First, you need to export the data from Reply.io. Log into your Reply.io account and navigate to the section containing the data you wish to transfer (e.g., contacts, campaigns). Use the export functionality provided by Reply.io to download the data in a CSV format. This will be the raw data set you will work with to load into Amazon Redshift.

After downloading the CSV file, inspect the data to ensure it is clean and formatted correctly. Open the CSV file using a spreadsheet application or a text editor and check for any inconsistencies like missing headers, incorrect data types, or formatting issues. Make any necessary corrections to ensure the data will align with the Redshift table schema you'll create.

To load data into Redshift, you first need to store your CSV files in an Amazon S3 bucket. Log into your AWS account and create a new S3 bucket if you don’t have one already. Ensure the bucket is properly configured with the necessary permissions to allow access from Redshift. Upload your CSV files to this S3 bucket.

If you haven’t already set up a Redshift cluster, you’ll need to do so. Log into the AWS Management Console and navigate to the Redshift service. Launch a new cluster, specifying your preferred configurations such as node type, number of nodes, and security settings. Take note of the cluster’s endpoint and database credentials as you will need them to connect to Redshift.

Access your Redshift database using a SQL client or AWS Query Editor. Create a new table that matches the schema of your CSV data. Use the `CREATE TABLE` SQL command, defining the table name, column names, and data types to match those of your CSV file. Ensure the table is configured to handle the expected volume of data.

Use the `COPY` command in Redshift to load data from your S3 bucket into your Redshift table. The command will look something like this:
```sql
COPY your_table_name
FROM 's3://your-bucket-name/your-file.csv'
CREDENTIALS 'aws_access_key_id=your_access_key;aws_secret_access_key=your_secret_key'
CSV
IGNOREHEADER 1;
```
Replace placeholders with your actual table name, S3 bucket path, and AWS credentials. The `IGNOREHEADER 1` parameter is used to skip the header row in the CSV file.

After the data has been loaded into Redshift, run queries against your table to verify that the data has been transferred correctly and that there are no discrepancies or missing entries. Check for consistency, validate data types, and ensure that all records have been imported. This step ensures that your data in Redshift accurately reflects the original data from Reply.io.

By following these steps, you can manually transfer data from Reply.io to Amazon Redshift without relying on third-party connectors or integrations.