In this quick overview, we’ll take a look at why data matters when it comes to the, often times, less nimble world of mobile apps, and how you can accelerate your product design efforts.
First off, every company should make data-driven product design decisions a priority, but having a stable and robust data set can lead to challenges in the world of mobile apps. And waiting for the perfect set of circumstances to do so is not an option.
When it comes to mobile apps, you can create an experience that your customers love and come back to often, but the pain points on the way to getting there can leave you questioning your investment. According to Gartner, less than 0.01% of consumer mobile apps will be considered a financial success by their developers. As you can tell, the competition is fierce, and a lot of businesses may not want to design a mobile app due to expensive development and the possibility of it being a financial risk.
So how does data influence your mobile app product design? With data-driven prioritization, a long-term testing plan, and an analytics practice that focuses on iterating the right features, you can cut through the limitations to deliver results that make an impact, and have a mobile app that is successful.
Let’s begin with comparing the differences between web and mobile app design.
Web Product Design vs Mobile App Design
The world of web product design features a robust suite of testing tools, common coding languages, easy to acquire data, and a fast development cycle. Analytics on the web is a tried and true process where testing and implementing quickly is the norm. A great example is with A/B Testing. In A/B Testing on web, you can create a test, launch it tomorrow, and scope it into the next release once you have a winning experience. Sounds like a smooth process, right?
Native apps, on the other hand, can require more development time to set up a test, leading to a longer cycle between hypothesis and result. Here’s where the pain points and struggles come in. Mobile app tagging requires access to the app code base and may require working side-by-side with developers to implement tagging. This increases the amount of time it takes from identifying a tracking need to having access to the data to tag. This may mean finding ways to work around data collection gaps while waiting for more permanent solutions.
Why Data-Driven Mobile Design?
While these drawbacks in terms of agility may seem like roadblocks in the world of mobile apps, with a disciplined plan, you can move from insight to experiment to optimization, just as you would in the world of web.
There has to be a constant focus on prioritizing features that deliver the greatest conversion impact. It’s important to frame out which are the most impactful insights to action off of, so if your release cycle isn’t as fast as you’d like, you move the needle on the most important things first. By stacking wins and proactively planning for a future state, you can truly build a data-driven optimization culture.
If this sneak peak was not satisfying enough for the data-savvy in you, learn more by checking out my FREE online presentation about this topic at the ObservePoint Analytics Summit.