Question: Using a neural network (LSTM) I'm making an objective features prediction (I have multiple features). Good accuracy is observed during operation. But can I show the effect of any feature on the target feature?

For example, I am predicting a user purchase on a site and want to estimate the impact of a discount on a purchase. That is, to show that such and such a discount will or will not be such a purchase. How to do this using an existing neural network for prediction?

Answer: 
Neural Networks are **black box** models, they do not provide explanation for their decisions. Answer to such a question is essentially a whole research area.
There are indeed techniques to get insights like that for a already **trained** model.

You can start with

* **Partial Dependence Plots** (will show you how a change in your feature's value will effect the target variable). A great explanation can be found here: <https://www.kaggle.com/dansbecker/partial-dependence-plots>
* **Permutation Importance** (will show you how important the feature is for the model to make its prediction). A great explanation can be found here: <https://www.kaggle.com/dansbecker/permutation-importance>