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Data Analytics for Sales Teams Flashcards

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

Read the first 7 Data Analytics for Sales Teams flashcards as text
  1. A sales manager wants to identify which deals are most likely to close this quarter. Which predictive analytics technique is best suited for this?

    Answer: Opportunity scoring models

    Opportunity scoring models use historical deal data and behavioral signals to rank deals by close likelihood.

  2. What does 'data granularity' mean in the context of sales reporting?

    Answer: The level of detail at which data is captured and reported

    Data granularity refers to how detailed the data is—e.g., deal-level vs. rep-level vs. territory-level data.

  3. A sales enablement leader notices reps are underusing a newly deployed analytics dashboard. What is the most likely root cause?

    Answer: Reps lack training on interpreting the data

    Low adoption of analytics tools is most commonly driven by insufficient training on data interpretation rather than tool design alone.

  4. Which metric best measures how efficiently a sales team converts leads into customers?

    Answer: Lead-to-close conversion rate

    Lead-to-close conversion rate directly measures the proportion of leads that ultimately become paying customers.

  5. What is 'pipeline velocity' in sales analytics?

    Answer: A measure of how quickly revenue moves through the sales pipeline

    Pipeline velocity combines deal count, average deal size, win rate, and sales cycle length to show revenue generation speed.

  6. A company's win rate has dropped 15% over two quarters. Which analysis would best identify the cause?

    Answer: Competitive win/loss analysis

    Win/loss analysis examines the reasons deals are won or lost, revealing competitive, pricing, or process-related factors.

  7. In data-driven sales enablement, what is the primary purpose of a 'sales funnel analysis'?

    Answer: To identify where prospects drop off between pipeline stages

    Funnel analysis shows conversion rates between each stage, revealing bottlenecks where prospects disengage or stall.