Big data tops the charts when it comes to providing a considerably better user experience by increasing app engagement and optimizing resources correctly. While it not only makes content for users more relevant but also personalized content and when analyzed from a business point of view, it improves conversion rates. To put it in simpler words, the future of big data is the gold mine that app developers need in providing information and creating apps that users want.
Here is a breakdown of the various ways in which big data is being used to create the next generation of mobile apps:
Seamless and easy to use UX
Big data is incredible in providing insights that help tract every movement of a user by crunching numbers to improve overall user experience. Additionally, it also helps in signaling developers when apps do not meet either the design standards or the UX. Studies suggest that most app users stick to or delete an app based on its user-friendly quotient, which is the ease of use. This kind of information helps big data constantly make improvements for user interface and reduce friction.
Machine learning and artificial intelligence
With the help of machine learning and usage of artificial intelligence, big data can recognize failure patterns if any and suggest improvements. Also, this helps understand any glitches that might be acting as slowdowns, including loading time for a website or a page.
Predictive analytics and customization
Big data helps customize the user experience and deliver content based on previous usage patterns. This is where predictive analytics come into play by suggesting what you should buy or what you should watch. This gets increasingly better as you consistently use a particular service.
Widely used by companies like Netflix and Amazon, predictive analytics shows up an image or shows pricing options based on user data buying patterns and more. Basics of predictive analytics are taught during a Data Analytics Course.
Increase app engagement
Users often get more engaged with a particular app and keep returning to it frequently. A term referred to as- app stickiness, this actively engages customers more than its competitors and factors like duration session, the flow of content on the screen and churn tracking help in contributing to stickiness.
Real-time analytics
Real-time analytics help an app developer to analyze data related to that app and make dynamic changes based on the present situation. The mobile app market in itself is a pretty dynamic one, where things significantly change every minute. Organizations are using real-time analytics o predict patterns that include flying for airlines when visibility is good, avoiding certain roads to get rid of traffic, avoiding extreme weather conditions, sharing driver and customer live locations, estimates fares at a given point in the day and more.
Evolve marketing strategies
Big data can help make better marketing strategies, by capturing user data that helps app developers understand the kind of people their users are. Existing strategies are reworked on to reach out to new users and rearrange older users. Study of user demographics, buying patterns social behavior of apps, posts liked, websites visited, all of which can be used to build individual user personas which are then used to strategize marketing strategies.
Considerable cost reduction
Lastly, big data helps understand and predict app development costs, since building a standard app might often be time-consuming and quite expensive. This not only includes the app development process costs but also calculates the number of developers, designers, testers and more will be needed to have an app up and running. Additionally, the longer time it takes to build the app, the higher the cost graph goes.
