Sales Qualified Lead: Definition, Criteria & How to Find Them

A sales qualified lead is a prospect your sales team has vetted and confirmed is ready for direct sales engagement. Not just interested-actually ready to have a conversation about buying.

I've sent millions of cold emails and booked over 500,000 sales meetings across my companies. The biggest mistake I see teams make is treating every inbound form fill or email reply like it's a qualified opportunity. It's not. Most leads need more work before your closers should touch them.

Here's how to actually qualify leads in a way that doesn't waste your sales team's time.

What Makes a Lead Sales Qualified

A sales qualified lead has passed specific criteria that indicate they're worth your sales team's attention. This usually means they have:

• Budget to buy your solution
• Authority to make or influence the buying decision
• A real need or pain point your product solves
• A timeline for making a decision

This is the classic BANT framework, and it still works because it filters out tire-kickers. If someone doesn't have budget, can't make decisions, doesn't actually need what you're selling, or has no urgency, your closer is wasting time on that call.

Your SQL criteria should be stricter than your MQL criteria. A marketing qualified lead showed some interest-they downloaded a resource, visited your pricing page, or replied to an email. An SQL has been qualified by a human (usually SDR or BDR) who confirmed they meet your buying criteria.

The distinction matters because it changes how you allocate resources. Your most expensive assets-your closers-should only touch leads that have been properly vetted. Everything else is costing you money.

Why Sales Qualified Leads Are Critical to Your Business

SQLs represent the most efficient path to revenue. When you focus on properly qualified leads, you're not just improving close rates-you're fundamentally changing your sales economics.

In one of my SaaS businesses, we shifted from letting closers take any meeting to implementing strict SQL criteria. Our demo-to-close rate jumped from 18% to 34% in two months. Same closers, same product, same pricing. The only difference was lead quality.

Here's what happens when you nail SQL qualification: your sales cycle shortens because you're talking to people who are actually ready to buy. Your win rates go up because you're not chasing prospects who will never convert. Your team morale improves because they're closing more deals instead of spinning their wheels on dead-end opportunities.

The cost implications are real. If your average closer costs $100K per year and spends 40% of their time on unqualified leads, you're burning $40K annually per rep on wasted activity. Scale that across a team of ten and you're lighting $400K on fire every year.

SQLs also give you predictable revenue forecasting. When you know that 35% of your SQLs close within 45 days, you can accurately project pipeline. When your lead quality is all over the place, forecasting becomes guesswork.

SQL vs MQL: Why the Distinction Actually Matters

Marketing qualified leads are top-of-funnel. They raised their hand somehow. Sales qualified leads are mid-funnel. Someone on your team talked to them and confirmed they're legit.

In my companies, we generate MQLs through cold outbound, content, and paid ads. But we don't let our closers touch any of those leads until they've been qualified. Our SDRs handle that initial qualification conversation.

Here's what that looks like in practice: an SDR books a discovery call, asks qualifying questions, and if the prospect meets our criteria, they schedule them with an account executive. The AE doesn't waste 30 minutes on a call with someone who has a $500 budget for a $5,000 solution.

The difference between a 20% close rate and a 40% close rate often comes down to how well you're qualifying before handing leads to your closers. Better qualification means fewer wasted demos and more deals closed.

MQLs are generated through automated systems-marketing automation, lead scoring algorithms, website behavior tracking. SQLs require human judgment. A bot can tell you someone downloaded three whitepapers and visited your pricing page twice. Only a human conversation can tell you if they actually have budget and authority.

The transition from MQL to SQL should be a deliberate handoff with clear criteria. In our CRM, we track the MQL-to-SQL conversion rate by source. If paid ads are generating MQLs that only convert to SQL at 10%, but cold outbound converts at 40%, that tells us where to invest.

Understanding the Lead Qualification Stages

Most B2B companies have more than just MQL and SQL. Here's the full qualification lifecycle I use:

Suspect: A name in a database. They fit your ICP on paper but you haven't contacted them yet. This is everyone in your prospecting list before outreach.

Prospect: You've made contact. They opened your email, answered your call, or replied to your LinkedIn message. They're aware you exist but haven't shown buying intent.

