2. “IF YOU CAN’T DESCRIBE WHAT
YOU ARE DOING AS A PROCESS,
YOU DON’T KNOW WHAT YOU’RE
DOING.”
W. EDWARDS DEMING
3. CONVERSION LESSON #1: THE
MINDSET OF AN OPTIMIZER
What do we optimize for?
Do NOT optimize for conversions alone.
Reduce your product price to $.99 and your
conversions will inevitably go up.
4. THEN WHAT AM I OPTIMIZING
FOR??
GROWTH. IT’S ABOUT GROWTH.
How do we optimize our website so that our
business will grow?
5. IT’S ABOUT BETTER
MARKETING
There are two approaches to improving a website:
1. Go in and change what you think is a good idea to
change—hope your sales will go up.
1. Start by figuring out which pages cause the drop off.
Once you understand WHERE the problem is, you can
identify WHAT the problem is.
Which one would you choose?
6. DUH. THE SECOND ONE.
That’s right!
You should seek to understand your customer better:
their needs, concerns and what is going on inside their minds.
You can gather quantifiable information in order to understand
what people are doing on your site and the impact that each
action has on the revenue.
7. YEAH, THAT MAKES SENSE
You can do better marketing if you actually
understand what the market wants
and focus on pages that have the biggest
problems.
8. SO HOW DOES ONE BECOME A
GOOD OPTIMIZER?
Step 1. Accept these undeniable truths:
• Your opinion doesn’t matter.
• You don’t know what will work.
• There are no magic templates for higher conversion.
Stop thinking in tactics and start thinking in processes.
Step 2. Turn your unsupported, baseless opinions into data-
informed, educated hypotheses.
• Focus on KNOWING what’s happening and understanding WHY.
10. RESEARCH XL
Step 1: Technical Analysis
• Cross-browser testing
• Cross-device testing
• Speed analysis
Step 2: Heuristic Analysis
• Areas of interest
• Check key pages for
relevancy, friction issues
Step 3: Web Analytics
Analysis
• Health check
• Identify KPI’s and leaks
Step 4: Mouse Tracking
Analysis
• Heat, click, & scroll maps
• User session video replays
Step 5: Qualitative Research
• Customer, web traffic surveys
• Interviews
Step 6: User Testing
• Identify usability and clarity
issues
Step 7: Sum Up
• Categorize and prioritize each
issue
• Translate into a test
hypothesis
11. LET’S GET STARTED…
Step #1: Technical Analysis
Bugs are your main conversion killer.
1. Cross-test browser and device functionality.
Google Analytics Audience Technology Browser & OS Report
Plugging cross browser and cross device leaks are what equals growth!
2. Figure out overall website speed, and analyze speed per page.
Google Analytics Behavior Site Speed Page timings
• Pay attention to “Page Interactive Time.”
More than 10 seconds? Gotta do something!
12. STILL HOLDING ON TO THAT
USELESS OPINION?
Step #2: Heuristic Analysis
A.k.a. the closest you will get to validating an opinion—an experience
based assessment where the outcome is not guaranteed to be optimal,
but might be good enough.
In essence, you/optimizers review a website page by page in a VERY
structured way looking for:
• Relevancy
• Clarity
• Value
• Friction
• Distraction
But remember: whatever you write down is merely an area of interest.
13. CONVERSION LESSON #3
GOOGLE ANALYTICS FOR CRO
Step 3: Web Analytics Analysis
Gone are the days when a brilliant idea was enough in marketing.
Now you need to know the specific impact of every idea.
From Google Analytics we can learn:
• What people are doing.
• The impact and performance of every
feature, widget & page.
• Where the site is leaking money.
But we won’t know WHY. It’s up to YOU to pull
insights from the data.
14. GOOGLE ANALYTICS CONTINUED…
Tips and Tricks:
• Averages lie—look at distributions, segments, and comparisons.
• Always use absolute numbers next to ratios.
• Measure the important stuff a.k.a. your KPI’s & goals.
• If you have no goals set up, you’re a voluntary idiot.
• Set up goals for ALL key actions (purchase, lead generation, etc.).
• Use Google Tag Manager to set up event tracking.
