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Research & CRO Audits
Find Out What Is Holding Customers Back.
Before changing a journey, launching experiments or redesigning a funnel, it helps to understand where performance is being lost and why.
PrettyDamnGreat combines quantitative data, behavioural research, customer feedback and UX analysis to uncover friction, missed opportunities and areas with the greatest potential for improvement.
The result is not just a list of observations. Research is translated into evidence-based opportunities, hypotheses and clear priorities your team can actually act on.
Start With Evidence
Your Analytics Shows What Happened. Not What Almost Happened.
A conversion rate can tell you that people did not buy. It cannot tell you what they were trying to do, what made them hesitate or which unanswered question changed their mind.
That is why a useful CRO analysis rarely comes from a single dashboard. Quantitative data helps identify where something is happening. Behavioural and qualitative research helps us understand what might be causing it.
Looking at those signals together creates a much stronger basis for deciding what deserves attention, what should be tested and where a larger redesign may be justified.
The Difference
From Symptoms to Causes
Where do customers drop out?
Which devices, segments or journeys underperform?
What are users struggling to understand or complete?
What causes hesitation, friction or uncertainty?
Which opportunities are worth pursuing first?
Research Scope
We Look at the Journey From More Than One Angle.
A CRO audit combines quantitative data, behavioural evidence, customer feedback and expert analysis to build a clearer picture of what is happening and why.
The exact research mix depends on your business, traffic, technology and available data. We can work with your existing platforms or use tools such as Google Analytics, Microsoft Clarity and Zigpoll to collect the evidence we need.
01
Analytics & Funnel Analysis
Analyse traffic, conversion, revenue, journeys and funnel drop-off to understand where performance changes and where customers leave the journey.
02
Data Integrity Check
Compare analytics data with the webshop, CRM or back-end to check whether transactions, revenue and other critical metrics are being measured accurately before using them to make optimization decisions.
03
Device & Browser Analysis
Compare performance across devices, browsers and relevant segments to identify technical or experience-related differences that may be affecting conversion.
04
Heatmaps & Scrollmaps
Examine how visitors interact with key pages, where attention is concentrated, how far people scroll and which elements are overlooked.
05
Session & Behaviour Analysis
Use behavioural tools such as Microsoft Clarity or the client's existing platform to understand navigation, hesitation, repeated actions and potential friction.
06
Full Funnel Walkthrough
Review the complete journey rather than isolated pages, following the experience from entry and orientation through consideration, cart, checkout or lead conversion.
07
Heuristic Analysis
Review usability, clarity, hierarchy, persuasion, accessibility and conversion principles across important parts of the experience.
08
Best-Practice Review
Compare the experience with established UX and e-commerce principles while treating best practices as potential opportunities rather than guaranteed solutions.
09
Competitor Research
Analyse relevant competitors and adjacent businesses to understand category conventions, propositions and potentially useful approaches.
10
Entrance & Exit Polls
Ask visitors why they came, whether they found what they needed and what prevented them from continuing or converting.
11
Targeted Customer Surveys
Use focused surveys to investigate specific questions, motivations, objections and customer needs that behavioural data cannot explain on its own.
12
Quick Wins & Hypotheses
Translate research into immediate improvement opportunities and larger hypotheses that can be prioritized for further optimization or experimentation.
CRO Audit
Not Every Finding Needs an A/B Test.
Research should help distinguish obvious problems from ideas that still need validation.
Some findings point to clear usability, technical or content issues that can often be fixed directly. Others represent opportunities where we still need to validate whether the proposed solution actually improves performance.
PrettyDamnGreat separates those situations rather than turning every observation into an A/B test or, at the other extreme, presenting every recommendation as proven fact.
Research Output
Data and measurement issues
UX and customer journey friction
Quick fixes that can be implemented directly
Opportunities requiring additional research
Testable CRO hypotheses
Prioritized optimization backlog
Research Technology
Use the Tools You Already Have. Add What We Need.
A CRO research program does not require rebuilding your analytics stack.
Analytics
Google Analytics
GA4 is commonly used for traffic, conversion, funnel, segmentation, device and commercial performance analysis.
If your organization already works with another analytics platform, we can use the existing setup instead.
Behaviour
Microsoft Clarity
Heatmaps, scrollmaps and session recordings provide another layer of evidence around how customers actually interact with the experience.
Existing behavioural analytics platforms can also be used, including tools such as Contentsquare, Hotjar or FullStory.
Voice of Customer
Zigpoll
Entrance polls, exit polls and targeted surveys help uncover customer intent, questions, objections and reasons for abandoning a journey.
Again, if an equivalent customer research platform is already available, there is usually no reason to replace it.
The tool is not the research. The questions we ask and the signals
we connect are what make the data useful.
How It Works
A Structured Route From Questions to Priorities.
The exact research plan changes by project, but the logic stays consistent.
01
Define the Question
Clarify business objectives, customer journeys, existing
knowledge, KPIs and what the organization needs to understand
or improve.
02
Validate the Data
Compare analytics with available back-end, transaction or CRM data
and investigate meaningful discrepancies before drawing conclusions
from the numbers.
03
Gather Evidence
Analyse quantitative data, customer behaviour, UX, surveys,
polls and other relevant signals across the customer journey.
04
Connect the Signals
Look for patterns across data sources and distinguish stronger
evidence from assumptions that still need validation.
05
Identify Opportunities
Translate findings into optimization opportunities, hypotheses
and potential journey improvements.
06
Prioritise
Help determine what deserves attention first based on evidence,
expected impact, effort, risk and business relevance.
What You Get
Research That Your Team Can Actually Use.
The objective is not to create the largest possible research document. It is to make better decisions easier.
01
Findings
Clear evidence of friction, behavioural patterns, weaknesses and opportunities across the journey.
02
Priorities
A structured view of which opportunities deserve attention first instead of treating every observation equally.
03
Hypotheses
Actionable optimization hypotheses that connect the observed problem to a proposed improvement and expected outcome.
04
Next Steps
Recommendations for experimentation, UX improvements, implementation or additional research where more evidence is needed.
When Research & Audits Make Sense
Especially Useful When You Know Something Could Work Better, But Not Exactly What.
Conversion has stagnated and the reason is unclear.
Your team has many CRO ideas but little evidence for
prioritising them.
A redesign or major journey change is being considered.
Traffic is healthy, but too few visitors become customers.
Different data sources are telling different stories.
You want to build a structured experimentation or CRO
backlog.
Already Know What to Improve?
Move From Research to Optimisation & Testing.
Research is often the starting point, but it does not have to be a separate phase. When enough evidence already exists, we can move directly into optimization, concept development and experimentation.
Research & CRO Audit FAQ
Before We Start Digging.
Do I need a lot of data?
No. The research approach depends on what is available. Analytics can provide valuable signals, but behavioural research, customer feedback, UX analysis and other evidence can also be used when quantitative data is limited.
Is this only for e-commerce?
No. PrettyDamnGreat works extensively with e-commerce, but the same research principles can be applied to lead generation, service journeys, forms, funnels and other digital conversion experiences.
Do you only deliver recommendations?
No. Research can be delivered as a standalone assignment, but PrettyDamnGreat can also continue into prioritisation, optimization, UX concepts, experimentation and ongoing CRO support.
Can you work with our existing analytics and CRO team?
Yes. Research can be carried out independently or as part of an existing product, UX, analytics, marketing or experimentation team.
Start With the Right Problem
Before Optimizing the Solution, Make Sure You Understand the Problem.
If you want to know where customers are getting stuck, what deserves attention and where the strongest optimization opportunities may be, let’s investigate it.