MQL (Marketing Qualified Lead): They've taken an action that suggests interest. Downloaded content, attended a webinar, clicked through to pricing, or replied positively to outreach. Marketing considers them warm enough to pass to sales development.

SAL (Sales Accepted Lead): An SDR or BDR has accepted the lead and committed to working it. Not all companies use this stage, but it helps track accountability between marketing and sales.

SQL (Sales Qualified Lead): The lead has been qualified against your BANT or similar criteria. They're ready for your closers to engage.

Opportunity: A deal is officially in your pipeline with a realistic close date and deal value. The prospect is actively evaluating your solution and you're in the proposal stage.

The key is defining exactly what moves a lead from one stage to the next. Document the specific actions and criteria required. When your whole team understands the stages, your pipeline data actually means something.

How to Set SQL Criteria for Your Business

Your SQL criteria should be specific to your business model and ideal customer profile. Don't just copy BANT and call it a day.

Start by looking at your best customers. What do they have in common? Company size? Industry? Tech stack? Pain points? Buying triggers?

For one of my SaaS companies, our SQL criteria included:

• Company has 10-100 employees (our sweet spot)
• They're currently using a competitor or manual process
• They're talking to the founder, head of sales, or head of marketing
• They want to implement within 90 days
• They have budget allocated or can get approval quickly

We didn't require all five, but they needed at least three. This gave us flexibility while still filtering out bad fits.

Document your criteria in a shared resource. I created a qualification checklist in our CRM that SDRs had to complete before marking a lead as SQL. This kept everyone aligned and made it easy to audit quality. You can track this stuff in a sales KPIs tracker to see which lead sources produce the best SQLs.

Your criteria should evolve as your business matures. When you're scrappy and early-stage, you might take any lead with a pulse and a credit card. As you scale, you can afford to be selective. We tightened our SQL criteria every six months as we learned what actually predicted closes.

Common SQL Criteria by Sales Model

Your criteria will vary based on whether you're selling $500/month SaaS or $50K enterprise deals. Here's what I've seen work:

For lower-priced products ($500-$2K/month): Focus on fit and timeline. Can they start quickly? Do they match your ICP? Are they the decision maker? You can't spend hours qualifying a $1K deal.

For mid-market ($2K-$10K/month): Add budget verification and use case validation. Make sure they actually have the problem you solve and can afford your solution.

For enterprise ($10K+/month): Full BANT qualification plus technical requirements, security needs, and buying process understanding. You need to know who else is involved and what their procurement looks like.

For enterprise deals, I also qualify for political dynamics. Who's the champion? Who might block the deal? What's happened with past vendor evaluations? These deals rarely fail on product fit-they fail on internal politics.

Alternative Qualification Frameworks Beyond BANT

BANT works, but it's not the only framework. Depending on your sales model, these alternatives might fit better:

CHAMP (Challenges, Authority, Money, Prioritization): Starts with the customer's challenges instead of budget. This works well for consultative sales where you need to uncover pain before discussing price. I use this for higher-touch deals where we're solving complex problems.

MEDDIC (Metrics, Economic Buyer, Decision Criteria, Decision Process, Identify Pain, Champion): Built for enterprise sales with multiple stakeholders. It forces you to map out the entire buying committee and understand their process. Overkill for SMB deals, essential for six-figure contracts.

GPCT (Goals, Plans, Challenges, Timeline): Focuses on the prospect's strategic objectives. Works well for solution selling where you're aligning to their business outcomes rather than just solving a tactical problem.

ANUM (Authority, Need, Urgency, Money): Prioritizes authority first. If you're not talking to a decision maker, nothing else matters. I use this framework for cold outbound where we want to disqualify fast if we're talking to the wrong person.

Pick one framework and stick with it. Switching frameworks confuses your team and makes your data inconsistent. The best framework is the one your team will actually use consistently.

The Qualification Process: What to Ask

Qualification happens in that first real conversation. Here are the questions I train my SDRs to ask:

On current situation: "What are you using now to handle [problem]?" This tells you if they're actively feeling pain or just browsing.

