Instructions and covered skills
Complete the test in a quiet setting with notifications turned off. Read each scenario carefully before selecting an answer. Base your choice on the behavioral evidence described, not on assumptions about design preferences. Focus on the stated conversion goal and audience segment. Avoid rushing through questions that include metrics or page-context details. Choose the response that best supports a clear, measurable next action.
Key Areas
This assessment covers the interpretation of click maps, movement maps, scroll maps, rage clicks, dead clicks, and session recordings in a conversion optimization context. Candidates must recognize behavior that may indicate unclear affordances, hidden information, form friction, distracting navigation, ineffective calls to action, or mismatch between visitor intent and page content. The assessment also examines whether a candidate can distinguish an isolated observation from a repeated pattern supported by an appropriate sample.
Strong performance requires segment-aware analysis. Visitor behavior often differs by device type, traffic source, new versus returning status, geography, and conversion outcome. Candidates should know when an aggregate heatmap can obscure meaningful differences and when separate views are needed. They should also understand the limits of behavioral tools: a click or scroll pattern can identify where to investigate, but it does not by itself prove motivation or causation.
The assessment emphasizes practical decision-making. Candidates evaluate evidence, frame concise hypotheses, identify the relevant success metric, and recommend a focused experiment or validation step. They should prioritize issues using the likely effect on a defined conversion action, the frequency of the observed behavior, and the confidence provided by several supporting signals.
Recommended Preparation
Review how common behavior-analysis tools collect and display click, scroll, and recording data. Practice examining pages by device category and by outcomes such as converted, abandoned, or form-started sessions. Learn to identify interaction signals including repeated taps, rapid back-and-forth navigation, clicks on noninteractive elements, abandoned fields, and attempts to interact with images or text.
Practice writing hypotheses in a structured form: identify the observed behavior, name the likely source of friction, describe a proposed change, and state the expected effect on a conversion metric. Pair behavioral findings with complementary evidence such as form analytics, page speed data, surveys, funnel reports, or user research. This approach helps ensure recommendations are grounded in observed patterns and can be evaluated through measurable outcomes.