First, ensure you have access to ChartMogul's API. Log in to your ChartMogul account, navigate to the API section, and create an API key. This key will allow you to authenticate and interact with your ChartMogul data programmatically.

Use a script to interact with ChartMogul's API and retrieve the desired data. You can use programming languages like Python with libraries such as `requests`. For example, use:
```python
import requests

API_KEY = 'your_api_key'
url = 'https://api.chartmogul.com/v1/data_endpoint'

response = requests.get(url, auth=(API_KEY, ''))
data = response.json()
```
Replace `data_endpoint` with the specific endpoint you need, such as customers or subscriptions.

Once you have the data, process it into a structured format like CSV or JSON. This makes it suitable for storage and later analysis. You can use Python's `pandas` library to convert the data into a DataFrame and then export it:
```python
import pandas as pd

df = pd.DataFrame(data['entries'])
df.to_csv('chartmogul_data.csv', index=False)
```
Adjust the key `entries` based on the specific structure of the API response.

Log in to your AWS Management Console and create an S3 bucket if you haven't already. Note the bucket name and region, as you'll need these for uploading files. Ensure you have the necessary permissions to write to this bucket.

Install and configure the AWS CLI on your local machine or server. Use the following commands:
```bash
aws configure
```
Enter your AWS Access Key, Secret Access Key, region, and output format when prompted. This sets up your credentials and allows you to interact with AWS services.

Use the AWS CLI to upload your processed data file to the S3 bucket. Run the following command:
```bash
aws s3 cp chartmogul_data.csv s3://your-bucket-name/path/to/destination/
```
Replace `your-bucket-name` and `path/to/destination` with your bucket’s details. This command copies the local file to your specified S3 path.

Finally, verify that the data was uploaded successfully. You can do this by checking the AWS S3 console or by listing the contents of the S3 bucket using the AWS CLI:
```bash
aws s3 ls s3://your-bucket-name/path/to/destination/
```
Confirm that your file appears in the list, ensuring the data is now stored safely in S3.

By following these steps, you can successfully transfer data from ChartMogul to AWS S3 without relying on third-party connectors.