Create Your Own Spotify Wrapped: A Step-by-Step Guide
In an innovative twist on Spotify’s Wrapped AI Podcast, a user created a personalized version utilizing NotebookLM after finding the original unavailable in their region. This endeavor not only showcased individual listening habits but also highlighted the potential of AI in crafting unique audio experiences.
Limited Access Sparks Creativity
When Spotify and Google announced their Wrapped AI Podcast in December 2024, excitement surged among users. However, the podcast was accessible only to Spotify users in select regions: the United States, United Kingdom, Australia, New Zealand, Canada, Ireland, and Sweden. This limitation left many fans, including the author, feeling excluded.
Determined to join in on the fun, the author explored various methods to access the podcast, including VPNs, but to no avail. With Spotify Wrapped 2025 approaching, the author devised a creative solution: creating a personalized version of the podcast using NotebookLM. This venture not only catered to their desire for a Wrapped experience but also showcased the platform’s capabilities.
Crafting a Customized Podcast Experience
The first step involved gathering listening history, which is crucial for generating a Wrapped-style podcast. While Spotify allows users to download their listening history, the process can take several days. Instead, the author opted for data from Last.fm, where they had logged their listening habits for the past ten months. This data provided a comprehensive view of their musical preferences, eliminating the wait.
Using a user-friendly tool called BenjaminBenBen, the author quickly exported their Last.fm data into a clean CSV file. This file included details such as artist names, album titles, track information, and timestamps. To integrate this data with NotebookLM, the author converted the CSV file into a PDF format, as NotebookLM does not currently support CSV or XML files.
Once the data was loaded into NotebookLM, the author crafted a custom prompt to generate the audio recap. The prompt instructed the AI to emulate the upbeat and engaging style of Spotify’s Wrapped AI Podcast, while also encouraging natural banter between the hosts. The aim was to create a lively recap of the author’s musical year, exploring listening patterns, standout moments, and evolving preferences.
The author decided to generate two versions of the podcast: a Short and a Default version. The Short version aimed for brevity, while the Default version provided a more in-depth exploration, resulting in approximately ten minutes of content.
The results were impressive. The generated podcast highlighted the author’s top artists, most-played tracks, and even revealed trends that had gone unnoticed, such as fluctuations in listening habits across different months. Feedback from colleagues who had experienced the original Wrapped AI Podcast provided further insights. While some noted the original’s brevity, others appreciated the depth of analysis in the author’s version.
On comparing notes, the author found that while the original podcast referenced Spotify’s official metrics, their version relied solely on Last.fm data, offering a different perspective. The AI-generated podcast delved deeper into personal statistics, revealing unique insights into the author’s listening behavior.
The author reviewed a few official Wrapped AI Podcast episodes on YouTube to better understand the style and pacing. They noted similarities in tone and pacing, with both podcasts maintaining a relaxed, conversational flow. The natural humor and camaraderie between the AI hosts mirrored the experience users might expect from the original.
Overall, this DIY project not only filled the gap left by the unavailability of the official podcast but also served as a testament to the capabilities of AI in personalizing audio experiences. The process took only about five minutes to set up and resulted in a podcast that felt tailored and engaging.
For those who felt left out of the Spotify Wrapped experience, creating a personalized version using NotebookLM offers a fun and satisfying alternative. It showcases the potential for individual expression in the age of AI, making the journey through one’s musical year an exciting adventure.