• Find leaks by identifying specific pages and steps that are losing
money.
15. CONVERSION LESSON #4: MOUSE
TRACKING & HEAT-MAPS
Step 4: Mouse Tracking Analysis
You can record what people do with their mouse/ track-pad and
quantify that information.
BUT you need enough of a
sample size per page or
screen BEFORE you can trust
any results.
• Heat-Map is a graphical representation of data where the
individual values are contained in a matrix and represented
as colors. HOWEVER accuracy is always questionable.
16. BUT WAIT! THERE’S MORE
• Scroll Maps show how far down people scroll, which
helps you prioritize content.
• User Session Replays allow you to record video
sessions of people going through your site, which is
helpful for observing how people fill out forms, etc.
• Click-Maps show aggregated data though a visual
representation of where people click.
• Attention Maps show which areas of the page have
been viewed the most.
17. CONVERSION LESSON #5: USING
WEBSITE SURVEYS
Step 5: Qualitative Research
There are two ways to survey your web traffic:
1. Exit survey: hit them with a popup when
they’re about to leave.
2. On-page survey: ask them to fill out a
survey as they’re on a specific page.
ASK about the fears, doubts, and
hesitations customers are experiencing on a
specific page.
Every page on your site has one job, and your
survey question should be about that one
page, one job.
18. SURVEY TIPS…
START WITH determining the most wanted action for the page.
THEN come up with a question that asks about friction.
E.g. “What’s keeping you from buying this right now?”
Try to come up with multiple different wordings to the question.
• Ask questions in the form of Y/N to start out.
• 100-200 responses is ideal.
Look for trends in people’s responses.
19. CONVERSION LESSON #6: USER
TESTING
Step 6: User Testing
Observe actual people use and interact with your website
while commenting their thought process out loud.
START WITH creating test protocol—tasks that you want
your user to complete (4-5 tasks per test is average).
THEN have your user complete key actions (e.g. signing up
for something, or completing a purchase).
You generally want to include 3 types of tasks in the test
protocol:
• Specific task
• Broad task
• Funnel completion
20. USER TESTING GUIDELINES
DON’T ask your users questions; simply observe their actions.
Recruit 5-10 testers that are within your target audience if
possible.
21. CONVERSION LESSON #7:
FROM DATA TO TEST HYPOTHESES
Congrats!
You have completed the Research XL Framework! Once you go
through steps 1-6, you will identify issues:
Allocate every finding into one of these five buckets:
1. Test (traffic, leakage)
2. Instrument (beef up the analytics reporting)
3. Hypothesize (something isn’t working, but there is no clear solution)
4. Just Do It (issues with an easy fix)
5. Investigate (dig deeper on the issue, ask more questions)
22. SO YOU’VE GOT 99 PROBLEMS…
Prioritize!
• Start with high priority items and leave
low priority for last.
• Use a ranking system of 1-5
(5 being the most critical).
There are 2 criteria to keep in mind:
1. Ease of implementation.
2. Opportunity score (subjective opinion on
how big of a lift you might get).
Translate the issue into a hypothesis, and
conduct further investigation.
All hypotheses should be derived from your
conversion research.
23. CONVERSION LESSON #8: GETTING
A/B TESTING RIGHT
Make sure your
sample size is big
enough.
**Bad testing is
even worse than no
testing at all.
Ignore your test results until you have at least 350
conversions per variation.
A/B testing involves creating “treatments” and alternative
variations to test against the current page (control).
24. LOOK FOR 95% CONFIDENCE
We want to see if one of the variations is better than the
control, a.k.a. statistical significance.
Statistical significance is the probability that a test result is
accurate and not due to chance alone.
There is no substitution for experience. Start
running tests now.
25. CONVERSION LESSON #9:
LEARNING FROM THE TEST
RESULTS
Iterative testing is the name of the game:
10 tests to a sizeable win is not uncommon.
It’s about learning.
26. KEEP SWIMMING
But my test results are inconclusive…??!
• Your hypothesis may be wrong or your test wasn’t as bold
or brave enough in shifting away from the original design.
• Analyze the segments.
• Consider how the variations performed across the
different segments.
Learn from failure. Brainstorm a new test.