Data visualization feedback … It’s complicated
Feedback provides users with an opportunity to learn quickly. What are the pros and cons of different types of feedback? How can we make it impactful while minimizing pain points?
I received and given constructive feedback from and to hundreds (if not thousands) of people on thousands of visualizations. I’ve participated in this process in various ways. This blog will cover the three most common (general) methods of feedback when considering public or social media communities. Visualizations covered here for feedback fall under data visualization hobbyists items and not professional visualizations like those shared by media, governments, or companies critiqued using a different lens. The “impact” measures are not based on the number of bullet points but my opinion on the net positive assistance provided.
Least Positive Impact
Sharing a visualization from another person, without asking permission, but providing a point by point viz takedown.
Positives
- Potential knowledge sharing
- Promotes open discussion
Negatives
- Unsolicited feedback
- Hurtful and can extend to harassment
- Tonally negative
- Potentially unethical
- Feedback is less likely to be constructive; particularly in deeper comment threads
Last week in our community, there were a couple of significant issues with people sharing another person’s visualization and providing unsolicited feedback on missteps they saw with the visualizations. Many points shared were valid but came off as unfavorable and soap-boxy. Sure, the author shared their visualization publicly, but the turnoffs of public viz-shaming and gratuitous feedback leave a sour taste to many in the dataviz community. The input may come from a genuine place but looks and feels like an attack rather than anything beneficial.
Mixed Impact
A person provides feedback publicly on a thread because the author requested public input on their visualization on social media.
Positives
- Knowledge sharing
- Author requested feedback
- Feedback likely constructive
Negatives
- Context may be lost when commenting on places where characters are limited
- The thread may devolve into something less helpful (e.g., poor feedback)
- The person requesting feedback may get hurt by comments and may have only intended to ask for feedback to enhance engagement and support of their work
Frequently users or a community get tagged, and a post mentions that ‘feedback is welcome.’ In this case, public feedback is solicited, so the author can see and act on suggestions. A person leaving feedback is often (although not always) someone who can provide helpful direction. However, like on Twitter, there are times where character limits can cut corners on context and niceties and get straight to the point. This approach can appear negative and rub the person asking for feedback the wrong way. In addition, given sensitivities, it’s hard to see anything that may result in someone providing feedback rather than general praise of work — even more, this feedback is public where the world can see it and provides a source of unintended embarrassment. There’s no real blame to apply here, just unintended consequences of getting what you asked for even though it’s not what you want.
Generally Positive Impact
A person provides private feedback through channels like direct messages, video conferencing, or in-person.
Positives
- Provides an opportunity for detailed and contextual feedback
- Reduces anxiety of public embarrassment
- Likely to get better iteration results
Negatives
- More time consuming
- The person providing the feedback may not get credit for assistance
- Can also lead to more requests to provide input in the future
- It may not help others learn if the person receiving feedback doesn’t share knowledge
My best experiences have been through private measures. It does take more time for the person providing feedback as it may result in more detail and multiple messages but yield better results for the person desiring feedback. Typically, even a sensitive person is less on edge. That person can feel the discourse is open and appreciates the time spent helping them, and is more likely to iterate and learn.
On the flip side, public feedback can provide a more macro learning experience as those that review it on the feed can apply it on their own (if relevant). Of course, it’s also possible the person providing the valuable feedback doesn’t get credited for helping (but that shouldn’t be the reason assistance isn’t offered). The least likely, is the person receiving feedback will get offended (but on rare occasions, that happens too).
Pro Tip: If you are seeking feedback privately. Please provide a brief summary of the request, a link to the visualization or image of it, and ask whether they have time to provide feedback. Whether they do or do not, thank them. Sometimes, people simply say ‘hi’ without context and it makes
In Summary
Suppose you are confused about how to act in a data visualization community. In that case, Tableau does provide a code of conduct, which thoughtfully lays out how we can best get along when sharing feedback and other related events where we need to put the community first.
Edit: Thanks to Valerie Mais for pointing out the storytelling with data community shares well-considered critique questions and considerations when structuring a critique. I’ve seen many positive outcomes from the work that collectively does with its members. For more context, please check out Valerie’s outstanding comment below.
In the immortal words of Bill and Ted…
