Lessons Learned from the Feedback Loop

Nicole Klassen
5 min readApr 11, 2022

In the past year since joining the Tableau community I have learned so much as a data viz professional. Being open to new ideas and feedback has been vital in my growth. I am appreciative of all the feedback I have been given, so when Michelle Frayman proposed her and I co-running The Feedback Loop I very enthusiastically said yes because I also wanted to learn how to give constructive feedback.

Giving constructive feedback is hard! It’s easy to tell someone “I’d change this” or “this should be vizzed a different way,” but that isn’t constructive and can actually be harmful. There are many blogs out there around how to give feedback. This article by Josh not only outlines the fundamentals of how the Feedback Loop approaches feedback but also links to some other articles that provide great content as well. Below are the tips I found the most helpful as I started providing feedback to those who asked for it.

  1. Be cautious about providing unsolicited feedback, especially publicly. This article by Ben Jones gives some great talking points about providing unsolicited feedback. It can be easy to think that giving unsolicited feedback is necessary to help avoid creating a “Love Fest” community; it can prompt conversations and help people grow. But giving feedback is a balance, and involves understanding the author’s purpose and their desire to receive feedback. He suggests that if someone doesn’t explicitly ask for feedback, ask them privately if they are open to it and how they want to receive it. Remember: it is never your duty to provide unsolicited feedback, especially in a setting where it’s anonymous or you cannot have a conversation with the author. Sharing your work publicly is nerve-wracking, and receiving unsolicited feedback can do more harm than good. Reaching out privately to see if someone is open to feedback also helps start a conversation (and maybe make a new friend!); giving unsolicited feedback publicly and/or anonymously becomes a one-sided conversation that can create a “Shark Tank” environment where people provide feedback more as a means to demonstrate their knowledge than to help others.
  2. Don’t take the reins from the author. Data viz is a combination of mathematics and art, and as such to important to understand the author’s purpose before suggesting changes. There are exceptions; sometimes you need to provide direct feedback to ensure a viz isn’t unethical or spreading misinformation, such as “use the median instead of the mean” or “be sure to start bar graphs at 0.” Otherwise, just because a topic isn’t shown in the way you would doesn’t mean it’s bad or needs changing. This falls back into that Shark Tank mentality, even if unintentionally. Instead, you can give feedback such as “I feel like X is working, can you turn that up?” or “Y isn’t working, could you turn that down?” It’s important to remember: Even if it doesn’t make sense to you, there was probably a reason the author made their choices. So instead of throwing out “This feels out of place to me” you can ask “what were you trying to achieve here?”
  3. Be open to learning yourself. I learned just as much giving feedback as receiving it. By having conversations I got a glimpse into the authors’ point of view and I can bring that perspective into my own work. Instead of saying “change this or that” you can ask “do you think this would work?” A bit of humility goes a long way. This will help both yourself and the person who you are giving feedback to. If your feedback comes off as aggressive the first reaction of the author could be to defend themselves or to change their viz into something that isn’t authentic to them as the artist. For example, if you just tell someone “this serves little purpose” instead of asking “what are you trying to achieve with this portion?” the author may just take out that portion of the viz. But if you framed that feedback as a conversation then you will learn the motivation behind the viz, the author will know it isn’t quite working, and the outcome could help both of you learn something new in design or storytelling.
  4. Remember, there is no right way to data viz. Pointing out ethical or accessibility concerns is one thing, but beyond that every person has their own thought process and goal. By telling someone what to do or change you can actually hinder their growth. By saying “I think a vertical bar chart would be best” or “use annotations instead of clicking” you are actually hurting a person’s growth rather than helping. It can be difficult to remember that your way isn’t always the right way, because there is no “right way” in data viz. This article from the Harvard Business Review on the Feedback Fallacy is such a great read on this, so instead of summarizing I just linked to it for you to read yourself. TL;DR: when you give feedback it’s more about yourself than the author, and it’s important to remember this so you don’t cause harm. The article has some great suggestions on language I have included below; this isn’t data viz specific and can be used in many areas.
Tips for providing helpful feedback from the Harvard Business Review article “The Feedback Fallacy”

I have always been hesitant to give feedback, because I know that I don’t know everything and I don’t want to create that kind of Shark Tank or Love Fest environments. These tips from the Feedback Loop have really helped me learn how to give feedback and learn in the process to create a better community for everyone. I hope you find these tips helpful, and my DMs are always open for further conversations!



Nicole Klassen

A data viz lover, passionate about always learning and helping others.