AI Predictive Analytics And Its Implications For Custom Mobile App Development

At present, 6.3 billion people worldwide are utilizing mobile applications.


So many app users are roaming around the globe, looking for innovative apps to use.


Google Play Store gets loaded with 2.87 million apps.

The stats clearly indicate that the mobile app design and development industry is crowded and noisy. Thus, it does not make it easy for someone to step into it unless they are well equipped with good knowledge of this market.


You can enthusiastically invest in custom mobile application development. However, it does not necessarily imply the app’s success.


25% of mobile phone users abandon an app after their first use, while 71% of smartphone users worldwide uninstall an app three months after downloading it.


Hence, it is clear that developing your mobile app to make it dazzle the crowd is not that simple.

But with the strategy in which you prepare for the worst-case scenario, you can reap the best results. By learning the possibilities and why users may abandon your app, you can prevent them, thus retaining people on your app. But how can you predict the facts that will make the users abandon your mobile app in advance?


Don’t fret! The magic bullet is AI predictive analytics.


Lately, many individual app developers and custom app development services have been leveraging predictive analytics to ensure mobile app success.


So, let’s dive into AI-enabled predictive analytics and learn how it benefits custom mobile app development.


What Is AI Predictive Analytics?


Market analysis is crucial for all kinds of businesses. That’s why predictive analytics has recently gained tremendous support from many organizations globally.


  • By the end of 2022, the market value of predictive analytics will hit $12.4 billion.


  • Meanwhile, the global predictive analytics market will reach a whopping $35.45 billion by 2027.


Even in the mobile app development space, predictive analytics has become a dominant technological trend, shaking up the industry.


  • AI predictive analyticsutilizes AI/ML algorithms and statistical data techniques to validate trending and historical data. These efforts lead businesses to predict future mobile app trends and outcomes.


In simple terms, predictive analytics is like the magic mirror, letting companies know,


  • Whether the apps be able to retain the users or not?


  • What actions should the companies take to prevent the failure of their apps?


The effective way to boost the app engineering is to make it delightful to the users for a long time. AI predictive analytics leverages all the information during the app design, development process and market analysis to make insightful predictions. Once the project rolls on the floor, the technology gets hold of the information during development, testing, project management, source codes, Etc. All this information helps it to identify the patterns and future outcomes of the mobile apps.


  • With AI predictive analytics, companies can find out the development cycle bottlenecks, quality issues, and the veiled scopes of the apps.


  • Through a detailed analytical approach, the technology brings light to the users’ behaviour towards the mobile app after the launch.


Benefits That AI Predictive Analytics Deliver To The Mobile App Industry


Predictive analytics delivers outstanding benefits to the mobile app industry, undoubtedly. The countless benefits gear the start-ups to integrate the technology and experience a remarkable feat.


What are they?


Check out below:


Driving Sales And Profit


  • AI predictive analytics offer mobile users practical product recommendations based on their previous purchases or search.


  • Moreover, predictive analytics may recommend products they had no plan to buy to users.


  • For example, You have saved a few items in your cart. A predictive analytics engine recommends items that users frequently buy alongside the products in your cart.


  • For another example, you are about to order food online. A predictive analytics engine will suggest dishes or beverages that users often buy alongside the food item you are about to order.


Hence, what do predictive analytics do?


  • It analyses customers’ data first.


  • After the analysis, it presents products or service recommendations based on users’ web browsing patterns and purchase history.


  • Additionally, the inbuilt geo-location feature of Smartphones helps PAs generate recommendations for users.


  • The personalized recommendations make the marketing campaign more relevant, driving sales and profit for businesses.


Improving Customer Engagement And Interaction


  • Mobile apps, primarily social media apps, rely on user engagement and interaction.
  • The mobile app will surely fall to the ground if these two go wrong.


  • Predictive analytics effectively presents recommendations based on user behaviour and choice. It helps companies maintain user engagement effortlessly.


  • For instance, a predictive analytics engine will recommend to users whom to follow or which groups best suit their interests.


  • Additionally, PAs can collect users’ data like location, friends, likes, groups, keywords in their posts, Etc. These data serve as the fundamental pillars for social media apps to present the feed more appealing to users.


  • There is more. Custom app development services can leverage PAs to detect which design elements of the app are turning down the users. Why are the users uninstalling the app after the download?


  • Consequently, app developers can design and develop mobile apps according to users’ expectations. It ensures a hike in user engagement.


Enhanced User Retention


It is pretty obvious; when users get what they want, they will stay with the app for a long time, maybe forever.


PA helps companies in growing loyalty and user retention.


  • Since it detects the pain points of the apps, and the app developers get the time to work on those pain points, the mobile app becomes invincible.


  • With enhanced features and flawless function, mobile apps allure users to attain their loyalty.


  • By and large, predictive analytics detect touchpoints that impact users’ attention and retention.


  • Customer retention will never hinder the app’s success when all issues get fixed.


Wrapping Up


In a nutshell, AI predictive analytics is crucial for mobile app development. The future market prediction and user behaviour analysis aid developers in reducing the churn rate and maximizing conversion and profit.


In terms of custom mobile application development, PAs enable companies to make critical decisions with less pain.