Nalpeiron analytics introduction webinar

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Two part series explaining the benefits and pitfalls of Software Analytics.

Join Jon Gillespie-Brown, CEO of Nalpeiron and an Angel Investor, as he presents the latest insights on this topic.

You will learn more about:
- How to fully understand your product lifecycle from download/signup all the way to end of life
- How customers discover and use product features to drive improved adoption
- How features operate in complex, real-world configurations to reduce support headaches
- The biggest take-aways from two essential books on the topic: Lean Analytics & Consumption Economics
Great user understanding through analytics leads to better software, happier users, higher adoption, and more revenue.

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Nalpeiron analytics introduction webinar

  1. 1. Turn Data into Useful Insight The Software Analytics Playbook (Part 1)
  2. 2. About your Host • Jon Gillespie-Brown • Angel Investor – focus SaaS Software/Internet • Author of “So you want to be an Entrepreneur” (wiley) • Stanford and UC Berkeley lecturer • CEO, Nalpeiron – 20 years in software licensing/analytics – Analytics solutions for desktop/enterprise
  3. 3. Housekeeping • Ask questions as we go along within the system • Give us your feedback as we go along • 10 minutes Q&A at the end • Watch this on demand after the end anytime • This webinar is 30 minutes long
  4. 4. Contents of this Webinar • Why use Software Analytics? • Today’s leaders in Software use Analytics • Build it and they will come…(not) • Challenges for most Software Developers • Trying to get user insights the old way • Nalpeiron (example data sources) • Complex and fragmented data • What is Software Analytics? • What are the Analytics choices? • Which organizations needs Software Analytics? • How does Software Analytics help? • Why use Analytics in your development cycle? • Avoiding feature bloat with Analytics • How it works – Desktop Software • Data collection and the Law • A final word…Just do it! • Get a Free Book • Q & A
  5. 5. Management Guru and Author Peter Drucker famously observed “If you can’t measure it, you can’t manage it”
  6. 6. Why use Software Analytics? Organizations that apply analytics to their business outperform their peers: *Source: “Outperforming in a data-rich, hyper-connected world,” IBM Center for Applied Insights study conducted in cooperation with the Economist Intelligence Unit and the IBM Institute of Business Value. 1.6X revenue growth 2X EBITDA growth 2.5X stock price appreciation
  7. 7. Today’s leaders in Software use Analytics Today’s leader doesn’t have all the answers. Instead, today’s leader knows what questions to ask.
  8. 8. Build it and they will come…(not) Go lean: Use Analytics for “validated learning”
  9. 9. Challenges for most Software Developers Decisions are based on “gut feelings” => risky strategy
  10. 10. Trying to get user insights the old way Getting “real” and useful data is time consuming and hard
  11. 11. Lots of data, in many systems, in many formats Internal systems Salesforce Google Analytics Nalpeiron as example Anecdotal sales data Surveys Internal Support Systems UX analytics
  12. 12. Complex and fragmented data Internal systems Products Websites (marketing) CRM Sign-up pages
  13. 13. What is Software Analytics? Sales cycle Error reporting User ecosystem Feature usage
  14. 14. What are the Analytics choices? Simpler Web Apps e.g. Google Analytics, Kissmetrics Mobile Apps e.g. Flurry, Keen SaaS Software e.g. Nalpeiron, Redgate Desktop/packaged e.g. Nalpeiron, Trackerbird Software Analytics: Types and providers
  15. 15. Which organizations needs Software Analytics? Internal teams developing Software for non- commercial use • Reducing waste, improving user satisfaction and software quality Teams at Open Source Developers & Embedded devices • Different business model, software quality and legal requirements Outsourced Software development teams • Accountability, optimum development processes, better quality Teams at Independent Software Vendors (ISVs) • Commercial success, engineering focus and risk reduction
  16. 16. How does Software Analytics help? More user insight Better Software Happier users More revenue • Lower Support • Increased satisfaction
  17. 17. Why use Analytics in your development cycle? • Fully understand your product lifecycle • Learn how customers discover and use product features • Understand how features operate in complex, real-world configurations • Learn about error conditions to improve customer satisfaction and software quality • Understand how well marketing promotions are working to focus resources • And so much more… Copyright: Ben Yoskovitz
  18. 18. Avoiding feature bloat with Analytics 1. Why Will It Make Things Better? 2. Can You Measure the Effect of the Feature? 3. How Long Will the Feature Take to Build? 4. Will the Feature Overcomplicate Things? 5. How Much Risk Is There in This New Feature? 6. How Innovative Is the New Feature? 7. What Do Users Say They Want? “Save millions in development costs as you stop the feature overshoot”
  19. 19. How it works – Desktop Software Retro-fit Collect Insight
  20. 20. Data collection and the Law • Be aware if you collect any data you will be subject to the law • Be sensitive and transparent • Managing the data you collect from “people” is complex Copyright: MicrosoftAsk Nalpeiron for their extensive whitepaper on the topic
  21. 21. A final word…Just do it! • Most developers operate in the “dark” – It’s fast and easy to avoid these risks • It requires planning and forethought to get value • It’s all about asking “questions” and testing, not data • Modern organizations use Analytics to avoid “waste” • Todays leaders need a “data-informed” mindset to succeed • Choosing the right partner/fit will save a lot of time The first step is to give it a try, its low risk and high reward…
  22. 22. Get a Free Book…with a Trial Learn more at: www.nalpeiron.com
  23. 23. Sneak peak of the next Webinar: Advanced Analytics • More details on metrics and dashboards • Working through the challenges of using Analytics • Using KPIs and the lean Analytics cycle • Analytics for Product Manager and the Engineering team • More about data collection and the law • More specific use cases for desktop/enterprise Software
  24. 24. Q & A Any Questions? #nalpeiron
  25. 25. Acknowledgements • Lean Analytics: Use Data to Build a Better Startup Faster by Croll, Alistair; Yoskovitz, Benjamin • Consumption Economics: The New Rules of Tech by J. B. Wood, Todd Hewlin, Thomas Lah • Web Analytics 2.0 by Avinash Kaushik • Segment.io analytics academy • Seth Godin • IBM/Economist

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