What is SQL (Sales Qualified Lead)?
A lead that has been vetted by the sales team and meets specific criteria indicating they're ready for direct sales engagement.
Quick Definition
SQL (Sales Qualified Lead): A lead that has been vetted by the sales team and meets specific criteria indicating they're ready for direct sales engagement.
Understanding SQL (Sales Qualified Lead)
A Sales Qualified Lead (SQL) is a prospective customer who has been researched and vetted by both marketing and sales teams and is deemed ready for direct sales engagement. SQLs have moved beyond initial interest—they have been qualified as having a genuine need, appropriate budget, decision-making authority, and a realistic timeline for purchase.
The SQL stage represents a critical handoff point in the revenue funnel. While Marketing Qualified Leads (MQLs) have shown engagement with marketing content, SQLs have been further validated through sales development activities. This might include discovery calls, needs assessments, or direct conversations that confirm the lead's readiness and fit.
The distinction between MQL and SQL is crucial for sales efficiency. By the time a lead reaches SQL status, sales reps should be confident that investing significant time in the opportunity is worthwhile. This qualification process prevents sales teams from wasting time on leads that are unlikely to convert, allowing them to focus on high-probability opportunities.
Key Points About SQL (Sales Qualified Lead)
SQLs have been vetted by both marketing and sales for purchase readiness
They meet defined criteria for budget, authority, need, and timeline (BANT)
SQL status indicates the lead is ready for direct sales engagement
The MQL-to-SQL conversion rate measures marketing-sales alignment
SQLs should receive prioritized attention from account executives
How to Use SQL (Sales Qualified Lead) in Your Business
Define Clear SQL Criteria
Work with your sales team to establish specific requirements for SQL status. This typically includes: confirmed budget range, identified decision-maker involvement, articulated business need, and defined purchase timeline. Document these criteria so everyone applies them consistently.
Implement a Qualification Process
Create a structured qualification process—usually a discovery call or series of questions—that sales development reps use to determine SQL status. Use frameworks like BANT, MEDDIC, or GPCTBA/C&I to ensure thorough qualification.
Track SQL Metrics
Monitor key metrics including: MQL-to-SQL conversion rate, SQL-to-opportunity rate, average time from SQL to close, and SQL win rate by source. These metrics reveal funnel health and help optimize your qualification criteria.
Create SQL-Specific Playbooks
Develop sales playbooks specifically for SQL engagement. Include talk tracks, objection handling, competitive positioning, and next-step recommendations. SQLs deserve a different approach than early-stage leads.
Real-World Examples
B2B Software Example
An MQL who downloaded several whitepapers is called by an SDR. During the call, they confirm: they have a $50K budget approved, the VP of Operations is the decision-maker and wants to meet, they need to solve their problem within Q2, and they're evaluating three vendors. This lead is now an SQL.
Professional Services Example
A consulting firm's SDR speaks with a CFO who attended their webinar. The CFO confirms they're planning a digital transformation initiative, have board approval for a $200K consulting engagement, and want to start within 60 days. Clear SQL criteria met.
Enterprise Sales Example
After multiple touchpoints with a Fortune 500 account, the champion confirms: there's an active RFP process, budget is allocated in this fiscal year, a buying committee is formed, and they want your company to submit a proposal. This account-level SQL warrants executive involvement.
Best Practices
- Align sales and marketing on SQL definitions before implementing
- Require sales to accept or reject SQLs within 24 hours with feedback
- Document why leads are disqualified to improve MQL quality over time
- Create a service-level agreement (SLA) for SQL follow-up timing
- Review SQL criteria quarterly and adjust based on conversion data
- Implement a recycling process for SQLs that aren't ready to buy yet
Common Mistakes to Avoid
- Using different SQL definitions across sales reps, creating inconsistency
- Qualifying based on a single criterion rather than multiple factors
- Not getting sales buy-in on SQL criteria, leading to rejection and conflict
- Failing to track SQL outcomes, making it impossible to optimize
- Over-qualifying leads to the point where pipeline volume suffers
Frequently Asked Questions
What's the difference between an SQL and an opportunity?
An SQL is a qualified lead ready for sales engagement. An opportunity is created when that SQL enters an active sales process—typically after an initial meeting where both parties agree to explore a potential deal. Not all SQLs become opportunities; some may be disqualified during initial conversations.
What is a good MQL-to-SQL conversion rate?
A healthy MQL-to-SQL conversion rate typically ranges from 15-30%. Below 10% suggests marketing is passing unqualified leads; above 40% might mean marketing's criteria are too strict, limiting volume. The ideal rate depends on your sales capacity and deal values.
Who is responsible for qualifying SQLs?
Sales Development Representatives (SDRs) or Business Development Representatives (BDRs) typically handle SQL qualification. They bridge marketing and sales, taking MQLs and qualifying them through outreach and discovery before passing true SQLs to Account Executives.
How long should SQL qualification take?
Initial SQL qualification should happen within 24-48 hours of the lead reaching MQL status. The actual qualification conversation might be a 15-30 minute discovery call. Speed matters—leads that are contacted quickly convert at much higher rates.
What happens to SQLs that don't convert?
SQLs that don't convert immediately should be recycled back to marketing for continued nurturing—not abandoned. Their status changes, but they remain in your database. Many deals close months or years after initial contact when timing finally aligns.
Related Terms
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