Sales Qualified Lead (SQL) Definition for B2B Teams

Why SQL Definitions Break Down

Most B2B companies define an SQL as 'a lead that's ready to talk to sales.' This is meaningless. Without specific, measurable criteria, marketing passes leads too early (inflating MQL counts) and sales rejects them (complaining about quality). The result: mutual blame, wasted pipeline, and a 67% disagreement rate on what constitutes a qualified lead.

The fix starts with a shared definition built from closed-won data, not opinions. Analyze your last 50 closed deals and identify the common attributes at the moment sales accepted the lead. Was there a confirmed budget range? A specific use case? A timeline for decision? These empirical patterns become your SQL criteria — grounded in reality, not wishful thinking.

Building Your SQL Criteria Framework

An effective SQL definition has two layers: fit criteria (who they are) and intent criteria (what they've done). Fit criteria cover firmographics: company size, industry, geography, and job title of the contact. Intent criteria cover behavior: content downloaded, pages visited, demo requested, or engagement with outbound sequences. Both layers must be satisfied — a perfect-fit company with no intent is not an SQL.

Score each criterion on a 1–5 scale and set a threshold. Example: Company size (1–5), Industry match (1–5), Budget indication (1–5), Timeline stated (1–5), Engagement score (1–5). An SQL requires a minimum total score of 18/25 with no single criterion below 3. This removes subjectivity and ensures consistent qualification across reps and regions.

The MQL-to-SQL Handoff Process

The handoff is where most leads die. Marketing marks a lead as MQL, but sales doesn't follow up for 72 hours because they don't trust the quality. Meanwhile, the lead's interest cools. The solution: automated routing with a 4-hour SLA for first touch. Track SLA compliance as a KPI for both teams. Companies that respond to SQLs within 5 minutes convert at 8× the rate of those responding after 24 hours.

Create a standard handoff document that travels with every SQL: contact details, company profile, engagement history (pages visited, content downloaded, emails opened), any notes from nurture conversations, and the specific trigger that qualified the lead. Sales should never need to ask marketing 'why was this lead sent to me?' — the answer should be self-evident from the handoff data.

Measuring and Iterating SQL Definitions

Review your SQL definition quarterly using three metrics: SQL-to-opportunity conversion rate (target: 40–60%), sales acceptance rate (target: >80%), and SQL-to-closed-won conversion rate (target: 15–25%). If acceptance is below 80%, your criteria are too loose. If conversion is below 15%, you're qualifying on the wrong signals.

Build a feedback loop: sales flags every rejected SQL with a specific reason (wrong persona, no budget, bad timing, wrong geography). Aggregate these reasons monthly to identify systematic gaps in your qualification model. The best B2B organizations treat SQL definition as a living process — updated quarterly based on win/loss data, market shifts, and product changes.

Frequently Asked Questions