1. Given a choice of 10 potential experiments, how do you determine which ones to do? 2. Say we tried experiment X and failed to generate the returns we’re looking for, how do you diagnose the issue? 3. Given what you know about Canva, what would do if our current growth channels plateaus? Why? 4. Look at and explore www.canva.com. What are 5 things you’d do to grow active users? Include your math. 5. Let's say the CEO asks you if searches are up on the weekends year over year? You check the data and they are. What else do you look at before you communicate your findings? 6. Let's say you see data that looks at email sends by user state for a specific email: Dormant (not in last 30 days) 5% Core (DAU) 45% Casual (WAU) 30% Marginal (MAU) 15% Resurrected (wasn't in last 30 days, then came back as WAU) 5% 7. Let's say you walk in one morning and see a report that says signups from a particular channel drops 20% day over day? What do you do to identify the cause? 8. A colleague suggests we should send more emails to drive growth. How do you determine if we should do it? 9. Let's say Canva is considering is considering an additional business model that allows new users to use unlimited amount of design elements for a single subscription price. How do you determine its potential impact? 10. Let's say Canva asks you to figure out which locale the International team should establish a local presence in. How would you go about answering this question and why? 11: Let’s say a colleague suggests we should double our customer service because it’s important. How would you verify such claims? 12. What do you think is the most thought provoking article about data that you have read? 13. What is one thing you think is right that most people don’t agree with you about? (this is not a nice-to-have question)