How do you measure the success of your data presentations?

Defining a clear goal and gaining stakeholder agreement sets you up for success. The goal will guide your decisions and clearly describes what you will and will not do. This will help prevent scope creep. Whether answering a question or discovering insights, goals must be specific, measurable, and aligned with organizational needs (this helps ensure funding and relevance). Without well-articulated goals, efforts and scope become aimless, consuming time and resources without clearly delivering value. The goal is your benchmark for success, so you should begin by defining what success looks like for you and your stakeholders.

Put yourself in the shoes of your stakeholders. Think in terms of what they want to see and what they are looking for. Thinking through this beforehand will allow you to frame your presentation or project through the right context.

Data presentation can be measure by the feedback from the Audience. To get it success we need to prepare our presentation by considering the below mentioned. 1. Type of the audience and knowledge of the audience about the topic. 2. Is our Presentation required questioner, if it so? The exact relevant questions to be asked. 3. Does our presentation required any illustrations? What is the response of the audience about your illustrations? 4. Knowledge of the topic to the presenting person...to address the doubts of the audience on the presenting topic. 5. The voice clarity and weather atmosphere of the location.

If the audience gains actionable information that is applicable to their decision-making, the presentation is considered successful. Engagement and Interaction: Successful data presentations encourage audience engagement and interaction. If the audience actively participates in discussions, asks questions, and seeks further information, it indicates the presentation's success in capturing their interest. Example: During a financial conference focused on Africa's technology sector, I present data showing the rapid growth of mobile money adoption across various African countries. I highlight the economic impact of digital financial services on small businesses and financial inclusion.

An example of engagement metric is how long developers spent on a query, including query execution time. This metric can help identify any inefficiencies in query executions.

When it comes to data presentations, I mostly choose engagement as a metric. I tend to focus on the context of the questions asked as it'll show how much the audience is understanding.

With Action as your metric, getting your audiences to want to delve deeper on the data and study other possible angles after you’ve “scratched the surface” with your data presentation is a good indicator that you were successful. Another good indicator is when your data presentation is now being used as a reference for facts/hard data that would support the action plans that are related to what you presented.

The thing about data is that how easy or difficult it is to get information from depends on how it's structured. If your data is coming from a database it's probably going to be well structured. If you're collecting it yourself and are finding it frustrating to then get insights from it's probably because your data is in the wrong shape. It may not sound like an obvious step but talking to a data professional could save you a lot of headaches!

Here's where knowledge of how well you understand your audience is key - personalizing the story, or at least its delivery, to have the best comprehension is what I generally go for. Also, target the top 2/3 decision makers in the room, cause you can't win them all every time.

In my experience a great way to improve your data presentation skills is to log the questions asked to prepare for future presentations. In your next presentation you can get ahead of potential questions by having those answers in there or just having them ready if asked.

Being cognizant of client needs and preferences can be a very important thing to consider. If your presentation is interactive and able to visualize the granular details then more power to you. Additionally, feel free to experiment with colors, assuming your stakeholders don’t have a pre-set template. Color variations can make your presentation be perceived as vivid whilst showcasing your creative side as well. For the more technical readers, I’d suggest referring to: J.Bertin’s Semiology of Graphics or C.Ware’s Information Visualization Perception for Design, and see my suggestion in action.

The previous builds are on point. That being the case, here are some other general data presentation thoughts so you can give good presentations. Not the post mortem data analysis. Don't overload slides. Target the presentation at or just a bit below the expected comprehension level to ensure everyone stays engaged and not lost in translation. Regarding color palettes consider the color blind. Unless of course you have a mandatory corporate color pallette. If the presentation is online avoid transitions, animations, and memory hog files in case bandwidth or PC processing power is limited. This is for the presenter primarily, but also for the viewers wherever they are. You'll have less risk of a lagging or choppy presentation.

Data presentation success hinges on clarity, engagement, accuracy, feedback, and impact. Complex data must be clear and understandable. An engaged audience, asking questions and showing interest, reflects effectiveness. Accuracy ensures credibility. Positive feedback indicates relevance and delivery, while constructive feedback identifies improvement areas. Visual aids like graphs should enhance explanations. Ultimately, success is measured by informed decisions and improved understanding. Immediate surveys, ongoing feedback, interaction levels, retention, and real-world outcomes provide ways to measure success.