A data-driven approach gives your organization the metrics it needs to sufficiently grow its next digital venture. It enables your team to measure the impact of your app, including user engagement and usage patterns. This data plays a critical role in the iterative methodologies used to build software applications, including Lean Startup and Agile. The project team ultimately leverages this information to design enhancements to the product.
So let’s look at the data-driven approach to building a digital venture with the sizzle to attract the customers your organization wants. In the end, this process ensures the application provides what users truly need. Expect your app to seamlessly scale as a result.
A High-Level Overview of Data-Driven Development
Simply stated, data-driven development uses data to better inform the goals, design, and requirements of any digital venture. Data mature companies use metrics to test any assumptions driving the goals of the project. Additionally, any iterative lifecycle for developing apps generates additional data; ultimately helping the team craft something that makes an impact on the marketplace.
Data-driven development fits perfectly with iterative methodologies. For example, in Lean Startup the team uses data derived from market research to develop the goals and initial requirements for the project.
After the minimum viable product gets built, the team uses other datasets generated from A/B and user testing to design and code enhancements to the product. This “Build-Measure-Learn” cycle gets repeated until the project team is satisfied that the digital venture meets the goals of the project. Let’s look at the different steps of a data-driven software project in more detail.
Leveraging Data to Test Assumptions
Most digital ventures begin with a business devising a great idea for a mobile app, interactive website, or a similar product. At this point, the project team assumes their idea boasts a strong likelihood of going viral in the marketplace. The attitude feels similar to: “If we build it, they will come.”
However, this is obviously a risky expectation. If the team’s assumptions about public interest in the idea miss the mark, the likelihood of a successful project outcome remains close to nil. Performing the necessary market analysis, including identifying the potential customer base becomes essential during this early phase of the project.
This analysis generates a multitude of data. The market share currently enjoyed by competitor’s similar digital ventures provides one important example. Demographic data about the typical user of the app or website is another.
The project team uses this data to test their assumptions; with the findings being used to drive the requirements and design for the digital venture. Any marketing plan also takes advantage of this vital information.
Determining the KPIs that Best Measure Customer Engagement
Again, any software project using an iterative methodology takes place over multiple cycles. As noted earlier, these cycles are called “Build-Measure-Learn” in Lean Startup. One step in this process involves identifying the key performance indicators (KPIs) used to measure customer interaction with the digital venture.
Determining effective KPIs helps the project team understand the elements within the digital venture that work, and those that need improvement. They need to closely measure customer interaction with the app during testing. Ultimately, this approach better informs the process used for the enhancements to ultimately lead to a more effective and scalable product.
Craft Enhancements and Repeat the Cycle
At this point in the cycle, the development team uses the data generated during testing to build enhancements to the software product. Perhaps testing metrics highlighted that customers struggled with a certain screen in the app? Developers craft a streamlined interface design as a result.
The project team then deploys a new version of the app for testing purposes. This “Build-Measure-Learn” or similar cycle repeats itself until everyone is satisfied that the end product achieves the initial goals of the project. This final version of the digital venture is one boasting the quality to go viral in the marketplace.
What About Data Maturity?
The data maturity of an organization somewhat relates to their efficacy when using a data-driven software development approach. Data mature companies also understand how to leverage their data wisely for informed decision-making. They ensure corporate data remains accessible to employees who need it, as opposed to being stuck within silos.
Becoming data mature requires a business commit to making corporate datasets easily accessible to stakeholders throughout the organization. It enables companies to reengineer their business processes to leverage data-driven decision making, automation, and other modern techniques for improving operational efficiency. It’s an initiative that might take multiple years, but the ultimate rewards remain numerous.
If your company needs help turning its great idea into a captivating digital venture, connect with the team at NineTwoThree. We’re experts in modern development methodologies and crafting engrossing experiences in a data-driven fashion. Contact us to discuss how we can best help your organization bring its ideas to fruition.