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Advanced Reporting & Analytics Flashcards

7 cards from real CMO practice questions. Tap to flip, then mark Knew It or Still Learning โ€” missed cards come back until you master them.

Read the first 7 Advanced Reporting & Analytics flashcards as text
  1. In Mobilyze reporting, what does a 'cohort analysis' primarily track?

    Answer: User behavior grouped by a shared start date or event

    Cohort analysis groups users who share a common characteristic or start date to track their behavior over time.

  2. Which metric best measures the stickiness of a mobile application in an analytics dashboard?

    Answer: DAU/MAU ratio

    The DAU/MAU ratio indicates how often monthly active users return daily, measuring app stickiness.

  3. A CMO operator notices a sudden spike in session abandonment on a report. What is the FIRST step in diagnosing this anomaly?

    Answer: Cross-reference the spike timestamp with deployment or config change logs

    Correlating the anomaly timestamp with recent changes helps identify the root cause before making any configuration changes.

  4. What is the purpose of a 'funnel report' in Mobilyze Analytics?

    Answer: To display sequential step-by-step conversion rates toward a goal

    A funnel report shows how users progress (and drop off) through a defined sequence of steps toward a conversion goal.

  5. When configuring a scheduled report in Mobilyze, which delivery format is most appropriate for downstream automated data processing?

    Answer: CSV

    CSV is machine-readable and easily parsed by downstream scripts or data pipelines without additional rendering steps.

  6. An attribution report shows 80% of conversions attributed to 'organic'. What does this most likely indicate?

    Answer: Most users arrived without clicking a tracked paid link

    High organic attribution means the majority of converting users were not tagged with a paid campaign source at the time of arrival.

  7. In advanced Mobilyze analytics, what does 'data sampling' mean and when is it applied?

    Answer: Using a statistical subset of data to approximate results when query volume is very high

    Sampling computes results on a representative subset of data to reduce processing load when full dataset queries would be too costly or slow.