SQL

An SQL (sales qualified lead) is a lead that your sales team has vetted and classified as ready to buy. Unlike an MQL, this isn't decided by a set of marketing rules but by a person in sales – usually after a first call.

How to recognize an SQL

Many teams use a simple framework like BANT:

• Budget: The lead can afford your offer.
• Authority: Your contact is involved in the decision.
• Need: There is a concrete problem you solve.
• Timing: The decision will be made in the foreseeable future.

Only when these points are largely met is the lead added to the sales pipeline as an SQL.

Example

An insurance broker gets 40 leads per month from LinkedIn, 18 of which are MQLs. After the first call, 9 SQLs remain, and 3 of them close.

MQL to SQL rate = SQLs ÷ MQLs = 9 ÷ 18 = 50%
SQL to close rate = deals won ÷ SQLs = 3 ÷ 9 = 33%

SQLs in performance marketing

For ad campaigns, the SQL is one of the most meaningful signals before the sale: it shows which campaigns bring in leads sales can actually work with. But this information never shows up in your ad accounts, because it is created in the CRM.

LeadMetrics brings it back: with the CRM integration for HubSpot (including deal stages over time) or Close, you see which campaign generated which deals. If you want to track SQLs as a separate stage, you can send them as a custom metric via webhook, Zapier, Make or a HubSpot workflow and analyze them per campaign.

Common mistakes

• SQLs without clear criteria: If every sales rep decides differently, you can't compare campaigns.
• No feedback to marketing: Without knowing which leads became SQLs, marketing optimizes blindly.
• Mixing up terms: In marketing, SQL means sales qualified lead, not the database language.