Short answer is: as much as possible.
The more data you have, the more likely you can make correct inference. In the worse case, you could simply discard anything that you don't like. It's like money, the more the better - you always have an option to spend or use less.
Statistics could be doggy without sufficient sample size, your statistical power would be affected and any model you have could be biased.
Having said that, you don't want everything from your user. Use your common sense, and ask yourself what exactly you want to do.
Based only on the data in your question, I'd say: (I could be wrong because I don't understand where you got the data)
- How many total users you have that didn't drop out? If your total user base is like 10K, 28 users dropping out is not a problem. But if you only have 30 users...
- Your sample size is small. Is that one-day installation? In any case, 28 users for a mobile app is a tiny data set. You may want to focus more on marketing.
How many respondent you need is hard to tell. Apple probably needs better data quality than you. If you'd like to do it statistically, you may calculate the minimum sample size and it's related to statistical power.