How to Make Data-Driven Presentations Interesting

🟠 Most data scientists (and test managers) think explaining A/B test results is about throwing p-values and confidence intervals at stakeholders... I've sat through countless meetings where the room goes silent the moment a technical slide appears. Including mine. You know the moment when "statistical significance" and "confidence intervals" flash on screen, and you can practically hear crickets 🦗 It's not that stakeholders aren't smart. We are just speaking different languages. Impactful data people uses completely opposite approach. --- Start with the business question --- ❌ "Our test showed a statistically significant 2.3% lift..." ✅ "You asked if we should roll out the new recommendation model..." This creates anticipation and you may see the stakeholder lean forward. --- Size the real impact --- ❌ "p-value is 0.001 with 95% confidence..." ✅ "This change would bring in ~$2.4M annually, based on current traffic..." Numbers without context are just math. They can be in appendix or footnotes. Numbers tied to business outcomes are insights. These should be front and center. --- Every complex idea has a simple analogy --- ❌ "Our sample suffers from selection bias..." ✅ "It's like judging an e-commerce feature by only looking at users who completed a purchase..." --- Paint the full picture. Every business decision has tradeoffs --- ❌ "The test won", then end presentation ✅ Show the complete story - what we gained, what we lost, what we're still unsure about, what to watch post-launch, etc. --- This one is most important --- ✅ Start with the decision they need to make. Then only present the data that helps make **that** decision. Everything else is noise. The core principle at work? Think like a business leader who happens to know data science. Not a data scientist who happens to work in business. This shift in mindset changes everything. Are you leading experimentation at your company? Or wrestling with translating complex analyses into clear recommendations? I've been there. For 16 long years. In the trenches. Now I'm helping fellow data practitioners unlearn the jargon and master the art of influence through data. Because let's be honest - the hardest part of our job isn't running the analysis. It's getting others to actually use it.

Your execs don’t hate data...they hate how you present it 73.5% of managers and executives at data-leading companies say their decisions are always data-driven (Passive Secrets, 2025). But here’s the kicker: ↳ Many execs in YOUR company probably still roll their eyes when you bring up data. Not because they don’t care, but because they don’t understand what you’re saying. I know this because I’ve been on both sides. I’ve been the data analyst, the one diving deep into numbers, and I’ve also been the executive, the one making business decisions. And let me tell you: the gap is REAL. Data isn’t the problem. The way you deliver it is. If you want execs to beg for insights instead of avoiding them, you need to ditch the tech talk and start playing smarter. Here’s how: 1. Speak their language (ditch the jargon) ↳ If you start talking about “regression models” and “standard deviations,” they’re already tuning out. 💡 What to do instead? Translate it into business value. Better yet...tie it to THEIR interests. Try starting with: “Here’s how this impacts your bonus...” Watch their ears perk up. 2. Deliver quick wins (make data the hero) ↳ Executives don’t have time to sit through a 50-slide presentation on why your dashboard is revolutionary. 💡 What to do instead? Solve a tiny but painful problem FAST. Show them that data = speed, not headaches. 3. Keep it short (serve data like espresso shots ☕) ↳ You wouldn’t chug an entire pot of coffee in one sitting, right? ↳ Then why are you flooding your execs with 20-page reports? 💡 What to do instead? Give them one stat, one insight, and one action. 4. Tell a story (make data stick) ↳ Facts fade. ↳ Stories stick. 💡 What to do instead? Frame your data like a narrative. Use “you” 3x more than “data.” Make it personal. 5. Let them ‘steal’ the Idea (It’s psychology, not ego) ↳ Execs love their own ideas. ↳ Make them think they came up with yours. 💡 What to do instead? Ask: “What’s your gut feeling?” before showing the data. Now they’re invested. Now they want to see the numbers. 6. Address their hidden fears (Data = their safety net) ↳ Every exec has an unspoken worry...missing revenue goals, losing market share, failing to impress investors. 💡 What to do instead? Position data as their insurance policy. 7. Leave them hungry for more (The curiosity play) ↳ Want them to start chasing YOU for insights? ↳ Don’t dump everything at once. 💡 What to do instead? End every conversation with a question. ✔️ Data isn’t boring. ❌ Bad delivery is. What’s one data insight you WISH your execs would get excited about? Drop it in the comments. 👇 ♻️ Repost and tag someone who needs to hear this today. 📌 Found it helpful? Save for later. 👉🏻 Follow Glenda Carnate for more tips on Data/AI! #analytics #executives #entrepreneurship #innovation #data #ai 

Communicating complex data insights to stakeholders who may not have a technical background is crucial for the success of any data science project. Here are some personal tips that I've learned over the years while working in consulting: 1. Know Your Audience: Understand who your audience is and what they care about. Tailor your presentation to address their specific concerns and interests. Use language and examples that are relevant and easily understandable to them. 2. Simplify the Message: Distill your findings into clear, concise messages. Avoid jargon and technical terms that may confuse your audience. Focus on the key insights and their implications rather than the intricate details of your analysis. 3. Use Visuals Wisely: Leverage charts, graphs, and infographics to convey your data visually. Visuals can help illustrate trends and patterns more effectively than numbers alone. Ensure your visuals are simple, clean, and directly support your key points. 4. Tell a Story: Frame your data within a narrative that guides your audience through the insights. Start with the problem, present your analysis, and conclude with actionable recommendations. Storytelling helps make the data more relatable and memorable. 5. Highlight the Impact: Explain the real-world impact of your findings. How do they affect the business or the problem at hand? Stakeholders are more likely to engage with your presentation if they understand the tangible benefits of your insights. 6. Practice Active Listening: Encourage questions and feedback from your audience. Listen actively and be prepared to explain or reframe your points as needed. This shows respect for their perspective and helps ensure they fully grasp your message. Share your tips or experiences in presenting data science projects in the comments below! Let’s learn from each other. 🌟 #DataScience #PresentationSkills #EffectiveCommunication #TechToNonTech #StakeholderEngagement #DataVisualization