analytics @amazon | ex zomato/swiggy | SQL, python, statistical analysis
Diagnosing metrics is an analytics use case we solve at Swiggy pretty frequently. You observe a spike or a dip in a BAU KPI, and you wanna figure out why. Let’s take a hypothetical example - You’re analyzing a dip in user retention for a dining reservation platform. The data reveals that users are abandoning the booking flow midway. How do you turn this finding into a compelling story that drives action? 💡Don't just report the numbers. Craft a narrative that explains the "why," highlights the "so what," and drives action. 1️⃣ Focus on Insights, Not Just Numbers Instead of saying, "20% of users abandon the booking flow after selecting a restaurant," connect it to the impact: “20% of users drop off after selecting a restaurant, leading to ₹10L in lost potential bookings monthly. Addressing this could recover significant revenue.” 2️⃣ Use Visuals to Support Your Narrative - A funnel chart can show where users drop off in a multi-step booking flow. Annotate it with insights, like: “40% of drop-offs occur due to an unclear payment error message.” - Heatmaps can reveal high interaction zones on your platform or pages where users struggle. 3️⃣ Tailor Your Story to Your Audience - For Business Folks: Highlight business outcomes like revenue, customer satisfaction, or growth opportunities, like: "Fixing the payment flow could recover ₹1.5L in weekly bookings and improve customer trust." - For Product Teams: Focus on user behavior and actionable fixes, like reducing drop-offs or improving engagement, like: "A clearer error message during payment can reduce drop-offs by 15%, as users understand how to resolve failed transactions." 4️⃣ Highlight the Root Cause, Not Just the Symptom Raw metrics like conversion rates or drop-offs are symptoms. Dig deeper to understand the underlying reasons. Example: Data shows that 40% of users abandon the payment step. But why? After reviewing session recordings, you discover: - Many users encounter a vague “Payment Failed” error. - Some users are confused by the absence of a credit card option. By pinpointing the root cause, you can propose precise, impactful solutions. 5️⃣End with Actionable Recommendations Never leave your audience guessing. Wrap up your story with clear, actionable next steps. Storytelling with data isn’t just about presenting findings- it is about driving action. What’s your approach to crafting compelling data stories? Share your tips in the comments! _________________ 🔔 Follow Sanya Swain ♻ Repost to help others find it 💾 Save this post for future reference #businessanalysis #dataanalytics #dataanalyst #analytics #businessinsights #womenintech #product #sql #datascience