On decision making: "Who else would be involved in evaluating a solution like this?" If they say "I'd have to check with my boss," you're not talking to the decision maker.

On timeline: "What's driving you to look at solutions now?" If there's no trigger event or deadline, they're not urgent.

On budget: "Have you allocated budget for this?" or "What's your ballpark budget for solving this problem?" Don't dance around it. If they can't afford you, better to know now.

I don't script these word-for-word. The goal is to have a real conversation while hitting these points naturally. If you sound like a robot reading a checklist, prospects shut down.

After the call, your SDR should be able to answer: Does this person meet our SQL criteria? If yes, book them with sales. If no, either nurture them or disqualify them entirely.

One technique that works: the summary close at the end of the qualification call. "So if I'm hearing you right, you're currently using [current solution], spending about [time/money], and you're looking to solve [specific problem] in the next [timeline]. You're the [title] and you'd be making this decision with [other stakeholder]. Does that sound accurate?" This confirms you understood their situation and gives them a chance to correct anything you missed.

How to Identify Intent Signals That Predict SQLs

Not all interest is equal. Some actions strongly predict SQL status, others are just noise. Here's what I've found actually matters:

High-intent signals: Visiting your pricing page multiple times, requesting a demo, asking specific product questions, comparing you to competitors by name, asking about implementation timelines, requesting case studies in their industry. These prospects are actively evaluating solutions.

Medium-intent signals: Downloading multiple resources, attending a webinar, engaging with your email sequences, connecting with multiple people at your company on LinkedIn. They're interested but might not be in active buying mode.

Low-intent signals: Opening one email, visiting your homepage once, downloading a single top-of-funnel resource. This is basic awareness, not intent.

The best intent data comes from direct conversations. All the behavioral signals in the world don't beat a prospect saying "We need to solve this by end of quarter and I have $50K allocated."

If you're using intent data tools, focus on account-level signals-like a company suddenly researching your product category across multiple employees. That's more predictive than individual behavior.

Where to Find Sales Qualified Leads

You can't qualify leads you don't have. Here's how I source prospects who are likely to become SQLs:

Cold outbound: Build lists of your ICP and reach out directly. This is still the fastest way to fill your pipeline with qualified prospects. I've used this to book tens of thousands of meetings. You can grab sample scripts from my top 5 cold email scripts resource.

For list building, you need a reliable source of contact data. Tools like this B2B lead database let you filter by title, company size, and industry to find exactly who you're targeting. Other solid options include Apollo, ZoomInfo, and Lusha.

If you need to find specific contact information for prospects you've already identified, an email finding tool can fill in the gaps. Then validate those emails with an email verification service to keep your bounce rate low.

Inbound from content: SEO articles, YouTube videos, and lead magnets attract people searching for solutions. The key is qualifying them fast once they come in. Not everyone who downloads a PDF is sales-ready.

Referrals: Referred leads convert at 3-5x the rate of cold leads in my experience. They come in pre-qualified because someone vouched for them. Always ask happy customers who else they know who might benefit.

LinkedIn outreach: Direct messages to decision makers can work if you're targeting specific accounts. Keep it personalized and relevant. Tools like Expandi can help automate the connection process while keeping it safe.

The best lead sources are the ones where you control the targeting. Cold email and LinkedIn let you go after exactly who you want. Paid ads and SEO cast a wider net, which means more qualification work on the back end.

For enterprise outreach targeting Fortune 500 companies and large accounts, my Enterprise Outreach System walks through the specific approach that works for big deals.

Building Target Account Lists That Generate SQLs

The quality of your SQLs starts with the quality of your targeting. Garbage in, garbage out.

I build account lists by starting with firmographic data: company size, industry, revenue range, employee count, location. This gets you in the ballpark. Then I layer on technographic data-what tools they're using, what their tech stack looks like. If you're selling a Salesforce integration, you better be targeting companies that use Salesforce.

Next, I look for trigger events. Companies that just raised funding, just hired a new executive in a relevant role, just announced expansion, or just posted a job opening related to your solution. These trigger events create urgency and budget.

