What is SQL?
Sales Qualified Lead
Definition, formula, India benchmarks, and the operator-grade nuance behind it.
SQL is a lead that has been confirmed by sales as having genuine buying intent, budget, authority, and timing for purchase. SQLs progress to demo → opportunity → closed-won. SQL definition typically includes BANT (Budget, Authority, Need, Timing) or MEDDIC qualifying questions.
SQL = sales-qualified after discovery confirms BANT/MEDDIC.
SQL → close conversion: 15–35%.
SQL count is the most accurate predictor of pipeline health.
Sales Qualified Lead is a lead that passed sales discovery and confirms BANT or MEDDIC qualification criteria.
SQL = MQL × Sales Discovery Confirmation (BANT or MEDDIC criteria met)The operator's read on SQL
SQL is the most CFO-meaningful pipeline metric. SQL count × close rate × deal size = revenue forecast. Indian B2B SaaS Series A: typically 30–100 SQLs/month with 20–30% close rate. Below 30 SQLs/month at Series A indicates lead-gen weakness or sales over-qualification. Above 100 SQLs/month with low close rate indicates sales lacks discipline. Track ratio SQL → opp → won-lost-reasons monthly.
India 2026 benchmarks — SQL
- Indian B2B SaaS Series A SQLs/month: 30–100
- SQL → opportunity conversion: 60–80%
- Opportunity → closed-won: 20–40%
- SQL CAC (fully-loaded): ₹3,000–₹15,000
- Time from MQL to SQL: 3–14 days typical
Common mistakes to avoid
- Sales declining to formally qualify (calls everyone 'opportunity').
- Not tracking lost-reasons by SQL.
- Treating all SQLs equally (deal-size segmentation matters).
- No SLA from MQL to SQL.
Frequently asked questions
What's a typical SQL value in India?
India 2026 benchmarks vary by category: Indian B2B SaaS Series A SQLs/month: 30–100; SQL → opportunity conversion: 60–80%; Opportunity → closed-won: 20–40%. Bands compress in saturated CPM regimes and widen as products move from impulse to considered. The right benchmark for your business depends on stage, gross margin, and channel mix.
What are the most common mistakes when tracking SQL?
Three mistakes recur most often: Sales declining to formally qualify (calls everyone 'opportunity').; Not tracking lost-reasons by SQL.; Treating all SQLs equally (deal-size segmentation matters).. The simplest defense is to define each metric explicitly in your reporting playbook and avoid mixing definitions across teams.
How does SQL relate to other unit-economics metrics?
SQL is most useful in context. Pair it with MQL and PQL to build a complete picture. SQL alone can mislead — the relationship between metrics matters more than any single number.
Should I optimize SQL or accept industry-standard values?
Optimization depends on your stage. Early-stage businesses often have SQL values outside healthy bands and need to fix structural issues (audience, creative, retention) before chasing the metric. Established businesses can compound through marginal improvements. Frameleads' Growth System maps which lever moves which metric in your specific category.
How SQL behaves per industry
SQL is a universal metric, but its band, drivers, and optimisation levers vary by category. Drill into the industry-specific version below for the deep view.
- SQL for Real Estate DevelopersCAC 3,500–35,000 ₹ · CPC 40–280 ₹Open
- SQL for D2C BrandsCAC 250–2,200 ₹ · CPC 8–60 ₹Open
- SQL for B2B SaaS StartupsCAC 15,000–3,00,000 ₹ · CPC 50–1,200 ₹Open
- SQL for Healthcare Clinics & HospitalsCAC 500–15,000 ₹ · CPC 15–250 ₹Open
- SQL for Education & EdTechCAC 400–4,500 ₹ · CPC 12–160 ₹Open
- SQL for Financial ServicesCAC 1,500–20,000 ₹ · CPC 30–950 ₹Open
- SQL for Professional ServicesCAC 800–12,000 ₹ · CPC 20–500 ₹Open
- SQL for Restaurants, Cafes & Cloud KitchensCAC 150–2,500 ₹ · CPC 8–120 ₹Open
- SQL for Fashion & Apparel D2CCAC 200–1,200 ₹ · CPC 10–55 ₹Open
- SQL for Gyms, Studios & Fitness AppsCAC 250–1,800 ₹ · CPC 12–80 ₹Open
- SQL for Automotive Dealers & OEMsCAC 600–4,500 ₹ · CPC 18–120 ₹Open
- SQL for Manufacturing & MSMEsCAC 3,000–35,000 ₹ · CPC 25–220 ₹Open
Questions about SQL
Long-form guides on related topics
Pair this with
Sources & references
Cited primary and analyst sources. Independent of Frameleads' own data.
- IBEF — India Brand Equity Foundation: Indian Industry Reports — IBEF (Ministry of Commerce & Industry)
Sector-level market size, growth, and policy context for Indian industries.
- IAMAI — Internet & Mobile Association of India — IAMAI
Digital advertising industry body; reports on India internet user base, ad spend, and platform shares.
- MoSPI — Ministry of Statistics and Programme Implementation — Government of India
Primary source for India macro-economic indicators (CPI, GDP, household consumption).
- ASCI Code for Self-Regulation of Advertising in India — Advertising Standards Council of India
Mandatory baseline for all advertising claims in India — including digital, influencer, and comparative ads.
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