First, Ann K. Emery encourages you to think through the following points:

• Identify Specific Audiences: List all the audiences for your project and prioritize the top three.

• Internal vs. External Audiences: Determine whether each audience is internal or external to your organization, as this affects how you present data.

• Technical vs. Non-Technical Audiences: Recognize whether your audience is technical or non-technical and adjust your data presentation accordingly. 

Stakeholders range in their comfort levels with data. Comfort level with data refers to an individual's or group's proficiency, confidence, and familiarity with working with data. It can vary widely among stakeholders, depending on their background, experience, and role within an organization or project. Moreover, understanding stakeholders' comfort level with data is crucial for tailoring communication strategies, providing appropriate support, and ensuring that data-related information is presented in a way that is accessible and meaningful to them. Below is a stakeholder identification chart that can help you determine stakeholder’s comfort level with data.

Ann K. Emery also encourages us to clarify whether the audience is expecting a story (storytelling graphs would be ideal for this situation) or not (use traditional graphs). Additionally, stakeholders often come into these conversations with types of data that they want to see. Some want all quantitative data. Some prefer stories in the form of qualitative data. We need to have a conversation that clarifies their goals so we can provide data that answers those questions. Sometimes we have to persuade stakeholders to use different data because what they have outlined may not meet their actual data needs. Therefore, it's essential to clarify whether the audience expects a story or traditional graphs to meet their data visualization needs.

Finally, outline which formats are best for your audience, making sure to tailor the format to the different needs of your audience (Emery, 2021). For example, a message intended for those in leadership positions is likely to benefit from having a high-level summary that outlines the key points using bullets. 

Below are some questions that you can ask stakeholders to better understand what the stakeholder wants to know and visualize.

• What is the purpose of this data analysis?

• What data do you have?

• Where did the data come from?

• What are your hypotheses or assumptions?

• What are the expected outcomes you hope to get from this analysis?

• What tools or software are you familiar with?

• What level of detail do you need?

• What constraints (such as time, budget, or data availability) exist?

• Who will use the analysis results?

While identifying stakeholder’s specific information needs depends heavily on the question and message, having a clear sense of the audience’s specific needs, expectations, and capabilities is critical for each visualization. 

Understanding your audience is paramount for effective data visualization and communication. By identifying specific audiences, distinguishing between internal and external stakeholders, and recognizing whether the audience is technical or non-technical, you can tailor your data presentations to meet the unique needs of each group. Additionally, understanding stakeholders' comfort levels with data and clarifying their expectations for storytelling or traditional graphs are crucial steps in this process. This initial connection with your audience is just the first step. You will need to partner with your audience throughout the development of visualizations to ensure that the data is presented in a way that is accessible and meaningful to them. By following these strategies, you can create more impactful and accessible data visualizations, ultimately enhancing decision-making and stakeholder engagement.

Emery, Ann K. (2021, Jun 1). Why "Know Your Audience" is Terrible Dataviz Advice and What to Do Instead.

Shah, Kunal. (2020). Designing Dashboards for Multiple Target Audiences with SAS Visual Analytics. SAS Institute. SAS Global Forum 2020.