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This presentation was given to startup founders and software people to help them understand how to better measure the success (or failure) of their product by using objective data.
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How to Measure Your ProductData Driven Little Bets
Liron Hayun [ UX & Analytics Consultant ] | [email protected]
ANALYTICS UX
ANALYTICS
DATABASE
SURVEYS
EMAIL SERVICE
ANALYTICS
DATABASE
SURVEYS
EMAIL SERVICE
5 Steps to Epiphany
1) Identify business objectives
2) Translate to technical requirements
3) Implement
4) Measure & Learn
5) Maintain
Business ObjectivesStep 1
The 5 Common Business Objectives
★ Ecommerce - sell products/services
★ Lead Generation - collect user info & connect
★ Content - engagement & visits
★ Online Support - finding info at the right time
★ Branding - awareness, engagement & loyalty
Practical Guidelines
● Include macro and micro conversions
------------------------------------------------------------
● Distill customer-problem-solution hypothesis
● Find the riskiest assumptions
Technical RequirementsStep 2
How It Works
Users Sessions Interactions
Your Product Analytics Server
UserInteraction
Session
Session
● Dimensions - characteristics of your users, their
sessions and actions (e.g. country, traffic source).
● Metrics - the quantitative measurements of
users, sessions and actions.
Data Types
Key Metrics
● Pageviews / Screens● Events
---------------------------------------------------
● Users● Sessions● Time on Page● Bounce Rate
Practical Guidelines
● Use a consistent syntax
○ upper/lower case letters
○ name of event actions
○ use of “-”
● Collect campaign data
ImplementationStep 3
ConfigurationCode
Practical Guidelines
● Build an infrastructure
○ maintain data integrity
○ easily measure new features
○ keep consistent syntax
● Setup goals in your analytics tool (!)
Measure & LearnStep 4
AARRR!1) Acquisition - users come from various channels
2) Activation - users enjoy first visit
3) Retention - users come back
4) Referral - users like product and refer others
5) Revenue - users conduct monetization behavior
Analysis Techniques
● Segmentation - isolate and analyze data subsets to understand behavior (by location, source).
● Context - use benchmarks to understand if your performance is good or bad (internal / external).
● Exploration - browse your data to find your next questions (landing/exit pages, bounce rates).
Acquisition
Sources Quality
Activation
Retention
Retention
Referral
Revenue
Maintain & RefineStep 5
Recommended Tools
➔ Google Analytics - free, robust analytics tool
➔ Optimizely - easy A/B testing
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➔ Google Forms - free surveys, easily embedded
➔ Qualaroo - onsite “nudges”
Thank You
Liron Hayun [ UX & Analytics Consultant ] | [email protected]