State-of-the-art general services have become the tale of old days now. Today, customers want services tailored to their needs otherwise they are likely to switch brands if their service provider doesn’t meet their needs. Also, they are willing to share personal details like email id, location and more with companies that offer personalized deals.

The digital improvements and technological progress are creating new opportunities for vendors to attract and retain their customers. However, there’s still a wide gap between mass and individual personalization. It is not limited to only mobile apps now. You need to add advanced features to your app for delighting the target audience.

Machine learning (ML) helps to bridge this personalization gap. Its cognitive technology enables companies to build machines and create algorithms that understand humans, assist them in their tasks or even entertain them. Machine learning makes the mobile platforms more user-friendly, enhances the customer experience, retains customer loyalty, and helps in offering consistent omnichannel experiences.

Below are some of the factors to learn and understand how Machine Learning can boost your business:

1) Customized Use Experience - The continual learning process and algorithms of machine learning analyze all the sources of information including social media activities, credit ratings and more. The algorithms offer recommendations to the customers by the gathered information.
Machine learning also helps you to classify and structure your users, define an individual approach to each user group, and adapt the content. The most significant use case of it is Uber. The company uses Machine Learning to provide the estimated time of arrival, cost, detailed real-time route information via maps and more.

2) Advanced Search - Machine learning solutions enable you to optimize the search in your app and deliver more contextual results. The ML algorithms learn from the customer queries and prioritize in the results that matter most to the user.
Modern mobile apps also allow you to collect all the available data about your customers like search history or standard actions. It helps you to rank your products and services and provide the best matching search results. If we talk about its use case, Reddit engages ML algorithms in improving the search performance for millions of community members.

3) Relevant Advertising - The most critical part of advertising is displaying the right ads to the right set of audience. The machine learning technology enables companies to target display ads and personalized messages more accurately. It helps you to avoid bothering customers with the marketing of the products they’ve already bought and are not likely to shop for them shortly.

With machine learning, you can also predict how a particular customer will react to your promotion. It helps you to show specific ads only to the customers who have the highest likelihood in the displayed product or service. It saves your valuable time, money and improves the brand’s reputation.

Coca-Cola keeps a close tab on how the company’s products are represented across the social media platform. It uses image recognition technology for identifying the people posting images of its or competitors’ products on Facebook, Instagram, Twitter and more. It helps Coca-Cola to learn about the situations that prompt the customers to talk about its brand. It also assists the company in defining the best way for serving advertisements.

To conclude, machine learning can empower your mobile app with a personalization engine, cutting-edge search technology, fraud protection and more. Contact a custom mobile application development services provider to elevate the mobile app and enrich your business.

Author's Bio: 

Kaushal Shah manages digital marketing communications for the enterprise technology services provided by Rishabh Software. This article focuses on app development by outlining the use cases of machine learning (ML) for the mobile app vertical. Also, provide a few examples of how companies are leveraging machine intelligence on a real-time basis.