For technographic prospecting, a BuiltWith data scraper helps identify companies using specific technologies. If you know your best customers all use Shopify, go find more Shopify stores.

The more specific your targeting, the higher your MQL-to-SQL conversion rate. When you're prospecting companies that look exactly like your best customers, qualification becomes easier because they naturally fit your criteria.

Disqualifying Leads: When to Walk Away

Good qualification means knowing when to say no. Not every lead deserves your time.

Disqualify immediately if they:

• Don't have budget and can't get it approved
• Aren't the decision maker and won't introduce you to them
• Are comparing 10+ solutions with no clear criteria (tire kickers)
• Want custom features you don't offer and won't buy without them
• Are a terrible fit for your ICP (wrong industry, size, use case)

Early in my career, I wasted weeks chasing leads that were never going to close. I'd take every meeting because I thought more activity meant more deals. Wrong. More qualified activity means more deals. Chasing bad fits just burns time and morale.

Now my team has permission to disqualify fast. If someone doesn't meet our criteria, we send them a polite "not a fit right now" email and move on. This keeps our pipeline clean and our close rates high.

I track disqualification reasons in our CRM. If 40% of leads are disqualified for "no budget," that's a targeting problem-we're prospecting companies that can't afford us. If 30% are disqualified for "wrong persona," our list building needs better title filtering.

Some reps are afraid to disqualify because they don't want to look like they're not working hard enough. I've seen reps keep zombie leads in their pipeline for months just to pad their numbers. This destroys forecast accuracy and wastes everyone's time. Disqualifying is a skill, not a failure.

Moving SQLs Through Your Funnel

Once you've qualified a lead, speed matters. The faster you can get them into a demo or proposal, the higher your conversion rate.

Our process: SDR qualifies and books meeting with AE same week. AE demos and sends proposal within 24 hours. Follow up until close or disqualify.

Long sales cycles aren't always about deal complexity. Often they're about slow follow-up. If you take three days to send a proposal, your SQL is talking to your competitor in the meantime.

Use a CRM to track every SQL and where they are in your pipeline. I like Close because it's built for outbound sales teams and makes follow-up easy. Monday.com works well too if you need more customization.

Set clear next steps on every call. "I'll send you a proposal by Wednesday, then let's schedule 15 minutes Friday to review it together." Don't leave it vague. Vague next steps kill deals.

The handoff from SDR to AE is critical. I have my SDRs join the first five minutes of the AE call to do a warm introduction and recap what was discussed in the qualification call. This prevents the prospect from having to repeat themselves and ensures context isn't lost.

Creating a Lead Handoff Process That Maintains Quality

Most revenue gets lost in the handoff between marketing, SDRs, and AEs. Information gets dropped, context disappears, and the prospect has to repeat their story three times.

Here's the handoff process that works in my companies:

Marketing to SDR: Marketing passes MQLs to SDRs with full context-what content they engaged with, what pages they visited, what emails they clicked. This lives in the CRM, not a Slack message. The SDR reviews this before reaching out so they can reference specific content: "I saw you downloaded our ROI calculator..."

SDR to AE: SDR completes a qualification checklist in the CRM before booking the meeting. Budget range, decision makers involved, timeline, current solution, pain points, and any specific requirements. The AE reviews this before the call. During the handoff, the SDR introduces the AE, recaps the prospect's situation, and sets expectations for the demo.

AE to implementation: Once a deal closes, the AE fills out an onboarding form with everything the implementation team needs to know. Technical requirements, use cases, stakeholders, success criteria. The implementation lead reaches out within 24 hours of close.

Every handoff should include a live conversation or call, not just a CRM note. Context gets lost in writing. A 5-minute verbal handoff prevents hours of confusion later.

Measuring SQL Quality

Not all SQLs are created equal. Track these metrics to understand if your qualification process is working:

SQL to opportunity rate: What percentage of your SQLs turn into real opportunities (demos completed, proposals sent)? Should be 60%+.

SQL to close rate: What percentage of SQLs become customers? This tells you if your qualification criteria actually predict buying behavior.

Time to close by source: Do SQLs from outbound close faster than inbound? This tells you which channels produce the best quality leads.

