Begin by logging into your Klaviyo account. Navigate to the list or segment you want to export. Use Klaviyo's built-in export functionality to download the data in a CSV format. Ensure that you have the necessary permissions to export the data you need.

Ensure that your local environment has the necessary tools to process CSV files and interact with Redis. Install Python and its required libraries, such as `pandas` for data manipulation and `redis-py` for connecting to Redis. Run `pip install pandas redis` to get started.

Use Python to read the CSV file. Utilize the `pandas` library to load the data into a DataFrame for easy manipulation. This step allows you to clean, filter, or transform the data as needed before inserting it into Redis. Here is a basic code snippet to load a CSV:
```python
import pandas as pd

data = pd.read_csv('klaviyo_data.csv')
```

Ensure that you have a Redis server running and accessible. You can install Redis locally or use a cloud-based instance. Verify the connection by using a Redis client or the command line interface to connect to your Redis instance.

Use the `redis-py` library to establish a connection to your Redis server. Here is a basic code snippet to connect to Redis:
```python
import redis

r = redis.StrictRedis(host='localhost', port=6379, db=0)
```

Iterate over the DataFrame rows and insert each record into Redis. Decide on the data structure you want to use in Redis (e.g., strings, hashes, lists). For example, you might store each row as a hash:
```python
for index, row in data.iterrows():
user_id = row['user_id']
r.hset(f'user:{user_id}', mapping=row.to_dict())
```

After transferring the data, verify that it has been correctly inserted into Redis. Use the Redis CLI or a client to query data and ensure that it matches the original CSV file. This step is crucial for ensuring data consistency and accuracy.

By following these steps, you can successfully move data from Klaviyo to Redis without the need for third-party connectors or integrations.