How can you use storytelling to build empathy with your audience when presenting data?

Companies such as Apple and Nike employ the power of storytelling to establish a profound connection with their audiences. Instead of merely presenting product details, their advertisements weave compelling narratives that are not only memorable but also emotionally resonant. Nonprofits often adopt a similar approach, using personal stories to shed light on their causes and elicit support through donations. Additionally, in the realm of education, stories play a crucial role in simplifying intricate concepts and enhancing engagement, as exemplified by the widespread popularity of TED-Ed videos that narrate educational content.

To build a compelling story invoking empathy; the presenter needs to take care of: 1. In person presentation - Voice Modulation coupled with pauses, examples from real life, content shouldn't be read from slides and explaining what is in there for the audience, why they should listen to you 2. Presentation - Needs to be with visuals, connected dots across slides, every slide should stand by itself (no more than 3 comparisons on a single graph), links for detailed deep dives Intrapersonal (believing and relating to what you are presenting) and interpersonal communication skills coupled with technical capabilities would make storyboard compelling and build empathy

Storytelling in data science is vital because it transforms complex findings into compelling narratives. It bridges the gap between data and decision-makers, making insights more accessible and actionable. A well-crafted story not only communicates results but also engages and persuades stakeholders, driving informed decision-making and maximizing the impact of data-driven insights. #DataStorytelling #DataScienceImpact

Brands like Apple and Nike leverage storytelling to connect with their audiences on a deeper level. Their advertisements often share a story, rather than just details about the product, making them memorable and emotionally engaging. Meanwhile, nonprofits frequently use personal stories to highlight their cause and inspire donations. Finally, in education, stories simplify complex concepts and make learning more engaging, as seen in the popularity of TED-Ed videos that narrate educational content.

In the realm of data science, numbers and statistics are the bedrock of our understanding. Yet, the true resonance of our work often lies beyond the raw data—it's in the stories that these numbers tell. Why does this matter? Because data, in isolation, lacks the power to motivate change. It is through storytelling that we give data a voice, one that can whisper or roar into the hearts and minds of our audience. When we build narratives around our data, we're not just presenting information; we're crafting a journey that can foster understanding, empathy, and connection.

One of the skills I acquired during my resent training; the COCOA presentation structure: 1. Context - core purpose beyond money (e.g.: message/idea/pain/impact) 2. Objective - business goals/specific sub-benefits etc. 3. Content - facts, data, visual, highlights 4. Options - alternate route to achieve the objective 5. Actions - decision/input/support required from the audience

Another version that simplifies the hero's journey and works well in the corporate world is SB7 (storybrand 7 by Donald Miller’s). It's a seven-step sequence to clarify your message. In this framework, “1. a character 2. with a problem 3. meets a guide 4. who gives him a plan 5. that calls him to action. When the character takes action, 6. he records notable successes 7. and avoids failures.” Cast your audience as the hero and be the guide they need.

When weaving a narrative with data, you need to evoke emotion and connect with your audience. You can start by introducing a relatable scenario or problem, then move on to humanize the data by giving it a face. It's also important to build tension by highlighting challenges or uncertainties, this will help you transition from a problem to the data itself and will develop a sense of hero journey. Try to use visuals effectively, guiding the audience through your logic and reasoning. Finish with a good resolution, emphasizing the impact of insights on the initial problem you mentioned. It should work for most cases!

Structuring a compelling data science story involves a clear narrative arc. Begin with a captivating introduction to grab attention, followed by a concise problem statement. Gradually unfold the data analysis process, emphasizing key findings and insights. Use visualizations effectively to enhance understanding. Conclude with a strong summary, linking back to the initial problem and proposing actionable recommendations. A well-structured story ensures that complex data is presented in a logical, digestible manner, fostering engagement and comprehension. #DataStoryStructure #EffectiveCommunication

Let's look at how Apple applies the SB7 principle in a product launch. First, they identify the customer (character) who needs a user-friendly device (problem). Then, Apple (guide) introduces the iPhone (plan), urging the customer to try it out (action). As a result, the customer successfully navigates technology (success) and is no longer frustrated by complicated gadgets (avoids failure). This approach maintains the focus on the customer's narrative and clearly conveys how Apple is the helper in their story.

