Why we need experimental frameworks for creating new models? The answer is that when you are planning to create a personalized model, which is nothing but a blend of your small experiments, carefully chosen algorithms, and a cup of common sense, then you need a fail-safe, sophisticated, and user-friendly ground where you can test your creative model, right? Particularly, if you are an experimenter with non-IT background, you need something very cool, easy-to-use, and simple experimental framework; using which you can test your innovative analytical models.
Actually, it is here where you check your understanding of your customers at a high scale. The overall idea is that your experimental framework should be in a position to understand your hypothesis and do the needed rest; it should allow you to enforce your experimental techniques at a scale and speed that you are OK with. Having data and sophisticated algorithms alone cannot ensure that you can create a better experience to your users. You need to anchor your actions in meaningful and result-oriented experiments to create an innovative and successful model using a solid experimental framework.
In summary, experimental framework acts as your testing ground where you can check your creative innovative models in a fail-safe mode before you start testing them on your real-time data.