pandas Series apply returns dtype:datetime though convert_dtype is set to False
pandas version 0.24.2

#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
import datetime

thisdf = pd.DataFrame({'date':['12.01.1999','','28.04.2012']})

def parseDate(date):
    try:
        return datetime.datetime.strptime(date,'%d.%m.%Y')
    except Exception:
        return None
    
print(thisdf.date.apply(parseDate, convert_dtype=False))
```
Output:
```
0   1999-01-12
1          NaT
2   2012-04-28
Name: date, dtype: datetime64[ns]
```
#### Problem description

I want to parse a pandas Series containing strings to datetime using the above function `parseDate`. The important thing is that `None` values **must not** be converted to `NaT` because I put it into a SQLAlchemy database afterwards which only recognizes `None` values as NULL. Hence the returned Series must be of `dtype object`. However, all methods I tried return the Series with `dtype: datetime64[ns]` after parsing. 

The solution of #14559 (using `.astype(object)` after the apply) does not help because the `NaT` values are still `NaT` values instead of None. Of course I could do another round of transformation after that but looping through twice does not seem very performant to me.

Any help appreciated .

#### Expected Output
A pandas Series with dtype=object

#### Output of ``pd.show_versions()``

<details>

[paste the output of ``pd.show_versions()`` here below this line]
INSTALLED VERSIONS
------------------
commit: None
python: 3.7.3.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
byteorder: little
LC_ALL: None
LANG: en
LOCALE: None.None

pandas: 0.24.2
pytest: 4.3.1
pip: 19.0.3
setuptools: 40.8.0
Cython: 0.29.6
numpy: 1.16.2
scipy: 1.2.1
pyarrow: None
xarray: None
IPython: 7.4.0
sphinx: 1.8.5
patsy: 0.5.1
dateutil: 2.8.0
pytz: 2018.9
blosc: None
bottleneck: 1.2.1
tables: 3.5.1
numexpr: 2.6.9
feather: None
matplotlib: 3.0.3
openpyxl: 2.6.1
xlrd: 1.2.0
xlwt: 1.3.0
xlsxwriter: 1.1.5
lxml.etree: 4.3.2
bs4: 4.7.1
html5lib: 1.0.1
sqlalchemy: 1.3.1
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None
</details>
