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Webinar: How to be More Effective Data-Driven PM by fmr Groupon Sr PM

Main Takeaways:
- Don’t stick to the book
- Understand team dynamics and be flexible
- Know your strength and elaborate

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Webinar: How to be More Effective Data-Driven PM by fmr Groupon Sr PM

  1. 1. www.productschool.com Webinar: How to be More Effective Data-Driven PM by fmr Groupon Sr PM
  2. 2. Join 60,000+ Product Managers on Free Resources Discover great job opportunities Job Portal prdct.school/PSJobPortalprdct.school/events-slack
  3. 3. CERTIFICATES Your Product Management Certificate Path Product Leadership Certificate™ Full Stack Product Management Certificate™ Product Management Certificate™ 20 HOURS40 HOURS40 HOURS
  4. 4. Corporate Training Level up your team’s Product Management skills
  5. 5. How to Be a Better Data Driven Product Manager By Emile Saad, Sr. Product Manager
  6. 6. About Me ● Sr PM at Groupon, KnowledgeView (startup in Beirut, Lebanon) ● Product management experience in mobile apps and mobile marketing ● Background in Computer Science, MBA
  7. 7. Agenda ● Automate and Simplify to Own Your Metrics ● Plan Ahead for Experimentation and Analysis ● Trust Your Instincts ● Key Takeaways
  8. 8. You run across the CEO in the hallway. She asks you: “How is your product doing?”
  9. 9. Possible Answers? “It’s doing great!” Another option: “Last week, we added a new feature. It’s currently driving X additional users to the product, an increase of Y% from last month”
  10. 10. Simplify and Automate your Metrics
  11. 11. Why Automate Your Metrics? ● Know the ins and outs of your product metrics ● Identify new opportunities and issues faster and address them ● Free up time to focus on important tasks ● Be comfortable answering questions on the spot
  12. 12. Invest Time Upfront to Automate your Metrics ● Identify main metrics sources and dashboards ○ If none, create them! ■ Dashboards: Tableau, Chartio, Looker, Google Data Studio ■ Logging and monitoring tools (Google Analytics, Splunk, Elastic…) ● Reserve 10-15 minutes every morning to review your main metrics ● Focus on most important metrics for your product. Dive deep when necessary Tip: When starting a new PM role or new product, use your initial learning days to identify metrics and compile/build your dashboard
  13. 13. Experimentation and Analysis: Plan Ahead for Success
  14. 14. Start With a Plan Start with a simple, 1 page plan to guide your analysis/experiment: ● Explain how this experimentation/analysis will be conducted ● Define what success will look like ● Clarify what to do in case of success/failure
  15. 15. Explain Your Approach ● A/B Test: ○ Treatment description ○ Number of users ○ Test duration ● Gradual Roll out: ○ Percent will start, percent increases, duration ● Pre/Post analysis: ○ What are the main metrics and how will they be interpreted? ● New product/MVP: interviews, landing page data, etc.
  16. 16. Define What Success Will Look Like S.M.A.R.T. Goal: Specific, Measurable, Attainable, Realistic, Time Bound This feature will improve buyer conversion rate VS. This new feature will increase buyer conversion rate by 5%, bringing in $100K additional revenue annually
  17. 17. Clarify What Happens in Case of Success or Failure ● A simple decision matrix helps clear the picture in advance and plan for all scenarios ● Failure is OK, as long as we know how to deal with it! Decision Matrix Metric 1 Success Metric 1 No Change Metric 1 Failure Metric 2 Success Roll out Roll out Rollback Metric 2 No Change Roll out Roll out Rollback Metric 2 Failure Re-Evaluate Rollback Rollback
  18. 18. Tips ● Keep your plan simple! (unless your company has specific policies) ● Beware of extremes: ○ Analysis paralysis ○ Oversimplification ● How you say it matters ○ Make sure you are using proper convention
  19. 19. Trust Your Instincts
  20. 20. Things Are Not Always What They Appear To Be ● The data will not always make sense ● Mistakes happen, even with the best analysts ● Confirmation bias can set us on the wrong path ● Accept that data will not always be available
  21. 21. What To Do When Things Look Too Good To Be True When you feel too good about your data ● Sometimes it’s good to do own due diligence ● Better to identify issues early, than later ● Challenge yourself to be a better PM Large variations. e.g. 20% increase, when expected 5% ● Dive deep: look at secondary metrics ● Look for outliers ● Review setup for mistakes ● Look for macro trends When estimates given to you seem unrealistic ● Review models and question assumptions ● Consider initial MVP instead of full product to quickly validate ● Wear the customer hat
  22. 22. Experience Will Get You There! Remember that it’s a marathon, not a sprint. Continuous learnings from daily metrics, launches, successes and failures will make you much better at suspecting when something doesn’t look right Identifying, launching and analyzing Familiarizing with metrics and customer trends Learning from customer trends and the data
  23. 23. Key Takeaways 1. Own your metrics and data by automating and simplifying 2. Plan ahead before experimenting 3. Trust your instincts and don’t be afraid to question the data
  24. 24. www.productschool.com Part-time Product Management Training Courses and Corporate Training