From smart cars to smart apps, everything has changed in a short period. Advanced technologies like Artificial Intelligence and Machine Learning have contributed high in such an evolution of the digital world.
Corporates are already investing heavily in reorganizing their infrastructures with machine learning integrations. Jobs related machine learning and AI has the most median salaries in the current scenario.
The machine learning market is also rising higher. It is forecasted to grow at a compound annual growth rate of 42.08% for the forecast period of 2018-2024. During this period, the surge in the revenues of the market will be $30.6 billion.
While there are integrations of ML-based technologies in almost every business domain, apps are not that far behind. Here, we have discussed some ways to leverage machine learning for mobile apps.
Have you ever thought of binging a show on Netflix? 75% of users on the OTT platform prefers personalized recommendations made by the app. The same can be done with your app too. For such an enhancement, you can leverage machine learning.
The technology has algorithms that use a user-data to identify patterns. You can use these patterns with model training in machine learning. The model learns from patterns and provides relative recommendations. You can integrate such models into your mobile app development for personalized user experiences.
Enhanced Product Search:
If you are developing a mobile app for an e-commerce platform, than machine learning is bliss. This is the same way e-commerce giants like Amazon offers product search and recommendations. You can integrate machine learning technologies in e-commerce mobile app development. It can help create unique filters for product searches. It can also help consumers find better product categorizations.
Fintechs and banking industries can develop smart mobile apps with ML. A machine-learning algorithm with predictive analytics can help financial institutions. Banking and commercial companies can leverage ML algorithms to create financial products for consumers.
These algorithms can easily use the user-data to find buying patterns, spending patterns, and even borrowing designs. Algorithms can learn from such patterns. With these training, algorithms can recommend personalized financial loans, lending products, and investment schemes. These financial products are according to the financial situation of consumers and thus suitable.
Firms can induce more user engagement with higher personalized communications. Machine learning can be leveraged for intelligent conversations. ML-powered chatbots can achieve natural interactions like humans.
They can use such interactions to gather data, analyze it, and provide relevant recommendations also. Machine learning algorithms can also help mobile app development automate the filtration of content. UGC or user-generated content needs higher filtration to maintain security. And ML can help firms achieve high data security.
Machine learning algorithms integrations can help make mobile apps more intelligent. It can help achieve automation in processes through apps. It can help firms automate lead generation and conversion through personalization. So, if you want your business to go smart, integrate machine learning in mobile app development.
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