Internet of ThingsThe drastic growth in mobile users has resulted in the boost of the mobile app development industry. Mobile application development companies assist businesses to plan and design top mobile apps that are unique yet meet the norms set by the client.

There is an increased dependency on mobile apps to perform day to day tasks. These apps require tremendous use of data. To efficiently analyze and manage this data, a robust information management tool is requisite. This is where big data analytics plays a crucial role. It assists companies in getting data-driven insight from the app. Also, read the mobile app development guide to understand all hidden milestones.

The Need for Big Data in Mobile App Development

According to a Statista report, the number of mobile app downloads worldwide was 205 billion in 2018 and expected to grow to 258.2 billion by 2022. This extensive user base of mobile apps produces large amounts of raw data. 

Raw data is in an unstructured form that needs high-level analytics to crunch down the numbers and develop valuable insights out of those numbers. This is where big data comes into play. Big data tools help mobile app developers to collect, organize, and evaluate different data sets in order to identify patterns in customer preferences. Developers can then leverage big data insights to build innovative and futuristic mobile apps.

Some of the most popular big data tools used by developers are Spark, Tableau, Hadoop, Cloudera, and Hive. These tools allow developers to create innovative mobile apps by integrating new features.

Advantages of Big Data in Mobile App Development

A mobile app has to be fast, engaging and easy-to-use to get more downloads in the app market. However, the most important factor is that it must meet user expectations and needs and become their first choice. Big Data technology helps mobile application developers in this context in the following ways:

Understanding the Audience

A great mobile should meet user needs and expectations. Big data analyze large volumes of user-generated data on a regular basis. This data provides useful insights to business owners. 

By understanding how users from different backgrounds, age groups, lifestyles, and geographies relate, react, and interact with mobile apps, you can formulate ideas for new and innovative apps and boost the capabilities of existing ones. Uber uses big data to improve its customer service. When a customer requests a cab, Uber analyzes real-time traffic conditions, availability of a driver nearby, estimated time for the journey and provides a time and cost estimate for improved engagement.

User Experience Analysis

In addition to understanding customer needs, mobile app development also requires to understand how users use apps. Big data conducts detailed user experience analysis, provides an overall view of usage and user experience, evaluates the engagement for each feature or page, and determines the most desired features as well as pain points.

The drastic growth in mobile users has resulted in the boost of the mobile app development industry. Mobile application development agencies like Ramotion assist businesses to plan and design top mobile apps that are unique yet meet the norms set by the client.

Big data lets you understand which elements of your mobile app make users spend more time and which makes them leave. You can then leverage this information to create a list of features that users demand, plan for changes or modifications in the design, improve user experience, and maximize engagement.

Improving Performance

Thanks to Big Data technology, developers can easily track how much traffic their application is generating. They can evaluate engagement from each particular feature or page and get information about the things that slow down application performance. This way, developers can easily improve their app performance and prevent user abandonment.

Real-Time Data

Businesses today have to be aware of the changing trends and customer needs to stay ahead in the game. Big data analytics provides this kind of information in real-time. By examining real-time data, companies can make data-driven decisions to improve client satisfaction and increase sales.

For example, fitness tracking applications monitor the eating, resting and activity habits to enable better lifestyle choices. Real-time data gathered by the app, allow doctors and healthcare providers to detect any health issues the user may face. 

Personalized Marketing Campaigns

Data analysis of user behavior including their likes, dislikes, needs, and expectations can build personalized marketing campaigns. Using big data, you can analyze demographic data, purchase patterns, and social behavior of users to modify your marketing strategies according to their current needs. By building the right strategies, you can drive adoption, fuel engagement, increase satisfaction and ultimately, grow app revenue.

Amazon uses big data to enable predictive analysis and offers product suggestions based on purchase history, viewed and trending products. Personalized recommendations deliver the most relevant products and interactive shopping experience to each shopper.

Social Media Analytics:

With the help of big data analytics, companies can identify mentions of their products on social sites. These mentions can be in the form of customer reviews, complaints or dynamic media like images and video. Companies use social media platforms to leverage positive customer experiences and reply to the customer who mentions their company. 

By knowing your customers better and understanding how they interact with different social media platforms, you can find more fascinating ways to sell your product.


Mobile apps change more than web apps. They are more popular due to the ease of usage and simple display. Hence, developers have to work hard to deliver a unique and engaging user experience. Big Data provides a large amount of information about user preferences, requirements, location and more. To stay ahead of the game, companies have to efficiently utilize the data procured by big data analytics.

Author bio:

gilad maayanGilad David Maayan is a technology writer who has worked with over 150 technology companies including SAP, Samsung NEXT, NetApp and Imperva, producing technical and thought leadership content that elucidates technical solutions for developers and IT leadership. You can follow him on LinkedIn