โ† All CCRM Flashcard Decks

Data Analytics Flashcards

7 cards from real CCRM 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 Data Analytics flashcards as text
  1. A CRM team runs an A/B test on two email subject lines and finds a p-value of 0.03. At a significance level of 0.05, what should they conclude?

    Answer: The difference in open rates is statistically significant and unlikely due to chance

    A p-value of 0.03 is below the 0.05 threshold, meaning the observed difference is statistically significant at the chosen confidence level.

  2. Which RFM dimension specifically measures how recently a client last interacted with the company?

    Answer: Recency

    Recency measures the time elapsed since the client's most recent purchase or interaction, with lower values indicating more recent activity.

  3. A client analytics team discovers a strong correlation between client age and product preference. Before acting on this, what should they verify?

    Answer: That the correlation is not driven by a confounding variable such as income level

    Correlation does not imply causation, and an observed relationship may be explained by a third confounding variable.

  4. In the context of CRM analytics, 'sentiment analysis' is used to:

    Answer: Classify client feedback text as positive, negative, or neutral using NLP techniques

    Sentiment analysis uses natural language processing to detect and classify the emotional tone of client-generated text such as reviews and emails.

  5. A CCRM professional needs to track client health scores continuously. Which data infrastructure approach is most appropriate?

    Answer: A real-time data pipeline feeding a live dashboard with automated alerts

    Real-time pipelines and live dashboards enable proactive intervention by surfacing changes in client health as they occur.

  6. Which scenario represents an ethical concern in client data analytics?

    Answer: Using personal client data to train models without obtaining explicit consent

    Using personal data without explicit consent violates privacy regulations such as GDPR and CCPA and constitutes an ethical breach.

  7. A relationship manager wants to forecast client revenue for the next 12 months using historical monthly revenue data. Which method is most appropriate?

    Answer: Time-series forecasting using ARIMA or exponential smoothing

    Time-series methods like ARIMA or exponential smoothing are designed to model sequential temporal data and produce future-period forecasts.