Disqualification reasons: Why are leads being disqualified? If 50% of your MQLs are getting disqualified for "no budget," your marketing targeting is off.

I review these numbers weekly with my sales team. If our SQL to close rate drops, we tighten qualification criteria. If we're disqualifying too many leads, we adjust our targeting on the front end.

You can't improve what you don't measure. Set up dashboards that show you lead quality in real time, not just lead volume.

Average deal size by SQL source: Are SQLs from referrals bigger deals than SQLs from cold email? This helps you prioritize where to invest resources.

SQL velocity: How quickly do SQLs move through your pipeline? If SQLs from one source take 90 days to close but another closes in 30 days, that affects cash flow and forecasting.

SQL to MQL ratio by channel: If paid ads generate 1000 MQLs but only 50 SQLs (5% conversion), while cold outbound generates 200 MQLs and 80 SQLs (40% conversion), you know where to double down.

Training Your Team on SQL Qualification

Your SQL criteria are only as good as your team's ability to apply them consistently.

I onboard every new SDR with recorded qualification calls from our top performers. They listen to how our best reps ask questions, handle objections, and determine fit. Then they shadow calls for a week before doing their own.

Role play is underrated. Have your SDRs practice qualification conversations with each other and with managers. The more comfortable they are asking budget and authority questions, the better they'll qualify.

Create a qualification checklist in your CRM that has to be completed before marking a lead as SQL. This forces consistency and gives you data on why leads are (or aren't) qualified.

I run weekly call reviews where we listen to qualification calls as a team. Not to criticize, but to calibrate. When everyone hears the same call and discusses whether it should be SQL'd, you build shared judgment across the team.

Document your objection handling for common qualification pushback. When a prospect says "I need to think about it" or "Send me some information," what do your reps say? Script out the responses that work and train everyone on them.

SQL Qualification at Scale

When you're booking 100+ meetings per month, manual qualification gets harder. Here's how to maintain quality at volume:

Automated pre-qualification: Use email or calendar form questions to screen before the first call. "What's your company size?" "What's your current solution?" "What's your timeline?" Filter out obvious bad fits before they hit your calendar.

Tiered qualification: Not every lead needs the same level of scrutiny. High-ticket enterprise deals get deep qualification. Lower-priced products get lighter qualification focused on fit and timeline.

Lead scoring: Assign point values to behaviors and attributes. Company size, job title, engagement level, etc. Leads above a certain score get prioritized for fast follow-up.

I've scaled multiple outbound teams past seven figures using these systems. The key is balancing speed with quality. You want to move fast on good leads without letting bad ones clog your pipeline.

Automation tools like Instantly or Smartlead help manage high-volume cold email campaigns. Once leads reply, they get routed to SDRs for qualification. The automation handles the top-of-funnel volume so humans can focus on qualification conversations.

For enriching lead data at scale, Clay pulls in company and contact information from dozens of sources. This helps you qualify on paper before you ever reach out-filtering for company size, tech stack, job titles, and more.

Using Technology to Improve SQL Identification

The right tools make qualification faster and more accurate. Here's my tech stack for SQL identification:

CRM: Everything starts here. Your CRM needs custom fields for qualification criteria, automation for lead routing, and reporting to track SQL metrics. I use Close but any modern CRM works if configured properly.

Email automation: For cold outbound, you need a tool that sends emails at scale while maintaining deliverability. Instantly, Smartlead, and Lemlist all work well. The key is rotating domains and managing sender reputation.

Lead enrichment: Tools that fill in missing data points-company size, revenue, tech stack, funding status. This helps you qualify before outreach. Clay and Apollo both do this well.

Conversation intelligence: Record and analyze qualification calls to identify what questions and approaches lead to higher SQL rates. Look for patterns in calls that result in closed deals versus calls that go nowhere.

Lead scoring: Most CRMs have built-in lead scoring. Set up rules that automatically score leads based on fit criteria and engagement. High-scoring leads get prioritized for immediate follow-up.

Don't over-engineer your stack. I've seen companies with 15 tools in their sales tech stack where three would have done the job. More tools means more things to break and more training required.

