Post on 07-Jul-2015
description
Turn Data into Useful Insight The Software Analytics Playbook (Part 1)
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
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
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
Management Guru and Author Peter Drucker famously observed
“If you can’t measure it, you can’t manage it”
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
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.
Build it and they will come…(not)
Go lean: Use Analytics for “validated learning”
Challenges for most Software Developers
Decisions are based on “gut feelings” => risky strategy
Trying to get user insights the old way
Getting “real” and useful data is time consuming and hard
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
Complex and fragmented dataInternal systems
Products
Websites (marketing)CRM
Sign-up pages
What is Software Analytics?
Sales cycle
Error reporting User ecosystem
Feature usage
What are the Analytics choices?
Simpler Web Appse.g. Google Analytics, Kissmetrics
Mobile Appse.g. Flurry, Keen
SaaS Softwaree.g. Nalpeiron, Redgate
Desktop/packagede.g. Nalpeiron, Trackerbird
Software Analytics: Types and providers
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
How does Software Analytics help?
More user insight
Better Software
Happier users
More revenue
• Lower Support• Increased
satisfaction
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
Avoiding feature bloat with Analytics1. 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”
How it works – Desktop Software
Retro-fit Collect Insight
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
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…
Get a Free Book…with a Trial
Learn more at: www.nalpeiron.com
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
Q & A
Any Questions?#nalpeiron
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