I think there are some things to consider.
Collecting data is trivial (you already said you'll use GA). You won't need to save anything; data is in the cloud, so you can generate reports as needed.
Now, about a new feature: you can use regression analysis or ANOVA to measure this, and you won't even need to test with users. Unless your feature is detrimental to the existing features, the worst-case scenario is a status that equals 0 (this article on Quantum UX may be of help).
Quantum UX Energy is a fundamental concept of the QUX paradigm: it is
what enables UX to acquire this Q, so to speak. In other words, it is
multiple information flows that set a static system in motion.
To understand it better: Let’s take a web page. Let’s say we see it in
its initial state, the day we launch it, before anyone else sees it.
This page will have an energy level (QUXE) of 0.
But once we observe its behavior and performance, we get data that
allows us to make decisions.
- increase or decrease the amount of advertising purchased
- reposition elements to do CTR tests
- develop engagement strategies
- create marketing strategies with multiple products
- define geographically localized strategies
- analyze results and create probabilistic predictions
As we can see, all the usual things that any more or less serious
company does on a daily basis, with tools that are available to
everyone. And just in case we’re talking about free analytics tools .
So once we have the data from multiple sources, at different times,
with different variables, we can take action.
In other words, the initial static element will have different types
of interactions; from stakeholders, from users, from dynamic content
scripts, from advertisers, and so on.
Therefore, it is logical to say that the static element already has an
energy charge that it did not have at another point in time. This
energy can be represented with formulas and equations. And at the same
time becomes part of other equations that allow us to generate more
efficient probabilistic systems than those we could develop by looking
at the data.
Technically, you can add a new feature every day, but it will be quite complex to measure its effects on the app, and of course, it will confuse users. However, adding a feature every now and then is a good idea because you're signaling to users that your app is under continuous development. More likely than not, engagement will be greater than zero.
In short: as long as you measure the effects, you'll be fine. Nonetheless, if you can't test with users before launch, I'd highly advise conducting very thorough QA.