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Make Good Products Great with Data and Analytics

Make Good Products Great with Data and Analytics

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Make Good Products Great with Data and Analytics

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  1. Make Good Products Great with Data and Analytics Dave Mathias @DaveMathias WorkLearnPlay.com mathias612@gmail.com

  2. About me • Currently: • Manage a product management and analytics team in information security dept. of a large bank • President of Minnesota PDMA Chapter • MinneAnalytics conference organizer • Previously: • Product manager in re/insurance industries, marketing, lawyer, chemist, blah, blah, blah

  3. What is analytics? Analytics is the method of logical analysis. Merriam-Webster (Feb. 22, 2015). Retrieved from www.merriam-webster.com/dictionary/analytics. Analytics is the discovery and communication of meaningful patterns in data. Wikipedia (Feb. 22, 2015). Retrieved from en.wikipedia.org/wiki/Analytics.

  4. What not to do Source: Youtube https://www.youtube.com/watch?v=xAfA3D8VSnk

  5. Common questions • Where to start? • Where do I get the data? • What analytics tools to use? • Does a product manager need to be a data scientist? • Do you need a data scientist? Are there others?

  6. Where to start? • What do are you looking to do? • Increase product value • Improve marketing effectiveness • New product ideation • New product evaluation • Pricing analytics • Track and increase product usage Others?

  7. Where do I get data? • Data Options: • Collect datasets yourself • Obtain open source datasets • Buy proprietary datasets • Initial: Other’s data AND use proprietary data • Mature: Your proprietary data emphasis Anyone with hidden data gems?

  8. What analytics tools to use? • Analytics tools are just that tools • Initially: Buy tools and algorithms • Mature: Buy tools AND build algorithms What tools do you use?

  9. Real world problems discussion • What real problems do you have that data and analytics can help?

  10. Key takeaways • Identify problem you are solving • Identify how analytics can solve the problem • Identify data needed to solve problem • Determine if you can get the data • Pick the right tool from the analytics toolbox • Learn enough to be dangerous • Get data scientist • Don’t boil the ocean • Start now What else?

  11. Stay in contact • Email: mathias612@gmail.com • Twitter: @DaveMathias • LinkedIn: www.linkedin.com/in/davemathias1 • Blog: WorkLearnPlay.com • Podcast: Coming soon…