The document discusses how software companies can use anonymous usage data and in-app messaging to better engage with users. It provides examples of how contextual, timed messages within an application can encourage feature usage, accelerate adoption, and increase conversions. While email is an option, in-app messages have advantages like perfect timing, user attention, and no spam issues. Best practices include personalizing messages, testing different options, and using a closed-loop system where analytics feeds messaging improvements. The goal is to educate and assist users through relevant, non-intrusive engagement within the software interface.

1. Message Like a Ninja
Powerful In-App Engagement with Anonymous Data
ProductCamp Boston – May 12, 2018
Keith Fenech
VP, Software Analytics
Dan Barrett
Customer Success

2. #SoftwareUsageAnalytics
Agenda
•Who is Revulytics?
•When & Why to Engage with Users
•Context is King: Data-Driven In-App Messages
•Anonymity in a GDPR World
•Timing & Message Delivery Options
•Best Practices
•Q&A
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3. #SoftwareUsageAnalytics
About Revulytics
Compliance Analytics
• Identify and quantify
software use and misuse
• Create actionable
intelligence
• Turn intelligence into
direct revenue
Usage Analytics
• Track and analyze
product usage
• Increase customer acquisition
and retention
• Generate revenue with
better products
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• Recognized as 2017 Gartner Cool Vendor
• More than 100 customers including Fortune 500 companies
• Technology deployed to over 72M machines across the globe
• Our data has supported more than $2.1 billion in new license revenue since 2010

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When to Engage with Users
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Source: Gartner

5. #SoftwareUsageAnalytics
Why Engage with Users
• Offer pre-sales assistance during evaluation
• Increase or accelerate conversions
• Educate on how to use product/features and increase ROI
• Upsell features or cross-sell other products/services
• Expiry reminder and renewal assistance
• Maintenance: Inform of new versions/updates
• Support & Educate: Alert on issues directly concerning user
– Bug fixes, sunset features, platform support, feature updates
• Collect Feedback
– Survey, net promoter score, feature requests, suggestions
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6. #SoftwareUsageAnalytics
Stages of User Engagement
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Installation
Trial Phase
Education
Onboarding
Conversion
Retention
Up-Sell
Cross-Sell
Feedback
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7. #SoftwareUsageAnalytics
Context is King
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• Google ads added relevance to
online advertising
• Amazon recommendation engine
• What was wrong with Clippy?
• People expect in-context
engagement

8. #SoftwareUsageAnalytics
How Usage Intelligence Feeds In-App Messaging
• Usage Intelligence helps
– Monitor state of your application
– Build persona/machine profile
– Track actions and behavior
– Trends and predictions
• In-app messaging criteria based on
Usage Intelligence metrics
– Perfect Timing
– Contextually Relevant
• Create messages that resonate
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9. #SoftwareUsageAnalytics
Data-Driven In-App Messaging for Onboarding
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10. #SoftwareUsageAnalytics 10
Privacy?

11. #SoftwareUsageAnalytics
Anonymous Data and GDPR
• What is GDPR and what is considered anonymous vs personal?
– IP address, user identifiable data, etc.
– Obtaining consent (opt-in/opt-out)
• How useful are anonymous usage intelligence metrics anyway?
• Exceptions: When you might want to collect personal information
– License compliance
– Account based usage monitoring
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12. #SoftwareUsageAnalytics
Timing of In-App Messages
• Time Based
– # days since install, # hours of runtime
• Event Based
– # runtime sessions, stage of evaluation, on license change
• Usage/Behavior Based
– Monitor product/feature usage and trigger based on these criteria
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How do I avoid
breaking the flow?

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Types of Messages
• Aggressive pop-up window
• Discreet system tray/balloon notification
• Notification icon in the menu
• Passive news area embedded in your
application UI
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15. EXAMPLES
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16. #SoftwareUsageAnalytics
• No hardcoding – context-based delivery
• Survey delivered once user meets product usage/engagement criteria
Example: Collect Qualitative Feedback
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1 2 3 4 5

17. #SoftwareUsageAnalytics
Example: Accelerate Adoption
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• Staged messaging
• From discreet to more aggressive

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How do I educate
users about my
product?

19. #SoftwareUsageAnalytics
Example: Encourage Feature Usage/Discovery
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How does in-app
compare to Email?

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Comparison to Email
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• 100% visibility
• Perfect timing
• User’s attention
1.5x
Increase in
product upgrades
9.7x
Increase in
click rate
4.5x
Increase in webinar
attendance
• No spam or lost messages
• Contextual relevance
• Behavior-based campaign
Note: Email and in-app messages can be complementary solutions, not mutually exclusive
Data-Driven In-App Messaging Offers:

22. #SoftwareUsageAnalytics
Best Practices
• Personalized based on user segments/profiles
• Actionable language with a clear CTA
• Timing is everything
– Trigger based on user activity, not only time since download/install
• A/B test and measure response
– CTA wording, message length, frequency
– Observe user behavior, learn, iterate
• Closed loop system
– Usage analytics feeds in-app messaging
– Messaging campaigns provide additional
data
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23. #SoftwareUsageAnalytics
Summary
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•Reasons to engage with your software users
•Increasing effectiveness of in-application messaging
– Timing
– Context
– Variety of visual notifications
•Applicability of anonymous usage metrics
•Best Practices for in-app message campaigns

24. #SoftwareUsageAnalytics
Questions
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