Sales Qualified Leads (SQL)
Last updated: May 30, 2025
What is Sales Qualified Leads?
A Sales Qualified Lead (SQL) represents a prospect who has progressed beyond initial marketing engagement and demonstrates genuine potential for conversion. Unlike Marketing Qualified Leads (MQLs) that indicate early interest, SQLs have been vetted by sales professionals and meet specific criteria that suggest a higher likelihood of becoming a paying customer. These leads sit strategically in the middle of your sales funnel, having moved past the awareness stage but not yet reached the final purchase decision point.
Sales Qualified Leads Formula
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How to visualize Sales Qualified Leads?
When tracking your SQLs, it helps to add segmentation to your data for more context. For example, you could track your SQLs in a bar chart segmented by lead source.
Sales Qualified Leads visualization example
Sales Qualified Leads
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Sales Qualified Leads
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Measuring Sales Qualified LeadsMore about Sales Qualified Leads
The transition from MQL to SQL marks a crucial handoff between marketing and sales teams, and getting this process right can dramatically impact your conversion rates and revenue pipeline. Marketing teams typically generate MQLs through content engagement, form submissions, webinar attendance, or other qualifying activities that demonstrate interest. However, an MQL simply indicates someone has raised their hand and shown receptiveness to learning more about your solution—they're not necessarily ready to buy. The sales team's role is to engage these prospects, conduct discovery conversations, and determine whether they meet the stricter criteria for SQL classification.
The key differentiator for SQL qualification typically revolves around the BANT framework: Budget, Authority, Need, and Timeline. A true SQL should have a clearly articulated business need that your solution can address, access to or influence over the purchasing decision, an allocated or accessible budget for your type of solution, and a realistic timeline for making a purchase decision. Some organisations also include additional criteria such as company size, geographic location, or specific use cases that align with their ideal customer profile.
Understanding the distinction between MQLs and SQLs is essential for accurate forecasting and resource allocation. SQLs should convert to opportunities at a much higher rate than MQLs—typically 20-30% for SQLs versus 5-15% for MQLs, though these benchmarks vary significantly by industry and sales cycle length. This metric helps sales leaders prioritise their team's efforts and provides marketing with feedback on lead quality, creating a continuous improvement loop that benefits both departments.
Sales Qualified Leads Frequently Asked Questions
What's the difference between an SQL and a sales opportunity?
While an SQL indicates a qualified prospect worth pursuing, an opportunity represents a more advanced stage where there's active engagement in your sales process. An SQL might convert to an opportunity when the prospect agrees to a formal needs assessment, requests a proposal, or enters into structured negotiations. Think of SQLs as qualified prospects who warrant sales attention, while opportunities are prospects actively working through your sales methodology with clear next steps and mutual commitment to explore a potential purchase.
How should we measure SQL quality and success?
The most important metrics for SQL performance include SQL-to-opportunity conversion rate, SQL-to-closed-won conversion rate, and the average time from SQL to close. Additionally, track the velocity of SQLs through your pipeline and the average deal size generated from SQL sources. Quality indicators include how well SQLs align with your ideal customer profile and whether they're progressing through sales stages at expected rates. Poor SQL quality often manifests as low conversion rates, extended sales cycles, or high drop-off rates in early sales stages.
Who should be responsible for defining SQL criteria?
SQL criteria should be collaboratively defined by sales and marketing leadership, with input from customer success teams who understand what makes customers successful long-term. Sales should take the lead since they'll be working these leads directly, but marketing needs to understand the criteria to ensure MQL-to-SQL handoff processes are effective. Regular review sessions between teams are essential, as SQL criteria may need adjustment based on market changes, product evolution, or performance data. The most successful organisations treat SQL definitions as living documents that evolve with their business rather than static rules set once and forgotten.