Last updated on Aug 22, 2024

You're receiving conflicting feedback on your data visualization. How do you decide what changes to make?

Creating effective data visualizations is essential for communicating complex information clearly and efficiently. However, when you receive conflicting feedback on your visualizations, it can be challenging to know which direction to take. It's crucial to approach this feedback with a critical eye, balancing the need for clarity and accuracy with the preferences and insights of your audience. By understanding the core principles of data visualization and the goals of your project, you can make informed decisions that enhance the effectiveness of your visualizations while satisfying diverse viewpoints.

1 Identify Goals

Before you dive into making changes, it's important to revisit the goals of your data visualization. What is the primary message you're trying to convey? Who is your target audience? By clearly defining the purpose of your visualization, you can use this as a benchmark to evaluate feedback. If a piece of advice aligns with your goals and helps to communicate your message more effectively, it's worth considering. Conversely, if a suggestion detracts from your main objectives or confuses the message, it may be best to set it aside.

Add your perspective

Load more contributions

2 Assess Validity

When confronted with conflicting opinions, assess the validity of each piece of feedback. Consider the expertise and perspective of each source. Is the feedback coming from someone with a deep understanding of data visualization or from a layperson who represents your broader audience? Both types of feedback are valuable, but they serve different purposes. Expert critiques might focus on technical accuracy and best practices, while user feedback will often give insights into readability and interpretability for a general audience.

Add your perspective

Eldar Aliyev, MPA

PG student @Imperial | Economist and BI Analyst | Sustainability | Technology | Energy | Transport | Data | Innovation | Environment
Report contribution
Evaluate the validity of the feedback by considering the source, expertise, and alignment with the project goals. Focus on input that enhances accuracy and relevance, ensuring your data visualization effectively communicates the intended message.

Like

3 Prioritize Clarity

Clarity should be the cornerstone of any data visualization. When deciding what changes to make, prioritize suggestions that enhance the user's ability to understand the data. This might include simplifying complex elements, choosing clearer fonts, or adjusting the color scheme for better contrast. Feedback that suggests improvements in these areas is typically worth implementing. Remember, a visualization that isn't clear won't effectively communicate your data, no matter how aesthetically pleasing it might be.

Add your perspective

Cesar Moreno B

Human | Carbonomics: Data Quality + Finance | Community Lead | Problem Manager | Climate Tech Fellow
Report contribution
In the context of the question I will prioritise clarity . Are the titles explicit enough? Are the graphics use the appropriate . For example stakeholder is able to quantify proportions with detail or graphics don’t specify numbers or percentages Graphics also should be designed thinking in audience. Is the audience savvy in the matter ? If savvy is not need to explain much acronyms for example .

Like

4 Consider Consistency

Consistency in design elements across your data visualization ensures a cohesive experience for your audience. When feedback suggests changes that would disrupt the visual harmony of your piece, weigh these suggestions carefully. Does the proposed change improve the overall comprehension or does it introduce a jarring element that distracts from the data? Maintaining a consistent visual language helps in reinforcing the narrative of your data and aids in viewer retention.

Add your perspective

Vinet Kakadea

Marymount'22 & NYU'23 | Entrepreneur
Report contribution
Consistency is pivotal when it comes to data visualization design due to its ability to provide a smoother experience for your target audience. Whenever receiving pessimistic feedback on your visualizations, put yourself in your audience's shoes and think accordingly. I'd recommend including whitespace in visualization designs since it grabs the target audience's attention pretty quickly.

Like
Sukha Singh
Report contribution
While consistency is key, it doesn’t mean you should be rigid. Sometimes, you can incorporate feedback in ways that preserve consistency. For example, if you’re asked to make a specific data point stand out more, rather than changing the entire color scheme, you might adjust the saturation or brightness of the existing color palette. This way, you highlight the important information without breaking the visual flow.

Like

5 Balance Feedback

Finding a balance between conflicting pieces of feedback is often about compromise. You may need to integrate elements from different suggestions to create a harmonious solution. For instance, if one person suggests using a bold color palette for impact and another prefers a more subdued approach for professionalism, you might opt for a middle ground that satisfies both needs. Balancing feedback is an art form in itself and requires a thoughtful approach to ensure that the final visualization is both impactful and appropriate.

Add your perspective

Elisa Andrea Bernal

Senior Consultant at Oracle
Report contribution
In practice, to ensure that the final product is effective and resonates with stakeholders or your audience, check whether it is possible to conduct small tests, seek more opinions to see how people react to those changes, and, while following the company's brand, ensure that the visualization remains true to its purpose- namely, transmitting the information clearly and effectively.

Like

6 Iterate Design

Finally, don't be afraid to iterate on your design. Data visualization is a process, not a one-time event. Implement changes that seem most aligned with your goals and test them with a subset of your audience if possible. Gather additional feedback on these revisions to see if they resolve the conflicts or if further adjustments are needed. Iteration allows you to refine your visualization incrementally, leading to a more polished and effective end product.

Add your perspective

You're receiving conflicting feedback on your data visualization. How do you decide what changes to make?

1

2

3

4

5

6

1 Identify Goals

2 Assess Validity

3 Prioritize Clarity

4 Consider Consistency

5 Balance Feedback

6 Iterate Design

Data Visualization

Rate this article

Thanks for your feedback

More articles on Data Visualization

More relevant reading

You're receiving conflicting feedback on your data visualization. How do you decide what changes to make?

1

2

3

4

5

6

1 Identify Goals

2 Assess Validity

3 Prioritize Clarity

4 Consider Consistency

5 Balance Feedback

6 Iterate Design

Data Visualization

Rate this article

Thanks for your feedback

Explore Other Skills