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Master the Essentials of
Conversion Optimization
Summary by Steve Clough
Mindset of an optimizer
 It’s about growth
 Better marketing
Accept
 You’re opinion doesn’t matter
 You don’t know what will work
 There are no magic templates for higher
conversions
Data-informed approach
 Set goals
 Set measurement
 Gather data
 Analyze data
 Turn data into insights
Conversion
Steps
 Technical Analysis
 Heuristic Analysis
 Web Analytics Analysis
 Mouse tracking Analysis
 Qualitative Research/Surveys
 User Testing
 Categorize/Prioritize
Technical Analysis
 Technical bugs on website are main conversion
killer
 Determine your conversion rate for each browser
and platform
 Make sure your website is optimized for all of
them
 Optimize site speed
Web Analytics
Google Analytics
 Averages lie – look at segments, distributions and
comparisons.
 Measure the important stuff (KPI)
 Identify leaks
Mouse Tracking
Tracking Clicks
 Heat maps
 Click maps
 Attention maps
 Scroll maps
 Form analytics
Website Surveys
Surveys
 Exit surveys when someone leaves your webpage
 On-page surveys
 Both can provide useful information
 Remember the end goal is to retrieve actionable
data
User Testing
Observe Users
 The test protocol for users to complete should
include: A specific task, broad task, and funnel
completion
 Avoid tasks that: Tell the user what to do, ask the
user if they would or would not buy, or what their
opinion is.
 The goal of user testing is to OBSERVE
Converting from data to
test hypotheses
 Allocate data into five categories:
1. Test
2. Instrument
3. Hypothesize
4. Just Do It
5. Investigate
A/B Testing
A/B Testing
 Make sure you are using a big enough sample
size
 Keep statistical significance in mind when testing.
95% confidence level should be benchmark
 Determine the duration of the test from traffic
data. Ex. High traffic website would need less
time to collect adequate sample size
Learn from test results
 Its ok if your test does not work as planned. This
gives you feedback to improve future tests.
 Before testing, make sure everyone is on the
same page – testing is about learning
 Inconclusive test results are common, learn to
analyze the segments.
Ending Points
 Conversion optimization is a process that is:
1. Systematic
2. Repeatable
 Keep an open mind and don’t get discouraged

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Master the essentials of conversion optimization

  • 1. Master the Essentials of Conversion Optimization Summary by Steve Clough
  • 2. Mindset of an optimizer  It’s about growth  Better marketing
  • 3. Accept  You’re opinion doesn’t matter  You don’t know what will work  There are no magic templates for higher conversions
  • 4. Data-informed approach  Set goals  Set measurement  Gather data  Analyze data  Turn data into insights
  • 6. Steps  Technical Analysis  Heuristic Analysis  Web Analytics Analysis  Mouse tracking Analysis  Qualitative Research/Surveys  User Testing  Categorize/Prioritize
  • 7. Technical Analysis  Technical bugs on website are main conversion killer  Determine your conversion rate for each browser and platform  Make sure your website is optimized for all of them  Optimize site speed
  • 9. Google Analytics  Averages lie – look at segments, distributions and comparisons.  Measure the important stuff (KPI)  Identify leaks
  • 11. Tracking Clicks  Heat maps  Click maps  Attention maps  Scroll maps  Form analytics
  • 13. Surveys  Exit surveys when someone leaves your webpage  On-page surveys  Both can provide useful information  Remember the end goal is to retrieve actionable data
  • 15. Observe Users  The test protocol for users to complete should include: A specific task, broad task, and funnel completion  Avoid tasks that: Tell the user what to do, ask the user if they would or would not buy, or what their opinion is.  The goal of user testing is to OBSERVE
  • 16. Converting from data to test hypotheses  Allocate data into five categories: 1. Test 2. Instrument 3. Hypothesize 4. Just Do It 5. Investigate
  • 18. A/B Testing  Make sure you are using a big enough sample size  Keep statistical significance in mind when testing. 95% confidence level should be benchmark  Determine the duration of the test from traffic data. Ex. High traffic website would need less time to collect adequate sample size
  • 19. Learn from test results  Its ok if your test does not work as planned. This gives you feedback to improve future tests.  Before testing, make sure everyone is on the same page – testing is about learning  Inconclusive test results are common, learn to analyze the segments.
  • 20. Ending Points  Conversion optimization is a process that is: 1. Systematic 2. Repeatable  Keep an open mind and don’t get discouraged