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Most Effective Ways AI Can Transform Mobile App Marketing

How AI Can Transform Mobile App Marketing

Artificial Intelligence (AI) has been around for the past few years and it appeared as a breakthrough technology with an era-defining impact. Over the years, it penetrated almost all digital channels including the web, mobile apps, social media channels, e-commerce stores, and IOT gadgets. It has also been one of the most reliable technologies for mobile app marketers all over the globe.

Already, a vast majority of dominant tech brands ranging from the likes of e-commerce giant Amazon to the search engine Google, are using artificial intelligence (AI) for the discreet advantage of their business. A recent study revealed that around 80% of business professionals in the B2B segment consider AI to have revolutionary potential for several industries by the year 2020.

AI Technologies For Mobile Apps

The utilization of artificial intelligence is evident in mobile applications. Particularly in enterprise apps and business apps where data-centric inputs and insights play a crucial role, artificial intelligence opened a new vista of opportunities. If a mobile app requires creating reports, market reviews, market analysis, etc artificial intelligence can play a crucial role.

A whole array of new and advanced technologies are actually playing a mission-critical role behind artificial intelligence. Natural language processing, automated insights, advanced semantics, speech recognition, are some of the key technologies sharpening artificial intelligence. When you want to unroll a mobile app which is capable to interact with the users for getting feedback or when you need chatbots for active user interaction based upon user insights, AI can play a significant role.

When you need to use a mobile app for forecasting and classification, your app can utilize machine learning. From Amazon, Google, Microsoft to SAS and several other leading tech companies are now actively utilizing machine learning for their AI based mobile solutions. A whole array of companies are also utilizing biometrics technology to utilize human behavior and identify user profiles for helping the app adjust to the user needs.

Besides advanced language processing, image processing is also opening new ways to understand users. Advanced image processing or audio data analysis can now recognize emotion. This opens up a new way to capture subtle human speech signals and voice innovations. Many startups are using such AI tools extensively.

Personalisation Will Define Mobile Apps Of Future

Mobile_App_UX_Principles_cover

AI as of now has been most impactful to personalize the user experience for mobile apps and websites across the niches. AI-based personalization helps to tweak the user experience positively in different user contexts. From allowing better recommendations based on individual user preferences to personalizing features like notification messages and newsfeed emails based on user profile and preferences, personalization can enrich applications in different ways and in a variety of contexts.

Since personalization is increasingly becoming the key to boost user engagement and customer satisfaction across the industries, AI is playing the crucial role by utilizing customer data and machine learning inputs to serve customers with design, function, and contents as per their preference. From My Starbucks Barista to Amazon Go, all big brands are adopting AI.

Thanks to AI personalization will make the user experience better in terms of both the front-end and back-end. AI capable to make the machine learn and process information just like the human brains can deliver up to the expectations of users and consumers. AI will also make the life of the developers easy by taking the repetitive tasks on its shoulder. All regular repetitive tasks, software testing, etc can now be taken care of by AI. This will significantly boost the development pace and help in making the development cycle shorter.

Automated Reasoning

Automated reasoning is all about the reasoning of the computer based on mathematical and few other logical approaches. This reasoning upholds logic in progression and carrying out of tasks and in that sense, it resembles human reasoning to a great extent. But, unlike a human, it doesn’t accommodate emotional understanding to overlap logic and thus offers a more precise and predictive course of action. With automated reasoning, the tasks can be carried out more precisely with less scope of human errors.

Uber is a nice example of automated reasoning works. Uber by utilizing AI based reasoning recommends drivers the easiest and least time-consuming routes. The automated reasoning here takes into consideration several on-route factors such as traffic congestion, the hour of travel, past history of driving in that route, etc. By continuously learning from the past trips of millions of drivers besides considering the actual data the automated reasoning precisely guides the drivers about the best routes.

AI-based Recommendations

Artificial-intelligence

AI also plays a crucial role in providing the most suitable product recommendations to users. Based on user preference, past browsing and purchase history and user behavior, products and services are recommended to the online customers generating increased traction and sales. This is particularly important to generate consistent sales when a whopping 80% of users abandon apps within just 3 months after downloading the app. This happens with all those websites that fail to deliver unique and engaging contents for their users.

As push notification messages are now extensively used by most services and brands they tend to generate very less traction these days. Naturally, users instead of being notified want to get recommendations on their screen while using an app. The users now expect a more personalized and tailored user experience. AI-based recommendations can just fit the bill to meet such expectations.

Thanks to artificial intelligence, a website can easily know about the choices of the users including the likes and dislikes. Such in-depth information and insights about the users help them making an engaging app. Machine learning algorithms are now being used extensively to track the options users choose and the way they prefer interacting. This user insights and data can further be utilized to keep users engaged. Both Netflix and YouTube use similar algorithms to monitor users.

Conclusion

From processing information to drawing insights to making value additions based on user preference, artificial intelligence will continue to make mobile app experience and marketing better.

Author Bio

Atman Rathod is working as the Business Director at CMARIX TechnoLabs, a leading web and mobile app development company with 13+ years of experience. He loves to write about technology, startups, entrepreneurship, and business. His creative abilities, academic track record and leadership skills made him one of the key industry influencers as well.

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