A/B testing has no doubt become ubiquitous in almost every business sector there is. Recently, though, the concept on everyone’s lips is A/B/n testing. It’s similar to its predecessor except it takes the testing process one step further by allowing to test multiple variables. While A/B/n testing has been a major player in the marketing industry for quite a few years, many companies see the value of applying the model to every level of their business which is being referred to as full-stack experimentation. If you’re ready to learn more about constant testing at all levels, keep this in mind.
The basics of full-stack
At its core, full-stack experimentation is testing at every single level of the analytics and data “stack.” It’s rapidly changing the face of development because it’s allowing developers and engineers to run this testing that was initially conducted by marketing teams. Previously, it was restricted to larger companies with extensive resources and technological know-how as a result of its prior custom stack needs. Luckily, software developments are making it easier for smaller companies to get their hands on full-stack solutions that were previously inaccessible.
One of the best applications of full-stack experimentation is through the use of a feature flag. Feature flagging turns large blocks of application code on and off to test performance at several levels which allows users to observe larger changes in real time. It’s a great way to test market readiness as a whole, but also helps both marketers, product managers, and engineers to collaborate to ensure that their products or applications are performing optimally much quicker than smaller tests would allow.
Experimentation applications
Full-stack experimentation allows for more granular analysis of a product’s performance. It allows you to determine precisely how an application is being used as well as how its users are receiving it. One of the biggest uses of this type of experimentation is testing for failures— the majority of which are the primary ways for product marketers to determine the efficacy of their applications. This is especially true of the larger scale of full-stack experimentation, where a majority of those experiments don’t readily pan out. It allows product marketers to steer away from trends and messaging that align with failed experimentation.
For developers and engineers, it’s an excellent way to weed out consistent failures and flag them for either replacement or retooling. It’s also enhancing the role of quality assurance engineers in that it’s helping streamline aspects of manual testing to change the role of a tester from being inherently reactive to the bugs that appear, to allowing them to be proactive in searching for defects during all stages of the development lifecycle.
Wider availability
Whereas full-stack experimentation was once limited to the companies with the most resources to allocate, several institutions are making it easier for smaller businesses to gain access. A handful of lineups are making it easier to implement changes at every step of the customer journey while simultaneously monitoring performance. These full-stack options are a great way for businesses to reduce risk and identify failure points much faster, which prevents products from being released to the public in unfinished or unstable states. This prevents reputational damages and increases buyer confidence across the board.
The time for implementation
If you’re ready to implement full-stack experimentation to your business, the time has never been better. With the wide variety of testing options available to not only marketers, but engineers and developers, as well, it’s a great time to ensure the overall quality of your products and applications before they are in customer-facing positions. Do your utmost to produce excellence through the capabilities of full-stack experimentation and your clientele will thank you.
