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The Best Audience Analysis Tools for Data Storytelling

The number one rule of crafting effective communication is to know your audience. Communicating with data is no different. Effective data storytelling begins with giving thoughtful consideration to who will be the viewer of your output. Before you create a single graph that you intend to share, first put some thought into knowing who the audience is for those data visualizations you are creating. Getting your signal heard through the noise dramatically improves when you tailor the message to the needs of your audience.

A woman is giving a presentation to a smiling audience


Data communication planning is the pre-production time of crafting your data message. It involves being clear on your intent, knowing your audience, and organizing your content. Understanding the context for the message is essential in creating effective data communication.

Context shapes the meaning for the listener, or rather, viewer of your data story. Data storytelling begins with data communication planning that is audience centered. Audience-centeredness keeps the audience foremost in mind at every step of the data visualization preparation and presentation.

Every effective communication starts with clear intent and purpose and a knowledge of the intended audience. Data communication is no different.


Communication is an audience-centered process. Audience analysis is the process of gathering information about the people who are going to be receiving your message so that you can understand their needs, expectations, beliefs, values, attitudes, and likely opinions.

Learning all that you reasonably can about an audience is essential to effective communication. Audience analysis tools help you to take into account the various aspects of your audience.

The best audience analysis tools for data visualization are going to help you answer the following questions about your audience:

  • To whom am I sharing this data story?

  • What are they going to want to see and understand?

  • What is the most effective way of presenting my data story to accomplish that aim?


Taking time to tailor your message to your intended audience will help your message to find deeper relevance and connection with your audience. When your message can engage your listener, you are much more likely to be successful in moving them toward action.

Different audiences understand the same ideas in different ways. Each audience has their own frame of reference for the data story. Understanding what is important to an audience, and why, is a core part of creating a data narrative that delivers immediate insights to the viewer.

With data communication, there is the additional factor of your audience’s familiarity with the data as well as the context. Providing clarity in your data visualization helps an audience to understand what data points are relevant to them.


In business, such as healthcare, these audiences are referred to as stakeholders. Understanding your audience allows you to tailor the storytelling and visualizations in a way that improves the chances of the communication being received. The more you know about your stakeholders, the better you can serve their interests and needs.

A volunteer pushes a man in a wheelchair

In the healthcare experience space, a volunteer-led initiative to impact the patient experience might have any of the following stakeholder audiences to consider:

  • Administration

  • Department Leadership

  • Non-clinical Personnel

  • Clinical Personnel

  • Front Line Staff

  • Hospital Volunteers

  • Patients

  • Community Members


The Business Analysis Body of Knowledge (BABOK) defines a stakeholder as “a group or individual with a relationship to the change, the need, or the solution”. Stakeholder lists can become quite lengthy as consideration is given to both internal and external audiences.

Audience analysis tools can help you identify stakeholder characteristics, such as:

  • Level of authority within the project scope

  • Attitudes toward or interest in the iniative/project/topic

  • Attitudes toward the analysis

  • Level of decision-making authority.

Using a business analysis approach, the use of the following audience analysis tools can be conducted using any number of techniques such as stakeholder lists, maps, and personas.

Stakeholder maps themselves are data visualizations that depict the relationship of the stakeholders to the topic and to one another. There are many forms of stakeholder maps that can be used to visualize relationships, but two common ones to use to identify the needs of an audience as it relates to the data you are communicating include the Stakeholder Matrix and Onion Diagram. (I will explore these techniques in a future post).

No matter which technique you use to elicit the information, be consistent in how you implement it with each analysis tool.

A busy hospital lobby


There are three best audience analysis tools for the data storytelling that you are creating. Those three tools are Demographic Analysis, Psychographic Analysis, and Situational Analysis. These three tools will help you understand what is most important to your intended audience.


While variables such as age, gender, culture, and educational level are part of larger population demographics, in organizations there are additional job-related demographics. Job-related demographics include the characteristics of our roles within the organization. Rooted in job analysis, job-related demographic analysis includes data such as job title, reporting structure, department, site, facility, shift, decision-making authority, and employment status.

  • How does this role relate to the data?

  • Will this audience have the ability to act on this information?

  • What is the general data literacy and data use of this group?


Values, opinions, attitudes, and beliefs are types of psychographic information. Whereas demographic data is fairly clear-cut, psychographic information about an audience most often has to be assumed. What assumptions can you safely make about what your audience cares about or motivates them to act? To make sure your assumptions are on target, be sure to share them with colleagues who can give you feedback.

  • Pre-existing notions of the topic/data?

  • What is their level of interest? How much do they care?

  • What is the audience’s pre-existing notions of the speaker?


How you publish your data story will be partly dictated by this audience analysis tool. Delivering your story via email versus a live presentation each present situational factors to consider. Occasion, voluntariness of audience, and physical aspects of the message delivery are examples of situational factors.

  • How does my audience prefer to communicate?

  • Is your audience expecting a presentation? A one-page executive summary?

  • How much time will the audience have to take in my story?


The great secret to data visualization is knowing your data and your audience. Different data visualizations are available, but it's important to choose the right one for your intended audience.

Key Question: Do you have more than one audience? If you do, you may need to tell more than one data story.

A data visualization about Quiet at Night HCAHPS scores should probably look different for a team of night shift nurse supervisors than when that same information is shared with a group of per diem physical therapists working at an offsite physical rehabilitation center.


Imagine that you are the director of an experience line in a hospital with purview over the volunteer department. Working with a manager from nursing, you develop and pilot a pilot volunteer-based program called the "Comfort Corps" that rounds on patient rooms in the late afternoon offering relaxing hand-massage as well as amenities such as sleep masks and white noise machines.

A woman holds a female patient's hand

After five months of data reporting you are able to observe an improvement in the HCAHPS Quiet-at-Night scores on the pilot nursing floor. Patients’ perception of the area around their room being quiet at night is improved compared to no change on other nursing units. The results, while not conclusive, are promising. You want to expand the program.

You identify four key audiences with whom you would like to share your data. After a bit of analysis and clarifying your purpose in communicating the data to them, you decide to make four separate data stories.





return on investment; effective use of resources

support the program by providing additional resources to expand program

Peer Leaders

the operational ease of implementing the program

trust volunteers and invite them onto other units to expand the program

Hospital Volunteers

the impact that they are having on the organization

be inspired to pick up additional shifts to expand the program

Community Members

the care they and their loved ones receive

perceive that the hospital makes every effort to give them restful conditions

Data visualization is not a one-size-fits-all practice. Knowing your audience will help you prioritize and make the most of data-driven storytelling. While you will still inevitably have to communicate with mixed audiences, by spending time doing some audience analysis you put yourself in a much better position to have your data story hit the mark with your core audience.

How much do you know about the audience intended for your next data story? How do you plan to apply these audience analysis tools as you create data visualizations in the future?

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Roseanna Galindo, ECBA, CAVS
Roseanna Galindo is Principal at Periscope Business Process Analysis and a champion for data literacy, the human experience in healthcare, and volunteer leaders everywhere. Learn more about Roseanna and her blog, The Periscope Insighter, by reading the opening post, Venn The Time Is Right

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Payal Sanyal
Payal Sanyal
Jul 24, 2023

Wow amazing

Replying to

Thank you for your kind words!

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