Common SQL Qualification Mistakes and How to Avoid Them

I've made every qualification mistake in the book. Here's what kills SQL quality:

Qualifying on fit, ignoring intent: A prospect might be a perfect ICP match-right company size, right industry, right title-but if they have no urgency, they're not an SQL. Fit plus intent is what matters.

Letting reps self-report SQL quality: If you let SDRs mark their own leads as SQL without oversight, quality will drift. Spot-check SQL designations weekly. Listen to the calls. Make sure criteria are being applied consistently.

Setting SQL criteria too loose: When you're desperate for pipeline, it's tempting to lower the bar. Bad idea. This just pushes the problem downstream to your closers who waste time on unqualified deals. Keep standards high.

Not adapting criteria as you learn: Your initial SQL criteria are a guess. As you close deals and gather data, you'll learn what actually predicts closes. Update your criteria every quarter based on what you're learning.

Ignoring soft factors: Sometimes a prospect checks all the boxes on paper but the conversation feels off. They're evasive about budget, they can't articulate their pain clearly, they keep rescheduling calls. Trust your gut. These behavioral signals matter.

Qualifying once and assuming it stays true: A prospect who was SQL-worthy three months ago might not be today. Their priorities changed, their budget got reallocated, their champion left the company. Requalify long-cycle deals at each stage.

What Happens to Unqualified Leads

Just because a lead isn't sales-qualified today doesn't mean they're worthless. Build a nurture track for leads that are:

• Good fit but no budget right now
• Right company but wrong contact (junior person who can't decide)
• Interested but no urgency or timeline

Put these leads into email sequences that provide value and stay top of mind. When their situation changes-they get budget, get promoted, or their pain intensifies-you want to be the first call they make.

I've closed six-figure deals from leads that were disqualified a year earlier. They weren't ready then. They are now. Nurture is a long game, but it pays off.

For leads that are just a bad fit (wrong industry, too small, need features you'll never build), delete them or mark them as disqualified permanently. Don't clutter your CRM with people you'll never sell to.

The difference between a bloated pipeline and a clean one is ruthless qualification. Keep only the leads that can actually become customers, and move them forward aggressively. Everything else is a distraction.

My nurture sequences are simple: one valuable email per month. A relevant case study, a how-to article, an industry insight. No hard selling. Just staying visible until they're ready.

Aligning Sales and Marketing on SQL Definition

The number one source of sales and marketing conflict is disagreement about what counts as a qualified lead. Marketing thinks they're sending gold, sales thinks they're getting garbage.

Fix this by creating a shared SQL definition that both teams agree to. Sit down together and define: What specific criteria must a lead meet to be considered sales-qualified? What does budget mean-verbal confirmation, allocated in their budget, or ability to get approval? What counts as authority-ultimate decision maker or strong influencer?

Document this in a service level agreement (SLA) between marketing and sales. Marketing commits to delivering X SQLs per month that meet the agreed criteria. Sales commits to following up within Y hours and providing feedback on lead quality.

Hold monthly meetings where you review SQL quality together. Which leads closed? Which were disqualified and why? Are the criteria too strict or too loose? Make adjustments based on data, not opinions.

In my companies, I have marketing sit in on qualification calls monthly. This helps them understand what actually happens when their MQLs get contacted. It builds empathy and improves their targeting.

The goal isn't for marketing and sales to be best friends. The goal is for them to agree on what success looks like and hold each other accountable to the SLA.

SQL Qualification for Different Industries

Qualification looks different depending on what you're selling. Here's what I've learned across different sectors:

B2B SaaS: Focus on current tech stack, user count, and integration requirements. Are they using a competitor? How many seats do they need? What's their data volume? Technical fit matters as much as budget and authority.

Professional services: Qualify on project scope, timeline, and past experience with similar services. Have they worked with agencies before? What happened? Are they looking for strategy or execution? One-off project or ongoing relationship?

Manufacturing and wholesale: Order volume, payment terms, and delivery requirements are critical. What's their typical order size? Net 30 or upfront payment? Do they need just-in-time delivery or can they hold inventory?

