location-Based Notifications

Location-based notifications are important for business apps that need real-time updates and information about their customers, such as a bank app that notifies its users when they’re near the branch/ATM or an eCommerce app that sends notifications about sales at nearby stores.


6) Customized App Experience

One of the biggest challenges with mobile apps is that they require a lot of user input for performing tasks or completing specific actions. Customizable app experience changes all that by making these tasks easier for users to complete. For instance, instead of having to type in their exact location, a user can just tap a button and the app will find them.


7) Product Recommendations

AI can be used to enable personalized shopping experiences as well. Take the example of Amazon, which recommends products based on your purchase history and browsing behavior. All you have to do is log into your Amazon account and the app starts serving relevant product suggestions based on your personal preferences.

Personalization has been an integral part of mobile app marketing strategies for a long time now. The use cases listed here are only the tip of the iceberg as companies will continue to experiment with AI-powered personalization to drive engagement and improve customer experience.

The main takeaway here is that AI makes it possible for marketers to market more closely, following our unspoken emotions and feelings. Marketers now need to hone their skills with AI to be able to stay relevant in this new world of personalization. It is no longer enough to think, “What would I want?” but rather “What do my customers want?” The more personalized the product becomes, the better it serves its purpose.


Sunvera Software develops next-level software applications from start-to-finish. We are a premier software and mobile app development agency specializing in healthcare mobile app development, custom mobile app development, telehealth software, sales dashboards, custom mobile app development services, retail software development, supply-chain software, ecommerce, shopify, web design, iBeacon apps, security solutions and unified access software.

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