The powerful analysis features in our card sorting tool

Taylor Swift's music has captivated millions, but what do her fans really think about her extensive catalog? We've crunched the numbers, analyzed the data, and uncovered some fascinating insights into how Swifties perceive and categorize their favorite artist's work. Let's dive in!

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The great debate: openers, encores, and everything in between ⋆.˚✮🎧✮˚.⋆

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Our study asked fans to categorize Swift's songs into potential opening numbers, encores, and songs they'd rather not hear (affectionately dubbed "Nah" songs). The results? As diverse as Swift's discography itself!

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Opening with a bang 💥

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Swifties seem to agree that high-energy tracks make for the best concert openers, but the results are more nuanced than previously suggested. "Shake It Off" emerged as the clear favorite for opening a concert, with 17 votes. "Love Story" follows closely behind with 14 votes, showing that nostalgia indeed plays a significant role. Interestingly, both "Cruel Summer" and "Blank Space" tied for third place with 13 votes each.

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This mix of songs from different eras of Swift's career suggests that fans appreciate both her newer hits and classic favorites when it comes to kicking off a show. The strong showing for "Love Story" does indeed speak to the power of nostalgia in concert experiences. It's worth noting that "...Ready for It?", while a popular song, received fewer votes (9) for the opening slot than might have been expected.

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Encore extravaganza 🎤

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When it comes to encores, fans seem to favor a diverse mix of Taylor Swift's discography, with a surprising tie at the top. "Slut!" (Taylor's Version), "exile", "Guilty as Sin?", and "Bad Blood (Remix)" all received the highest number of votes with 13 each. This variety showcases the breadth of Swift's career and the different aspects of her artistry that resonate with fans for a memorable show finale.

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Close behind are "evermore", "Wildest Dreams", "ME!", "Love Story", and "Lavender Haze", each garnering 12 votes. It's particularly interesting to see both newer tracks and classic hits like "Love Story" maintaining strong popularity for the encore slot. This balance suggests that Swifties appreciate both nostalgia and Swift's artistic evolution when it comes to closing out a concert experience.

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The "Nah" list 😒

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Interestingly, some of Taylor Swift's tracks found themselves on the "Nah" list, indicating that fans might prefer not to hear them in a concert setting. "Clara Bow" tops this category with 13 votes, closely followed by "You're On Your Own, Kid", "You're Losing Me", and "Delicate", each receiving 12 votes.

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This doesn't necessarily mean fans dislike these songs - they might just feel they're not well-suited for live performances or don't fit as well into a concert setlist. It's particularly surprising to see "Delicate" on this list, given its popularity. The presence of both newer tracks like "Clara Bow" and older ones like "Delicate" suggests that the "Nah" list isn't tied to a specific era of Swift's career, but rather to individual song preferences in a live concert context.

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It's worth noting that even popular songs can end up on this list, highlighting the complex relationship fans have with different tracks in various contexts. This data provides an interesting insight into how Swifties perceive songs differently when considering them for a live performance versus general listening.

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The Similarity Matrix: set list synergies ⚡

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Our similarity matrix revealed fascinating insights into how fans envision Taylor Swift's songs fitting together in a concert set list:

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1. The "Midnights" Connection: Songs from "Midnights" like "Midnight Rain", "The Black Dog", and "The Tortured Poets Department" showed high similarity in set list placement. This suggests fans see these tracks working well in similar parts of a concert, perhaps as a cohesive segment showcasing the album's distinct sound.

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2. Cross-album transitions: There's an intriguing connection between "Guilty as Sin?" and "exile", with a high similarity percentage. This indicates fans see these songs from different albums as complementary in a live setting, potentially suggesting a smooth transition point in the set list that bridges different eras of Swift's career.

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3. The show-stoppers: "Shake It Off" stands out as dissimilar to most other songs in terms of placement. This likely reflects its perceived role as a high-energy, statement piece that occupies a unique position in the set list, perhaps as an opener, closer, or peak moment.

