The Types of Leads, Explained
B2B lead types fall into two groups: temperature labels (cold, warm, hot) that describe engagement, and qualification stages (MQL, SAL, SQL, PQL) that describe where a lead sits in an agreed process. The taxonomy only becomes useful when each label has a written entry condition the system can check.
- A lead type without a written entry condition is a feeling with a job title.
- Temperature labels describe engagement. Qualification stages describe process position. Do not mix them.
- The two-axis model — fit and intent — makes most of the taxonomy unnecessary.
- SAL is the most useful underused stage, because it makes sales acceptance explicit and measurable.
- PQLs behave differently from MQLs and should never share a scoring model.
Two different things, both called lead types
Half the confusion in this topic comes from mixing two unrelated classification systems. One describes how engaged a lead is. The other describes where it sits in a qualification process. They are frequently used in the same sentence as if they were the same axis.
| System | Labels | Describes | Set by |
|---|---|---|---|
| Temperature | Cold, warm, hot | Engagement level and recency | Behaviour, usually informally |
| Qualification stage | Lead, MQL, SAL, SQL, PQL | Position in an agreed process | Explicit criteria, ideally enforced |
Temperature is a useful shorthand in conversation and useless in a system, because nobody can define the boundary between warm and hot. Qualification stages are the ones that belong in your CRM — provided each has a written entry condition.
The temperature labels
- Cold — no prior relationship or engagement. They have not heard of you. Everything in a standard outbound list is cold.
- Warm — some engagement exists: they downloaded something, attended a webinar, visited repeatedly, or came via a referral. They know who you are.
- Hot — active buying behaviour. Pricing page visits, demo requests, competitor comparisons, or a direct enquiry.
Useful for a conversation about prioritisation. Do not build routing or reporting on them — the moment two people have to agree whether a specific lead is warm or hot, the labels stop working.
The qualification stages
- 01Lead
A known contact record. Someone whose details you hold. No claim is being made about fit or intent — this is simply the entry state.
- 02MQL — marketing qualified lead
Meets marketing's agreed criteria for handing to sales. The one that causes the most conflict, because it is frequently defined by engagement alone rather than by fit and intent together.
- 03SAL — sales accepted lead
Sales has looked at it and agreed it is worth working. The most useful underused stage in B2B, because it converts 'sales says the leads are bad' from an opinion into a measurable rejection rate with reasons.
- 04SQL — sales qualified lead
Sales has spoken to them and confirmed a real opportunity exists — budget, authority, need, and timing are understood well enough to invest cycles.
- 05PQL — product qualified lead
A user of a free tier or trial whose usage indicates readiness to buy. Behaves differently from every other type on this list and needs its own model.
Why PQLs are genuinely different
Every other lead type is a proxy: you are inferring interest from behaviour that is adjacent to buying. A PQL is not a proxy. The person is using the product, and usage is direct evidence of value received.
That changes the mechanics in ways that matter operationally:
| MQL | PQL | |
|---|---|---|
| Evidence | Content engagement — a proxy for interest | Product usage — direct evidence of value |
| Best signal | Depth and recency of engagement | Reaching an activation milestone or a plan limit |
| Timing | Interest may be months from a decision | Often a live buying window right now |
| Typical conversion | Low single digits to low teens | Substantially higher |
| Right response | Nurture, then route when intent appears | Contact fast, with usage context attached |
Scoring PQLs with the same model as MQLs is a common and expensive mistake. A user who hit a plan limit yesterday and a contact who downloaded two ebooks are not comparable, and averaging them into one score buries the signal that actually predicts revenue.
The model that replaces most of this
The taxonomy exists because companies needed language for 'this lead is worth working'. A two-axis model expresses the same thing more precisely and is directly implementable.
- Fit — does this account match the ICP? Firmographic, technographic, and segment criteria. Objective and machine-checkable.
- Intent — has this account demonstrated a buying window? Behaviour, engagement depth, product usage, and trigger events. Also machine-checkable if instrumented.
| Low intent | High intent | |
|---|---|---|
| High fit | Nurture. Right company, wrong time. Do not route to sales. | Route immediately. This is the only true MQL. |
| Low fit | Suppress. Do not spend money here. | Investigate. Often a support query, a student, or a competitor. |
Reading that grid resolves most arguments about lead quality on the spot. High fit with no intent routed to sales is the single most common cause of a sales team learning to ignore marketing's leads. Low fit with high intent looks exciting in a dashboard and converts at close to zero.
Making the labels actually work
- 01Write one entry condition per stage
Objective, checkable by someone who was not involved. If the criterion is a feeling, it is not a criterion.
- 02Get both functions to sign it
Marketing and sales, on the same document. This is the cheapest high-value hour available to most B2B companies.
- 03Enforce it in the system
Stage transitions driven by conditions rather than opinion. A label anyone can set by hand will drift within a quarter.
- 04Require a reason on rejection
Every SAL rejection carries a reason from a fixed list. Within a month you know whether the problem is fit, intent, timing, or follow-through.
- 05Review the rejection reasons monthly
The patterns tell you what to fix. This is the most valuable ten minutes in the marketing and sales meeting.
For how to score against these axes, see lead quality. For where lead types sit in the wider process, the B2B lead generation playbook covers the full sequence.
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What are the different types of leads?
What is the difference between an MQL and an SQL?
What is a product qualified lead?
What is a sales accepted lead?
How should you classify leads?
Related guides.
Four metrics that measure quality honestly, why CPL hides the problem, and the rejection-reason loop that fixes targeting within a quarter.
Lead GenerationThe full process, the channel economics, and the qualification model — written for people who have to hit a pipeline number, not win a content award.
Lead GenerationOne creates the want, the other captures it. Getting the split wrong is why lead volume plateaus and cost per lead climbs at the same time.
Lead GenerationFirst we build your pipeline. Then we build the machine that scales it.
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