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The Role of Big Data in Mobile App Development

The Role of Big Data in Mobile App Development

With 4.57 billion mobile phone users in the world right now, the mobile app development industry is also at its pinnacle. With every company building mobile apps to address external as well as internal customers, there is a pressing need to keep pace with rapidly changing market trends, technology advances, and customer needs. One sure-shot way of out-performing the competition and achieving success is by letting data drive your decisions. Big data can enable you to unearth hidden patterns and customer preferences and you can lean on these to develop state-of-the-art mobile apps. Here’s how big data can play a major role in mobile app development.

Understand Customer Needs: A great mobile app is not one which looks stunning but one which meets the needs of users. Using big data, you can analyze the overwhelming volume of data that users generate on a regular basis and convert it into relevant insights. 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 in a big way to improve its customer service; when a customer requests for a cab, Uber analyzes real-time traffic conditions, availability of a driver nearby, estimated time for the journey, etc. and provides a time and cost estimate for improved engagement.
Drive User Experience Analysis: In addition to understanding customer needs, mobile app development also requires you to understand how users use your app. Using big data, you can conduct detailed user experience analysis, get a comprehensive 360-degree view of usage and the user experience, evaluate the engagement for each feature or page, and determine the most sought-after features as well as pain points. You can understand which elements of your mobile app make users spend more time and which cause them to leave. You can then use this information to create a list of the very features that users demand, plan for changes or modifications in the design, improve user experience, and maximize engagement.
Get Access to Real-time Data: Businesses today have to remain in touch with changing trends to stay ahead of the race. Big data helps a great deal in keeping up with the times. By examining real-time data, you can take real-time, data-driven decisions to improve customer satisfaction and bring in higher profit. Using big data, Fitbit tracks real-time health data including sleep, eating, and activity habits to enable better lifestyle choices. The data gathered by Fitbit not only helps individuals become healthier, but it also provides doctors and healthcare practitioners with a clear picture of overall health and habits across a wider population.
Build the Right Marketing Strategies: With a pool of data about user behavior including their likes, dislikes, needs, expectations, and more, you can build the right marketing strategies around how, when and where to target your audience. You can make better decisions of all types, from what type of push notifications to send and what strategy to use in increasing engagement. Using big data, you can analyze users’ demographic data, purchase patterns, and social behavior to modify your marketing messages according to their current interests. By building the right strategies, you can drive adoption, fuel engagement, increase satisfaction and ultimately, grow app revenue.
Enable Personalization: Big data also enables you to optimize search and make it more intuitive and less cumbersome for users. By analyzing data from customer queries, you can prioritize results, deliver better and more contextual experience that matter the most to a particular user. You can also group data and features to provide smarter self-service for immediate answers. Amazon uses big data to enable predictive analysis and offers product suggestions based on a user’s previous purchase history, products they have viewed or liked as well as trending products. By integrating recommendations across the buying cycle – from product discovery until checkout, Amazon delivers the most relevant products and delivers a personalized shopping experience to each shopper.

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