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4. Set list evolution: There's a noticeable pattern of higher similarity between songs from the same or adjacent eras, suggesting fans envision distinct segments for different periods of Swift's career within the concert. This could indicate a preference for a chronological journey through her discography or strategic placement of different styles throughout the show.

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5. Thematic groupings: Some songs from different albums showed higher similarity, such as "Is It Over Now? (Taylor's Version)" and "You're On Your Own, Kid". This suggests fans see them working well together in the set list based on thematic or emotional connections rather than just album cohesion.

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What does it all mean?! 💃🏼📊

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This card sort data paints a picture of an artist who continually evolves while maintaining certain core elements that define her work. Swift's ability to create cohesive album experiences, make bold stylistic shifts, and maintain thematic threads throughout her career is reflected in how fans perceive and categorize her songs. Moreover, the diversity of opinions on song categorization - with 59 different songs suggested as potential openers - speaks to the depth and breadth of Swift's discography. It also highlights the personal nature of music appreciation; what one fan sees as the perfect opener, another might categorize as a "Nah".

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In the end, this analysis gives us a fascinating glimpse into the complex web of associations in Swift's discography. It shows us not just how Swift has evolved as an artist, but how her fans have evolved with her, creating deep and sometimes unexpected connections between songs across her entire career. Whether you're a die-hard Swiftie or a casual listener, or a weirdo who just loves a good card sort, one thing is clear: Taylor Swift's music is rich, complex, and deeply meaningful to her fans. And with each new album, she continues to surprise, delight, and challenge our expectations.

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Conclusion: shaking up our understanding 🥤🤔

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This deep dive into the Swiftie psyche through a card sort reveals the complexity of Taylor Swift's discography and fans' relationship with it. From strategic song placement in a dream setlist to unexpected cross-era connections, we've uncovered layers of meaning that showcase Swift's artistry and her fans' engagement. The exercise demonstrates how a song can be a potential opener, mid-show energy boost, poignant closer, or a skip-worthy track, highlighting Swift's ability to create diverse, emotionally resonant music that serves various roles in the listening experience.

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The analysis underscores Swift's evolving career, with distinct album clusters alongside surprising connections, painting a picture of an artist who reinvents herself while maintaining a core essence. It also demonstrates how fan-driven analyses like card sorting can be insightful and engaging, offering a unique window into music fandom and reminding us that in Swift's discography, there's always more to discover. This exercise proves valuable whether you're a die-hard Swiftie, casual listener, or someone who loves to analyze pop culture phenomena.

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Card sorting is an invaluable tool for understanding how people organize information in their minds, making websites more intuitive and content easier to navigate. It’s a useful method outside of information architecture and UX research, too. It can be a useful prioritization technique, or used in a more traditional sense. For example, it’s handy in psychology, sociology or anthropology to inform research and deepen our understanding of how people conceptualize information.

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The introduction of remote card sorting has provided many advantages, making it easier than ever to conduct your own research. Tools such as our very own OptimalSort allow you to quickly and easily gather findings from a large number of participants from all around the world. Not having to organize moderated, face-to-face sessions gives researchers more time to focus on their work, and easier access to larger data sets.

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One of the main disadvantages of remote card sorting is that it eliminates the opportunity to dive deeper into the choices made by your participants. Human conversation is a great thing, and when conducting a remote card sort with users who could potentially be on the other side of the world, opportunities for our participants to provide direct feedback and voice their opinions are severely limited.Your survey design may not be perfect.

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The labels you provide your participants may be incorrect, confusing or redundant. Your users may have their own ideas of how you could improve your products or services beyond what you are trying to capture in your card sort. People may be more willing to provide their feedback than you realize, and limiting their insights to a simple card sort may not capture all that they have to offer.So, how can you run an unmoderated, remote card sort, but do your best to mitigate this potential loss of insight?

