Begin by familiarizing yourself with the data structure in Drift. This involves identifying the data types, formats, and how the data is organized or stored. Access Drift's API documentation to understand the endpoints available for data retrieval, such as conversations, contacts, and user events.

Prepare your development environment by ensuring you have the necessary tools and libraries to interact with Drift's API and Redis. You will need a programming language like Python, Node.js, or Ruby, along with their respective HTTP request libraries (e.g., `requests` for Python or `axios` for Node.js) and Redis client libraries.

Obtain the necessary API keys or tokens to authenticate your requests to Drift's API. This typically involves generating a personal access token or OAuth token from Drift's developer portal. Use this token to authenticate your API requests, ensuring you have the required permissions to access the data you need.

Write a script to extract the data from Drift using their API. Use the authenticated HTTP requests to fetch data from the desired endpoints. Ensure you handle pagination if the dataset is large by iterating over pages of results. Parse the response data into a format that can be easily manipulated, such as JSON or a Python dictionary.

Format and transform the extracted data into a structure suitable for Redis storage. Consider how you want to organize the data in Redis, such as using hashes, lists, or sets. Convert the data to string format if necessary, as Redis primarily stores data as strings, and decide on meaningful keys for your data entries.

Establish a connection to your Redis server using a Redis client library in your chosen programming language. Use the `SET`, `HSET`, or other relevant Redis commands to insert the formatted data into Redis. Ensure you handle exceptions and errors that may occur during the connection and insertion process.

After inserting the data, verify that the data has been correctly transferred and stored in Redis. Use Redis commands like `GET`, `HGET`, or `LRANGE` to fetch and inspect the data. Compare a sample of the data in Redis with the original data from Drift to ensure accuracy and completeness. Additionally, consider implementing logging or error handling to track the success of the data migration process.