Exploring Nuances Of Machine Learning & Personalization In Apps

machine learning in apps development
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The market for machine learning is projected to reach $20.8 billion by 2024. It is unbelievable that it was only worth $1.6 billion back in 2017. This means that the market has been growing around 45% a year over the course of a decade.

The rapid growth in the machine learning market is largely attributed to the growing list of applications for it. Machine learning is being leveraged in every industry from healthcare to criminal justice. However, some machine learning approaches are clearly much more in demand than others.

Content personalization is one of the biggest breakthroughs in machine learning technology. Personalization has been especially beneficial in the mobile content industry. Companies looking for custom ios app development are creating apps that are personalized to their target users.

Examples of apps using machine learning for top-tier content personalization

A number of brands have become more reliant on their mobile apps to improve engagement with customers. A couple of the most successful are listed below. They have used highly sophisticated machine learning technology to improve the personalization of their apps, which has made them far more engaging.

Drippler

Drippler is a leading news syndication platform. The interface is handled almost entirely through mobile devices.

One of the reasons that Drippler is becoming so popular is that it is providing highly personalized content. When the user first installs the Drippler app, it scans the phone to learn more about them. It then deliveries relevant content based on experiences on other sites.

This feature alone sets the app apart from other new syndicators. However, it doesn’t end there. The app constantly monitors the articles the user clicks and uses machine learning to get a better idea of the types of content they are interested in. It uses this information to provide more relevant results.

Starbucks

Starbucks is another major brand that has done very well with content personalization. It uses machine learning to deliver highly personalized content to mobile app users.

The app regularly monitors customer purchases. It uses this information to provide the best coupons and other offers to app users. This wouldn’t have been possible without highly advanced machine learning technology.

Business Insider published an article on the effectiveness of this technology. It is being incorporated into the company’s existing star rewards program.

“To figure out how to best convince customers to spend and shop more, Starbucks draws from factors like customers’ established purchase history, listed preferences, account info, and even the local weather — think an iced coffee deals on a hot day. The company says the new program, which began its mobile rollout two weeks ago, is already leading to increases in how often customers are visiting Starbucks and how much they are spending,”

writes Business Insider writer, Kate Taylor.

Inmate finder tools

Inmate lookup tools are also using machine learning to perform their tasks better. GNC has talked about ways analytics is used in the prison system. This new technology is just an extension of that. Inmate-search.online will provide as much as possible details about given inmate’s incarceration facility, visitation hours, contacts, and other crucial information to stay connected with your loved one. In general, this has helped find inmates far more quickly.

More brands are refining their mobile app personalization strategies with machine learning

While a number of large brands like Starbucks have already discovered the benefits of machine learning with mobile content, a number of smaller companies are starting to explore it as well. They are using personalization to improve their retention rates. The average brand has a churn rate of around 75%, which can cause them to lose a lot of revenue they would be able to retain by holding on to customers better.

Personalization has been proven to significantly improve retention rates. Companies will need to use it to the full advantage to get the most value up their customers.

Marina Thomas of Read Write Web has shared some invaluable tips for company’s that are trying to get the most of their mobile apps:

“In addition to the above, you can also be incentivizing a few activities. Boost motivation of the user of your app by asking them to get involved in the app improvement. Ask their opinion, and they will tell you. Have a place where they can respond to you and they will pick your app everytime.”

While this is good advice, it is important to emphasize the importance of machine learning, too. Customers are using their mobile devices constantly, so engagement data will tell you a lot more than anything they would share in a quick survey.

Sean Mallon
Sean is a freelance writer and big data expert. He loves to write on big data, analytics and predictive analytics.