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A quick look into the data

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In an effort to evaluate the usefulness of the existing “Leave a comment” feature in OptimalSort, I recently asked our development team to pull out some data.You might be asking “There’s a comment box in OptimalSort?”If you’ve never noticed this feature, I can’t exactly blame you. It’s relatively hidden away as an unassuming hyperlink in the top right corner of your card sort.

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Comments left by your participants can be viewed in the “Participants” tab in your results section, and are indicated by a grey speech bubble.

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The history of the button is unknown even to long-time Optimal Workshop team members. The purpose of the button is also unspecified. “Why would anyone leave a comment while participating in a card sort?”, I found myself wondering.As it turns out, 133,303 comments have been left by participants. This means 133,303 insights, opinions, critiques or frustrations. Additionally, these numbers only represent the participants who noticed the feature in the first place. Considering the current button can easily be missed when focusing on the task at hand, I can’t help but wonder how this number might change if we drew more attention to the feature.

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Breaking down the comments

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To avoid having to manually analyze and code 133,303 open text fields, I decided to only spend enough time to decipher any obvious patterns. Luckily for me, this didn’t take very long. After looking at only a hundred or so random entries, four distinct types of comments started to emerge.

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1. This card/group doesn’t make sense.Comments related to cards and groups dominate. This is a great thing, as it means that the majority of comments made by participants relate specifically to the task they are completing. For closed and hybrid sorts, comments frequently relate to the predefined categories available, and since the participants most likely to leave a comment are those experiencing issues, the majority of the feedback relates to issues with category names themselves. Many comments are related to card labels and offer suggestions for improving naming conventions, while many others draw attention to some terms being confusing, unclear or jargony. Comments on task length can also be found, along with reasons for why certain cards may be left ungrouped, e.g., “I’ve left behind items I think the site could do without”.
2. Your organization is awesome for doing this/you’re doing it all wrong. A substantial number of participants used the comment box as an opportunity to voice their general feedback on the organization or company running the study. Some of the more positive comments include an appreciation for seeing private companies or public sector organizations conducting research with real users in an effort to improve their services. It’s also nice to see many comments related to general enjoyment in completing the task.On the other hand, some participants used the comment box as an opportunity to comment on what other areas of their services should be improved, or what features they would like to see implemented that may otherwise be missed in a card sort, e.g., “Increased, accurate search functionality is imperative in a new system”.
3. This isn’t working for me. Taking a closer look at some of the comments reveals some useful feedback for us at Optimal Workshop, too. Some of the comments relate specifically to UI and usability issues. The majority of these issues are things we are already working to improve or have dealt with. However, for researchers, comments that relate to challenges in using the tool or completing the survey itself may help explain some instances of data variability.
4. #YOLO, hello, ;) And of course, the unrelated. As you may expect, when you provide people with the opportunity to leave a comment online, you can expect just about anything in return.

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How to make the most of your user insights in OptimalSort

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If you’re running a card sort, chances are you already place a lot of value in the voice of your users. To ensure you capture any additional insights, it’s best to ensure your participants are aware of the opportunity to do so. Here are two ways you may like to ensure your participants have a space to voice their feedback:

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‍Adding more context to the “Leave a comment” feature

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One way to encourage your participants to leave comments is to promote the use of the this feature in your card sort instructions. OptimalSort gives you flexibility to customize your instructions every time you run a survey. By making your participants aware of the feature, or offering ideas around what kinds of comments you may be looking for, you not only make them more likely to use the feature, but also open yourself up to a whole range of additional feedback. An advantage of using this feature is that comments can be added in real time during a card sort, so any remarks can be made as soon as they arise.

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‍Making use of post-survey questions

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‍Adding targeted post-survey questions is the best way to ensure your participants are able to voice any thoughts or concerns that emerged during the activity. Here, you can ask specific questions that touch upon different aspects of your card sort, such as length, labels, categories or any other comments your participants may have. This can not only help you generate useful insights but also inform the design of your surveys in the future.

