Plain-language questions
Ask for MQL to SQL conversion rate per month, customer or product in the SQL Explorer with AI. The AI writes the SQL, you see the query and run it yourself; the AI only receives metadata.
KPI · Marketing
MQL to SQL conversion rate is the percentage of marketing qualified leads that sales accepts as sales qualified leads. You follow a group of MQLs from the same period and count how many become SQLs. It shows how closely marketing and sales agree on what a good lead is.
Number of MQLs that become SQLs ÷ number of MQLs from the same period × 100%
In the third quarter, 190 of Acme Groothandel's leads reached MQL status. Sales accepted 76 of them as SQLs. The MQL to SQL conversion rate is 76 ÷ 190 × 100% = 40%.
Fictitious figures for Acme Groothandel, a sample wholesaler.
A higher rate means the leads marketing passes on are more often useful to sales. A low rate points to MQL criteria that are too loose, slow follow-up, or a disagreement between marketing and sales. Compare by channel and campaign, and with previous quarters.
SQL & DAX
Two examples on a fictitious data warehouse for Acme Groothandel: a PostgreSQL query and a measure for a Power BI model. Adjust table and column names to your own model.
SELECT date_trunc('month', mql_at) AS mql_month,
COUNT(*) AS mqls,
COUNT(sql_at) AS sqls,
ROUND(100.0 * COUNT(sql_at) / NULLIF(COUNT(*), 0), 1) AS mql_to_sql_pct
FROM leads
WHERE mql_at IS NOT NULL
GROUP BY 1
ORDER BY 1;MQL to SQL Rate =
DIVIDE(
CALCULATE(COUNTROWS(Leads), NOT ISBLANK(Leads[MqlAt]), NOT ISBLANK(Leads[SqlAt])),
CALCULATE(COUNTROWS(Leads), NOT ISBLANK(Leads[MqlAt]))
)In ENABLE
Ask for MQL to SQL conversion rate per month, customer or product in the SQL Explorer with AI. The AI writes the SQL, you see the query and run it yourself; the AI only receives metadata.
Define the KPI as a measure in your Power BI model and show it in the portal, with "Last refreshed" next to it. Access profiles and optional row-level security decide who sees which figures.
Add the KPI as a tile to a custom dashboard, compared with last year. The Dashboard Builder is a pilot and can be switched on per client.
With the built-in Targets app you set a target for the KPI per month, so you see actuals and target side by side.
FAQ
Take all leads that became MQLs in a period and count how many are now SQLs. Divide that number by the number of MQLs and multiply by 100%. With 76 SQLs from 190 MQLs, the rate is 40%.
An MQL has been rated as promising by marketing based on characteristics and behaviour, while an SQL has been accepted by sales after its own review, often following a first conversation. An SQL is therefore one step further down the funnel. Agree together when a lead moves from one status to the next.
You improve conversion by tightening the MQL criteria together with sales and asking sales to record a reason for every rejected lead. Those reasons show which leads marketing should stop passing on. Faster follow-up by sales also helps, as interest fades quickly.
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