Real estate and high-ticket local services: Geographic fit, property type, and transaction timeline. Are they in your service area? Is this their primary residence or investment property? Are they pre-approved for financing?

Tailor your qualification framework to what actually predicts deals in your industry. Generic BANT is a starting point, not the finish line.

The Role of Sales Development in SQL Creation

Your SDR or BDR team is the engine that creates SQLs. If this function isn't working, your closers starve for pipeline.

The best SDRs are curious, persistent, and comfortable with rejection. They're not intimidated to ask hard questions about budget and authority. They genuinely want to understand if there's a fit.

I compensate SDRs based on both SQL volume and SQL quality. They get a bonus for every SQL they create, plus an additional bonus if that SQL closes. This aligns incentives-they want to book meetings, but they want to book good meetings that actually close.

Career pathing matters. Your best SDRs should have a clear path to AE roles. If they're stuck doing qualification forever with no promotion path, they'll leave. I promote top SDRs to AE within 12-18 months if they're hitting their numbers.

Give SDRs the support they need: good training, regular coaching, quality leads to work, and tools that make them efficient. An SDR with a bad lead list and no training is set up to fail.

SQL Strategies for Outbound vs Inbound

Outbound and inbound SQLs behave differently and need different approaches:

Outbound SQLs: You initiated the conversation. They weren't actively looking for a solution. Your qualification needs to confirm that they have the pain you solve and that now is the right time to address it. Outbound SQLs often have longer sales cycles because you're creating urgency rather than responding to it.

The upside: you control who you target. You can build lists of perfect-fit accounts and go after them systematically. Quality is high if your targeting is good.

Inbound SQLs: They came to you. They're already looking for a solution, which means intent is higher. Your qualification focuses on confirming they're a good fit and that you're competitive with other solutions they're evaluating.

The challenge: you don't control who shows up. You get whoever your marketing attracts. Some will be great fits, others will be terrible. You need tight qualification to separate signal from noise.

I run both inbound and outbound motions in parallel. Outbound fills the pipeline with target accounts we want to land. Inbound captures demand we've created through content and brand. Both feed SQLs to the same AE team.

Advanced SQL Tactics: Multi-Threading and Expansion

Once you've identified an SQL, don't stop at a single contact. Multi-thread the relationship by connecting with multiple stakeholders at the account.

In enterprise deals, the person who requested the demo is rarely the only person involved in the decision. Find the economic buyer, the technical evaluator, the end users, and the procurement contact. Build relationships with all of them.

I train my AEs to ask during the first call: "Who else should be involved in this conversation?" Then actually get those people on the next call. Don't wait until the proposal stage to discover there are three other stakeholders you've never talked to.

Multi-threading also protects your deal. If your champion leaves the company or gets reassigned, you still have other relationships. Single-threaded deals die when your one contact changes roles.

For expansion, treat existing customers differently than new SQLs. They've already bought from you, so your qualification is about new use cases, additional products, or increased usage. The bar for an expansion SQL is lower because you've already de-risked the relationship.

Implementing Your SQL Framework This Week

Here's how to actually implement what I've covered:

Step 1: Document your current best customers. Make a list of your top 10 customers by revenue or lifetime value. What do they have in common? That's your ICP and the basis for your SQL criteria.

Step 2: Define your SQL criteria. Use BANT, CHAMP, or another framework. Write down the specific questions your team needs to ask and the answers that indicate SQL status. Get sales and marketing to agree on this definition.

Step 3: Build a qualification checklist in your CRM. Create custom fields for each criterion. Make it required to fill these out before changing a lead's stage to SQL.

Step 4: Train your team. Walk through the criteria with everyone who qualifies leads. Do role-plays. Listen to calls together and practice identifying SQL versus non-SQL.

Step 5: Start measuring. Track SQL to close rate, SQL to opportunity rate, and disqualification reasons. Review these weekly and adjust your criteria as you learn.

You don't need to be perfect on day one. Pick criteria that seem reasonable, implement them, and iterate as you gather data. The goal is consistent qualification, not perfect qualification.

If you want help implementing this entire system with live feedback on your specific business, that's what we do inside Galadon Gold.