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Make your remote card sorts more human

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Card sorts are exploratory by nature. Avoid forcing your participants into choices that may not accurately reflect their thinking by giving them the space to voice their opinions. Providing opportunities to capture feedback opens up the conversation between you and your users, and can lead to surprising insights from unexpected places.

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Further reading

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• "Moderated card sorts vs online card sorts — why you need both" - An article on our blog that explains some of the differences between these two methods and how to use both for great results.
• "The hidden benefits of remote research" - Kathleen Asjes writes for UX Booth and explains when to use remote research and some of its many benefits.
• "Remote research: real users, real time, real research" - A book by Nate Bolt and Tony Tulathimutte on how to design and conduct remote research studies.

A great information architecture (IA) is essential for a great user experience (UX). And testing your website or app’s information architecture is necessary to get it right.

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Card sorting and tree testing are the very best UX research methods for exactly this. But the big question is always: which one should you use, and when? Very possibly you need both. Let’s find out with this quick summary.

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What is card sorting and tree testing? 🧐

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Card sorting is used to test the information architecture of a website or app. Participants group individual labels (cards) into different categories according to  criteria that makes best sense to them. Each label represents an item that needs to be categorized. The results provide deep insights to guide decisions needed to create an intuitive navigation, comprehensive labeling and content that is organized in a user-friendly way.

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Tree testing is also used to test the information architecture of a website or app. When using tree testing participants are presented with a site structure and a set of tasks they need to complete. The goal for participants is to find their way through the site and complete their task. The test shows whether the structure of your website corresponds to what users expect and how easily (or not) they can navigate and complete their tasks.

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What are the differences? 🂱 👉🌴

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Card sorting is a UX research method which helps to gather insights about your content categorization. It focuses on creating an information architecture that responds intuitively to the users’ expectations. Things like which items go best together, the best options for labeling, what categories users expect to find on each menu.

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Doing a simple card sort can give you all those pieces of information and so much more. You start understanding your user’s thoughts and expectations. Gathering enough insights and information to enable you to develop several information architecture options.

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Tree testing is a UX research method that is almost a card sort in reverse. Tree testing is used to evaluate an information architecture structure and simply allows you to see what works and what doesn’t. 

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Using tree testing will provide insights around whether your information architecture is intuitive to navigate, the labels easy to follow and ultimately if your items are categorized in a place that makes sense. Conversely it will also show where your users get lost and how.

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What method should you use? 🤷

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You’ve got this far and fine-tuning your information architecture should be a priority. An intuitive IA is an integral component of a user-friendly product. Creating a product that is usable and an experience users will come back for.

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If you are still wondering which method you should use - tree testing or card sorting. The answer is pretty simple - use both.

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Just like many great things, these methods work best together. They complement each other, allowing you to get much deeper insights and a rounded view of how your IA performs and where to make improvements than when used separately. We cover more reasons why card sorting loves tree testing in our article which dives deeper into why to use both.

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Ok, I'm using both, but which comes first? 🐓🥚

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Wanting full, rounded insights into your information architecture is great. And we know that tree testing and card sorting work well together. But is there an order you should do the testing in? It really depends on the particular context of your research - what you’re trying to achieve and your situation. 

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Tree testing is a great tool to use when you have a product that is already up and running. By running a tree test first you can quickly establish where there may be issues, or snags. Places where users get caught and need help. From there you can try and solve potential issues by moving on to a card sort. 

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Card sorting is a super useful method that can be instigated at any stage of the design process, from planning to development and beyond.  As long as there is an IA structure that can be tested again. Testing against an already existing website navigation can be informative. Or testing a reorganization of items (new or existing) can ensure the organization can align with what users expect.

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However, when you decide to implement both of the methods in your research, where possible, tree testing should come before card sorting. If you want a little more on the issue have a read of our article here.

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Check out our OptimalSort and Treejack tools - we can help you with your research and the best way forward. Wherever you might be in the process.