How Real-Time Patient Journey Tracking Increased Trial Conversions by 39% for a Life Sciences Company
Clinical trial enrollment was stuck at 16%. We mapped the full patient journey and identified invisible drop-off points.
Clinical trial enrollment was stuck at 16%. We mapped the full patient journey and identified invisible drop-off points.
The patient journey from website visit to trial enrollment was a black box. Analytics could see page views but not behavior within the eligibility screener or drop-off reasons. And there was no connection between digital engagement and actual enrollment.
Map the complete patient journey from awareness through enrollment, identify where patients drop off and why, measure time-to-enrollment by traffic source, and reduce cost per enrolled patient.
Patients with specific medical conditions seeking clinical trial participation, typically diagnosed within the past 12 months.
We rebuilt the eligibility screener with detailed event tracking. Every question view, answer, validation error, and abandonment was captured. We immediately saw that 41% of patients dropped off at the "upload medical records" step.
We implemented Tealium EventStream to track patient behavior in real-time and trigger immediate follow-up for high-intent abandoners. If someone completed 80% of the screener but didn't submit, patient recruitment got an alert within 2 minutes.
We connected Veeva enrollment data back to Adobe Analytics. Now when a patient enrolled 6 weeks after their first website visit, that conversion was attributed to the original traffic source and content.
We analyzed every abandonment point and worked with the clinical team to simplify requirements. The "upload medical records" step became optional for initial screening, and completion rates jumped 34%.
The solution delivered measurable improvements and satisfied users, proving the value of the design and engineering choices.
“We had no idea patients were abandoning at the medical records upload step until MarTechRise instrumented the full journey. The real-time alerts alone recovered 27% of abandoners who would have been lost forever. Our enrollment targets went from impossible to achievable.”
Specific features and implementations that solved the problem.
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