2 min lesson
The data & measurement round
Pick two rows from the table in "The data & measurement round" and explain the choice each one supports.
Step 1 of 2
The data & measurement roundinferred for this role
Expect SQL reasoning over a funnel, defining program metrics and naming attribution caveats. Treat this as inferred from the role's measurement responsibilities rather than a confirmed Cursor stage - but prepare it, because feedback loops are core to the job.
-- 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
| Metric | What it tells you | Caveat to state aloud |
|---|---|---|
| Lead → SQL rate | Whether scoring/routing sends quality forward | Thresholds drift; recompute on recent cohorts |
| Routing SLA hit % | Whether hot leads reach owners in time | Averages hide tail; report p90, not just mean |
| First-touch attribution | Rough channel credit | Single-touch over-credits the first interaction |
| Program-qualified pipeline | Dollar impact of the program | Lagging; pair with a leading proxy like SQL count |
Define the metric, then name its caveat - measurement judgment, not just a passing query, is what this round grades.
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.