Customer Experience Analytics That Shows Where the Journey Breaks
Customers rarely tell you where the experience fails. Behavioural data does. I map journeys and trials, find the steps where people give up, and combine that with what customers say, so improvements are aimed at the right place.
What Journey Data Shows
Examples from my customer journey and trial conversion case studies.
of 9,935 sessions on a subscription platform ended at login, the largest single exit point in the journey
of multi-step conversions passed through the Pricing page, making it one of the highest-leverage pages to improve
of B2B SaaS trials never got a single worker onto the platform, a gap that behaviour alone could not explain
How CX Analytics Works
From raw event logs to a ranked improvement plan.
Map the Journey
Sessions, events or trial activity are turned into paths so you can see how customers actually move, not how the flow chart says they should.
Locate Drop-Off and Friction
Funnel and path analysis show where sessions end, which steps are skipped and which routes convert best.
Compare Converted and Non-Converted Customers
Segments such as plan type or channel are compared to see what successful customers do differently, and where behaviour alone stops explaining the outcome.
Recommend and Prioritise
Each fix is tied to the data behind it and ranked by likely impact, with limitations stated so you know how far to trust the result.
What You Receive
Journey Map and Path Analysis
A clear picture of how customers move through your product, site or store experience.
Drop-Off Report
The steps where experience breaks, with the size of each loss.
Converted vs Not-Converted Comparison
What separates customers who succeed from those who do not.
Ranked Recommendations
A short, evidence-backed improvement list your team can schedule.
Reusable Analysis
Documented code and SQL models so the analysis can be refreshed.
Related Projects
Case studies showing CX and conversion analysis on real data.
Funnel Analytics · Path Analysis
Conversion Journey Analysis
9,935 sessions mapped to find where users drop off.
Product Analytics · Python · SQL
SaaS Trial Conversion
Only 21% of trials convert, and behaviour does not explain why.
Retention Analysis · Power BI
Retail Revenue Decline
An 85% fall in repeat customers behind a revenue collapse.
Common Questions
VoC analysis starts from what customers say: surveys, reviews and tickets. CX analytics starts from what they do: sessions, paths and purchases. The strongest insight comes from using both, because behaviour shows where the problem is and feedback shows why.
A log of sessions or events with a customer or session ID, a timestamp and the step or page. Even a simple four-column export can be enough, as in my 9,935-session case study.
Yes. The SaaS trial conversion case study covers trial-to-paid conversion across 966 organisations with funnel, survival and cohort analysis.
Yes. In the trial study, product behaviour turned out not to explain who pays, and the report says so plainly. Honest limits matter as much as findings.
Fix the Experience Where It Breaks
See Exactly Where Your Customers Drop Off
Tell me about your journey or funnel. First call is free, and I will outline what the analysis would reveal.
Book a Free Discovery CallRemote worldwide · adeyemi@adediranadeyemi.com