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