How Predictive Analytics Helps Developers Anticipate User Needs
30.05.2023
Predictive analytics helps developers make informed decisions about future software changes to ensure a painless customer experience, writes Polina Tibets, head of business operations at Pangea.ai, on the InformationWeek portal.
Users are four times more likely to switch apps after a bad experience with a program, such as persistent problems, frequent crashes or errors, or an unintuitive user interface. To meet the ever-changing needs of users, developers can use predictive analytics, which involves using historical user data, statistical modeling, and machine learning to forecast or influence future decisions. However, according to ResearchAndMarkets’ “Global Predictive Analytics Markets Report 2022,” only 23% of companies currently use predictive analytics to anticipate customer needs.
When the goal is to obtain reliable and actionable information, a software developer can follow these four steps:
To achieve the best results in a predictive model, a software engineer should identify current software issues, such as compatibility with different devices. Next, a list of identified issues should be compiled and ranked to determine the priority of each.
At this stage, you also need to define the bahamas mobile database for data collection. For example, you can decide to collect information about the time of software use, download time, user interests, their age, region, etc.
Once you have defined the scope of data collection, identify possible solutions to collect the information you need. Define the goals you want to achieve. Ultimately, this is an improvement of your software product.
Choose a data collection method. There are a wide range of data collection tools and companies to choose from. Decide whether you want to integrate the tool with your system or use it yourself.
2. Identify useful data that meets the stated purpose