The Importance of Big Data in Mobile App Development
Big Data and mobile apps are a strong combination that can unleash unseen opportunities in the business, make it more data-driven, and lead to increase revenue. The benefits are enormous and include but are not limited to the following ones:
Getting to Know Users
One of the most important aspects of mobile app development is understanding your users. This understanding can be gained through a variety of methods, including user research, surveys, and usability testing. However, perhaps one of the most powerful tools available to developers today is Big Data.
Big data application development can help app owners gain deep insights into user behavior, such as their preferences, interests, and habits. By analyzing large datasets, they can identify patterns and trends that might not be immediately apparent through other methods.
For example, Big Data might reveal that users in a particular geographic region are more likely to use a certain feature or that users who engage with the app on weekends tend to have a different set of preferences than those who use it during the week.
Starbucks, the coffee giant, is a leader in using big data and artificial intelligence to drive its marketing, sales, and business decisions. With 25,000 stores globally, the company processes a staggering 90 million transactions every week.
Starbucks leverages its popular loyalty card program and mobile application to collect individual purchase data from millions of customers. With the help of advanced Business Intelligence (BI) tools, the company analyzes this data to predict customers' preferences and sends tailored offers to them through their app and email. This system not only increases sales volumes but also drives customer engagement, encouraging them to visit Starbucks stores more frequently.
User Experience Analysis
Big Data analytics can also be used to analyze user experience. Developers can use Big Data to track user interactions with the app, identify areas that need improvement, and make necessary changes to enhance the overall user experience.
Amazon, the global e-commerce giant, serves millions of customers worldwide and generates annual revenues exceeding $470 billion. The company utilizes Big Data analytics to enhance the user experience and streamline its operations.
By analyzing vast amounts of data from customer browsing habits, purchase history, and product reviews, Amazon can provide personalized recommendations to each user, improving the shopping experience and increasing sales. This personalization extends to marketing emails and targeted advertisements, ensuring that customers see products relevant to their interests.
Additionally, Amazon uses Big Data to optimize its supply chain and inventory management. By predicting product demand based on historical sales data and current trends, Amazon ensures that warehouses are stocked efficiently, reducing delivery times and minimizing stockouts. This data-driven approach helps Amazon maintain high customer satisfaction and operational efficiency.
More Targeted Marketing
Big Data can be used to create more targeted marketing campaigns. By analyzing user data, developers can identify specific demographics and create targeted marketing strategies to reach them. This can help businesses save time and money by focusing their marketing efforts on the most profitable areas.
Netflix employs Big Data to enhance its marketing efforts. For instance, for its popular series "House of Cards," Netflix produced over 10 variations of the trailer. The trailer shown to each user is customized based on their viewing habits. If a user has watched a significant number of shows featuring female leads, the trailer that highlights the female characters will be displayed to them. The algorithm adapts to each user's preferences, ensuring that the marketing campaigns are tailored to their interests.
As a result, during the first week, the final season consisting of eight episodes, attracted an average viewership of 1.53 million individuals in the United States.
Real-Time Data Acquisition
Big Data can also be used to acquire real-time data. This data can be used to monitor user behavior and track app performance. Real-time data can also be used to identify potential issues before they become major problems, allowing developers to quickly resolve them.
Procter & Gamble, a 179-year-old company, produces products that are used by people worldwide 2-3 times a day. The company has recognized the potential of Big Data app development and has integrated it into various business units around the world.
P&G places a strong emphasis on using Big Data to make better, smarter, real-time business decisions. To achieve this, its Global Business Services organization has developed tools, systems, and processes that enable managers to have direct access to the latest data and advanced analytics. Despite the emergence of many new companies in the market, P&G remains a major player due to its ability to adapt and leverage advanced technologies such as Big Data and development.
Personalized Experience
Big Data can be used to create a personalized experience for users. By analyzing user data, developers can create personalized recommendations and content based on user preferences. This can help increase user engagement and retention.
For instance, Netflix analyzes Big Data to predict users' preferences based on a variety of data points. This includes customer interactions on the app, responsiveness to shows and movies, device information like date, time, location, and type of device used to watch, and viewing habits such as pause and resume times, completion rates, search queries, preferred genres, and feedback and ratings from subscribers.
Using these data points, Netflix can accurately predict users' interests with an 80% accuracy rate, suggesting content that users are likely to be interested in watching next.
Social Media Analytics
Social media analytics can be used to track user behavior on social media platforms. This information can be used to create targeted marketing campaigns, as well as to monitor user sentiment and feedback. Social media analytics can also be used to identify potential issues and address them in a timely manner.
Major airlines, such as Delta, monitor social media activity to gauge customer satisfaction regarding delays, upgrades, in-flight entertainment, and other aspects of the flying experience. Twitter is particularly useful for this purpose. For instance, if a customer tweets negatively about lost baggage before boarding a connecting flight, the airline will detect the negative tweet and notify their support team.
The support team will then send a representative to the passenger's destination, offering a complimentary first-class upgrade ticket for the return flight and providing information about the tracked baggage with a promise of prompt delivery upon arrival. As a result of this gesture, the customer is likely to share their positive experience on social media, bolstering the airline's reputation.
