Three Ways to Improve Your Design Research with Wordle

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“Above all else show the data.”
–Edward Tufte

Survey responses. Product reviews. Keyword searches. Forums. As UX practitioners, we commonly scour troves of qualitative data for customer insight. But can we go faster than line-by-line analysis? Moreover, how can we provide semantic analysis to project stakeholders?

Enter Wordle. If you haven’t played with it yet, Wordle is a free Java application that generates visual word clouds. It can provide a compelling snapshot of user feedback for analysis or presentation.

Using Wordle for content strategy

Wordle excels at comparing company and customer language. Here’s an example featuring one of Apple’s crown jewels, the iPad. This text comes from the official iPad Air web page. After common words are removed and stemmed:

iPad Air Wordle

Apple paints a portrait of exceptional “design” with great “performance” for running “apps.” Emotive adjectives like “incredible,” “new,” and “Smart [Cover]” are thrown in for good measure. Now compare this to customer reviews on


To paraphrase Jakob Nielsen, systems should speak the user’s language. And in this case, customers speak more about the iPad’s “screen” and “fast[er]” processor than anything else. Apps don’t even enter the conversation.

A split test on the Apple website might be warranted. Apple could consider talking less about apps, because users may consider them a commodity by now. Also, customer lingo should replace engineering terms. People don’t view a “display,” they look at a “screen.” They also can’t appreciate “performance” in a vacuum. What they do appreciate is that the iPad Air is “faster” than other tablets.

What does your company or clients say in its “About Us,” “Products,” or “Services” web pages? How does it compare to any user discussions?

Using Wordle in comparative analysis

Wordle can also characterize competing products. For example, take Axure and Balsamiq, two popular wireframing applications. Here are visualizations of recent forum posts from each website. (Again, popular words removed or stemmed.)

Axure Wordle

Balsamiq Wordle

Each customer base employs a distinct dialect. In the first word cloud, Axure users speak programmatically about panels (Axure’s building blocks), widgets, and adaptive design. In the Balsamiq cloud, conversation revolves more simply around assets, text, and projects.

These word clouds also illustrate product features. Axure supports adaptive wireframes; Balsamiq does not. Balsamiq supports Google Drive; Axure does not. Consider using Wordle when you want a stronger and more immediate visual presentation than, say, a standard content inventory.

Beyond comparative analysis, Wordle also surfaces feature requests. The Balsamiq cloud contains the term “iPad” from users clamoring for a tablet version. When reviewing your own Wordle creations, scan for keywords outside your product’s existing features. You may find opportunities for new use cases this way.

Using Wordle in iterative design

Finally, Wordle can compare word clouds over time. This is helpful when you’re interested in trends between time intervals or product releases.

Here’s a word cloud generated from recent Google Play reviews. The application of interest is Temple Run, a game with over 100 million downloads:

Temple Run Wordle

As you can see, players gush about the game. It’s hard to imagine better feedback.

Now let’s look at Temple Run 2, the sequel:

Temple Run sequel Wordle

Still good, but the phrase “please fix” clearly suggests technical problems. A user researcher might examine the reviews to identify specific bugs. When comparing word clouds over time, it’s important to note new keywords (or phrases) like this. These changes represent new vectors of user sentiment.

Wordle can also be tested at fixed time intervals, not just software versions. Sometimes user tastes and preferences evolve without any prompting.


Wordle is a heuristic tool that visualizes plaintext and RSS feeds. This can be quite convenient for UX practitioners to evaluate customer feedback. When seen by clients and stakeholders, the immediacy of a word cloud is more compelling than a typical PowerPoint list. However, keep the following in mind when you use Wordle:

  • Case sensitivity. You must normalize your words to lower (or upper) case.
  • Stemming. You must stem any significant words in your text blocks.
  • Accuracy. You can’t get statistical confidence from Wordle. However, it essentially offers unlimited text input. Try copying as much text into Wordle as possible for best results.
  • Negative phrases. Wordle won’t distinguish positive and negative phrasing. “Good” and “not good” will count as two instances of the word “good.”

That’s it. I hope this has been helpful for imagining text visualizations in your work. Good luck and happy Wordling.


  1. I’m shocked this got publishing on this site. This is a horrible, horrible suggestion. Why would we ever convey to any client any kind of information like this that is obviously completely devoid of context and insight?

    “For starters, word clouds support only the crudest sorts of textual analysis, much like figuring out a protein by getting a count only of its amino acids. This can be wildly misleading”


    “At The New York Times, we strongly believe that visualization is reporting, with many of the same elements that would make a traditional story effective: a narrative that pares away extraneous information to find a story in the data; context to help the reader understand the basics of the subject; interviewing the data to find its flaws and be sure of our conclusions. […] Of course, word clouds throw all these principles out the window.” (source:

    I would be embarrassed to show this to a client.

  2. There’s no way I’d show this to a client. What I do think this is good for is finding a starting place. I’m working on something right now that is being built from the ground up out of my head. I need to do some competitive analysis and running some stuff through this gets me that sometimes evasive starting point and motivation.

    So I can see the benefit of it on a personal use basis, but I would NEVER use it as anything other than a pointer. Any conclusions I draw from it need to be reviewed and tested through other avenues.

  3. Regarding the first comment – Wordle is indeed a simple application. Like the New York Times, I probably wouldn’t use it to explain the Iraq War either. (Dear Lord.)

    That being said, any heuristic tool by definition is a timesaver. Comparing word clouds to multidimensional infographics is like comparing, say, to Morae.

    “Context” also deserves a more mature treatment. iPad terms like “screen” and “display” examine the context of vocabulary, not definitions. Reading the raw data for deeper understanding is usually important, as time allows.


  4. I totally agree with the first comment that this would be highly impractical to show to a client, but for internal testing and focussing I think it’s a great idea, especially done as a longitudinal study of users reaction to a product / feature over multiple iterations of design and/or development.

    Without some diligence any system can be abused, this would need some work to be useful, as stated in the article – Stemming and Negative Phrasing are two potential pitfalls, but treated correctly I can’t help but think this would be beneficial.

    Thanks for the great piece.


  5. totally agree with the first comment that this would be highly impractical to show to a client, but for internal testing and focussing I think it’s a great idea, especially done as a longitudinal study of users reaction to a product / feature over multiple iterations of design and/or development

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