When building a mobile application, a software developer has to understand what end users want from it. This is exactly where data science can give us adequate answers.
Data science is a field where programming, mathematical and statistical skills are combined together for the purpose of collecting, analyzing, and optimizing large amounts of data.
Every sector of the economy today has access to more data than was even impossible to imagine ten years ago. Companies accumulate new data at such a speed that is difficult to extract value from it.
Large amounts of big data transmitted at high speeds exceed the capabilities of storing and processing. Data science is here to help us extract value from the data in a timely manner for the purpose of developing sustainable software solutions.
Let’s find out what are the main benefits of using data science in mobile app development.
Our success in business always depends on our interaction with customers. Being able to follow their expectations and turn them into exciting phone features is a big step toward growing the business.
Keep in mind that mobile users leave behind large amounts of useful data with every action they take on their devices. Without collecting and analyzing the data, we would not be able to build a suitable product for our customers.
Data scientists take advantage of these insights to get the answers to the following questions:
How many users have installed an application?
How many active users are there?
How much time do they spend using the app?
Which parts of the application are visited the most?
The data you receive and analyze can help you in creating sales strategies and turning them into software features.
Who is accountable for implementing mobile app features – a data scientist or a software developer? Many companies are confused about this. This is why some of them decide to rely on IT outsourcing to enrich their team with the right talents. One of these talents is a data scientist.
A data scientist is in charge of extracting value from data to solve the most complex company problems. However, a software developer can use various tools to implement a specific application feature thanks to a data scientist’s input.
Thus, big data provide enough relevant information about the features customers want to use. There is a wide range of different mobile functionalities that data science can greatly contribute to:
Product or service recommendations – If you are running an online business, you can benefit a lot from this feature. Data scientists collect and analyze data such as previous purchases or clicks to get familiar with customer behavior. Thanks to their input, developers create algorithms that are able to generate personalized recommendations.
Customer segmentation – Every customer has different needs. Dividing customers into specific groups based on their behavior can result in efficient marketing campaigns. For instance, users can be grouped according to their age, education, social or income status.
Image recognition – The feature allows mobile devices to spot objects. Undoubtedly, facial recognition is one of the most significant features when it comes to keeping your data private. For instance, you can unlock your phone by just showing your face in front of it.
In order to become accepted by end users, mobile applications have to be fast, scalable, and user-friendly. If your application is unresponsive or running slow, developers with data scientists should take adequate measures to fix these problems.
Data analytics provide us with plenty of useful information for validating features and detecting potential issues. In addition to analytics, data scientists can sometimes be accountable for delivering machine learning solutions.
Machine learning algorithms are extremely good at detecting all potential issues related to an app. For instance, an algorithm can detect suspicious activities and errors.
The main goal of data science is to develop mechanisms capable of processing huge amounts of data coming from various sources. Data scientists are in charge of extracting value from the data which is a key input for software engineers to develop mobile applications.
When interacting with a mobile application, users leave tons of information. For instance, once we collect information about how many users have installed our application and which part of it is visited the most, we are on the right track. We can plan marketing campaigns and new features we are going to implement in the near future.
Data analytics uncovers patterns and trends derived from your data. For example, data from a mobile app might tell you that you sent 1,000 push messages last month. However, a data scientist can dig deeper and find out how many messages you sent per user. This is where your data starts working for you!