Crafting your message is about distilling complexity into simplicity. Your audience may not share your technical background, so it's crucial to translate data into terms that are universally understood. Use analogies and metaphors to make complex concepts relatable. Be concise and direct, but also descriptive—paint a picture with your words that brings the data to life.

As an example, let's try presenting AI impact via dashboards: Outline AI’s goal, display its journey—initial hurdles and growth. Visuals should aid—rising trends, improving efficiency. Humanize numbers by associating with team's efforts or experiences. Simplify visuals, avoid clutter. This storytelling humanizes AI analytics, you're not just showcasing AI metrics, making it relatable, fostering empathy for the tech teams behind innovation, you're sharing the evolution of technology and the human effort behind it.

Data visualization is a storyteller's ally. It can illuminate trends, highlight outliers, and make comparisons intuitive. The key is to choose the right type of visualization for your story. Bar graphs, line charts, heat maps—each has its own narrative strength. Remember, the goal is clarity, not complexity. Your visualizations should enhance understanding, not obscure it.

Algumas dicas úteis para storytelling com dados s?o: - Conhe?a muito bem sua audiência e tente imaginar como qual seria a melhor forma a qual ela entenderia os dados - Seja simples e destaque sempre as principais informa??es, evite painéis mais pesados e prolixos - Seja inclusivo, evite diversos tons vermelhos e verdes, por exemplo, cerca de 5% da popula??o é Dalt?nica e pode ter dificuldades para entender destaques que quedas ou subidas de valores nessas cores

Data visualization turns raw numbers into a visual story, adding clarity and appeal to your data. It's your ally in storytelling, helping you uncover patterns and trends that strengthen your message. But, like any tool, it requires finesse – choose visuals wisely, keep it clear with labels and titles, stick to consistent colors and fonts, and don't drown your audience in information. When done right, data visualization transforms your data from a jumble of numbers into a compelling narrative that speaks for itself.

Data doesn't evoke emotion, but stories do. To build empathy, you must humanize your data. Share real-world implications, tell the stories of individuals affected by the numbers, and allow your own passion for the subject to shine through. Empathy is born when your audience can see themselves in the story you're telling.

A common challenge for data scientists making presentations is finding the right balance between data-driven insights and emotional connection. While facts and data are essential, don't underestimate the power of storytelling techniques to engage your audience. But shifting the focus too much towards emotional manipulation might compromise your credibility, use emotional appeals only to amplify your message, not manipulate it, and to create a more impactful and memorable presentation.

The delivery of your story is as important as its content. Practice is non-negotiable. Rehearse your narrative, refine your pacing, and anticipate questions. Know your data so well that you can focus on engagement rather than recall. During delivery, be present and responsive. Use body language and tone to convey enthusiasm and sincerity. Remember, you're not just sharing data; you're inviting your audience on a journey.

Data storytelling awakens empathy through relatable context. ?????? Who is impacted by these insights? Why should the audience care? Perhaps there’s an individual whose journey illustrates the problem’s human dimensions. ??Or conceptualize systems, events, and numbers themselves as characters—an oppressive process preventing access to services; budget shortfalls limiting classes. Build tension with challenges then crescendo into your findings and recommendations as hope glimmers! ?? Share just enough personalized backstory and descriptive drama that dry analysis transforms into a compelling narrative. ?? Essentially make your audience care through creatively humanizing the trajectories at play. ? Let’s start storyboarding! ??

Each audience is unique and so preparing a story entails knowing to whom the data is to be presented and adjusting accordingly. For instance if you are presenting to top management, you will need to be precise, concise and demonstrate the impact of the data (is it good?, bad?, how will they gain or lose? etc.) you are presenting. If you are to convey to a larger public, then an individual should be able to identify themselves to it. A glearing example is Dr. Shawn Murphy in "The Good Doctor". He really portrays how someone suffering from Autism can behave and this made most of the Autism community identify themselves to it.