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The Interview Loop1 / 2

2 min lesson

The data & measurement round

Work through this case. "Your routing SLA dashboard shows a healthy mean time-to-owner. What do you say before anyone relies on it?" Say what you would do and why.

Step 1 of 2

The data & measurement roundinferred for this role

Expect SQL reasoning over a funnel, defining program metrics and naming attribution caveats. The posting asks for measurement and feedback loops, so this round is inferred from the role rather than confirmed. Prepare it anyway, because feedback loops are core to the job.

Funnel by program: conversion at each stage, the kind of query this round probes
-- Stage conversion for one program cohort, with simple attribution to first touch
WITH leads AS (
  SELECT lead_id, program, first_touch_channel, created_at
  FROM gtm.leads
  WHERE program = 'startup-program'
),
stages AS (
  SELECT l.lead_id, l.first_touch_channel,
         MAX(CASE WHEN s.stage = 'mql' THEN 1 ELSE 0 END) AS reached_mql,
         MAX(CASE WHEN s.stage = 'sql' THEN 1 ELSE 0 END) AS reached_sql,
         MAX(CASE WHEN s.stage = 'won' THEN 1 ELSE 0 END) AS won
  FROM leads l
  LEFT JOIN gtm.stage_events s USING (lead_id)
  GROUP BY 1, 2
)
SELECT first_touch_channel,
       COUNT(*)                                   AS leads,
       ROUND(AVG(reached_sql)::numeric, 3)        AS lead_to_sql_rate,
       ROUND(AVG(won)::numeric, 3)                AS lead_to_won_rate
FROM stages
GROUP BY 1
ORDER BY leads DESC;
Metric
Lead → SQL rate
What it tells you
Whether scoring/routing sends quality forward
Caveat to state aloud
Thresholds drift; recompute on recent cohorts
Metric
Routing SLA hit %
What it tells you
Whether hot leads reach owners in time
Caveat to state aloud
Averages hide tail; report p90, not just mean
Metric
First-touch attribution
What it tells you
Rough channel credit
Caveat to state aloud
Single-touch over-credits the first interaction
Metric
Program-qualified pipeline
What it tells you
Dollar impact of the program
Caveat to state aloud
Lagging; pair with a leading proxy like SQL count

Define the metric, then name its caveat. The caveat is where this round sees your measurement judgment.

Interview move

Make the dashboard actionable for a non-technical stakeholder. Say “the SDR lead opens this and sees which segments are under-SLA and which scoring tier is converting, so the next decision is obvious.” A metric a stakeholder can act on beats a clever query they can't read.