Rep Activity Consistency

Description

Purpose of Analysis

Effective coaching requires more than outcome-based metrics such as revenue or closed deals. To understand how and why reps perform differently, managers need visibility into day-to-day behaviors such as outreach volume, consistency, and engagement patterns.

The TrueAI platform captures rep activity signals that allow coaching teams to distinguish between:

• inconsistent execution,
• skill-related gaps,
• and structural or pipeline-driven constraints.

This analysis answers:
Which reps show inconsistent activity patterns over time, and where coaching intervention may be required?

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Query

Query Intent

This query analyzes rep activity over time to identify patterns of inconsistency. By aggregating activity counts by rep and time period, it highlights variability that may indicate:

• uneven execution,
• burnout,
• lack of process adherence,
• or early warning signs of underperformance.

The query is intended to support coaching conversations by grounding them in observable behavior rather than outcomes alone.

SELECT
  u.rep_id,
  u.rep_name,
  DATE_TRUNC('week', a.activity_date) AS activity_week,

  COUNT(*) AS total_activities,
  COUNT(CASE WHEN a.activity_type = 'call' THEN 1 END) AS call_activities,
  COUNT(CASE WHEN a.activity_type = 'email' THEN 1 END) AS email_activities,

  STDDEV(COUNT(*)) OVER (
    PARTITION BY u.rep_id
  ) AS activity_variance

FROM rep_activities AS a
LEFT JOIN users AS u
  ON a.rep_id = u.rep_id

GROUP BY
  u.rep_id,
  u.rep_name,
  DATE_TRUNC('week', a.activity_date)

ORDER BY
  activity_variance DESC;

Sample Output

In this example, some reps demonstrate consistent weekly activity levels, while others show significant variability. High variance suggests inconsistent execution rather than a steady operating rhythm.

rep_name	activity_week	total_activities	call_activities	email_activities	activity_variance
Rep A	2024-10-07	42	18	24	15.3
Rep A	2024-10-14	12	4	8	15.3
Rep B	2024-10-07	31	15	16	2.1
Rep B	2024-10-14	29	14	15	2.1
Rep C	2024-10-07	8	3	5	18.7
Rep C	2024-10-14	41	20	21	18.7

How to Interpret the Results

• activity_variance measures how consistent a rep’s activity levels are across time.
• High variance indicates uneven execution and may warrant coaching attention.
• Consistently low activity may point to pipeline constraints or enablement issues rather than effort.
• Combine with outcome metrics to avoid over-coaching high-performing but efficient reps.

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Coaching Application

This analysis supports coaching by:

• identifying reps who may benefit from process reinforcement,
• separating behavior issues from skill or opportunity gaps,
• enabling data-backed coaching conversations focused on execution consistency.