In general, yes, expect the same response as long as your training data is a good sample and the observation window of your model makes sense to you.
The more similar the training data to your scoring data, the more similar the response rate. In other words, the more similar the distribution of each input for both the target events (response in this case) and for the non-target events (non-response), the closer your response will be to the 10% response rate of your training data.
This is because you are assuming your data is a sample that can be scaled linearly and because you used training data that captures any seasonality and you expect the response rate to keep fairly steady in the future.
I hope it helps,
Thanks,
Miguel