Conversion Rate Optimization: Find Friction and Test the Fix

Start with the point where people stop

Choose one step in the customer journey: a paid visit reaching a page, a form being completed or a qualified lead becoming a booking. Check that the events and records agree before treating a drop in conversion as a page problem.

Write a testable explanation

State what you think is preventing the next step and what you will change. For example: people may be abandoning a form because it asks for information they do not have yet. Removing one field tests that explanation more clearly than changing the headline, form and offer together.

Choose the measure before the change

Record a baseline, define the audience and decide how long the test needs to run. A higher form-completion rate can be useful, but check lead quality and downstream outcomes too. With low traffic or small differences, the result may remain inconclusive.

Report what the evidence establishes

Separate observed behavior from the explanation you inferred. If several changes went live together, do not assign the entire result to one edit. Report the observation window and any missing attribution.

A retained example

We connected paid search, patient-focused pages and clinic records for Colonial Heart. Over about four months, ad calls and forms matched 35 patients in clinic records; 17 were new to the practice. Matching an inquiry to a patient also does not establish that a particular page edit caused the visit.

Read the case studies and their measurement limits, or book a call to discuss a specific conversion problem.