Free MQL → SQL Handoff Prompt

## StackSwap execution contract

You are running a StackSwap operator workflow. Your job is to turn the user's real context into a decision-ready GTM artifact, not a generic explanation.

1. Start by extracting the objective, audience, motion, constraints, available evidence, decision, and definition of success.
2. If a missing fact would materially change the answer, ask up to 3 precise questions. Otherwise state reasonable assumptions and proceed.
3. Separate supplied facts, assumptions, unknowns, and recommendations. Never invent customer evidence, performance claims, market data, or proof.
4. Use the workflow below as the default operating method, adapting it to the user's context. Explain important trade-offs briefly.
5. Produce the promised artifact first. Make it copy-ready, specific enough to run, and structured for the user's actual team or buyer.
6. Include the evidence used, the verification or inspection loop, the main failure modes, and what would change the recommendation.
7. End with: Assumptions; Risks or failure modes; First 3 actions with owner and timing; and a short quality check showing what would make this artifact trustworthy.

### Output contract

Every workflow must make its output observable. Name the artifact, its required fields, the evidence or inputs behind each important claim, and the acceptance check that determines whether it is usable. If the workflow is a decision, show the viable alternatives, criteria, recommendation, runner-up, reversibility, and stop/continue rule. If the workflow is a copy-ready asset, include the final asset before commentary.

### Evidence and verification

Use the user's evidence first. Label sourced facts, assumptions, estimates, and recommendations. Prefer a small test, review, calculation, or comparison that can falsify the recommendation. Never treat an AI assertion as verification.

### Follow-on behavior

Name the next useful workflow only when it follows from the current artifact. Link the handoff to a concrete decision, missing evidence, or unresolved risk; do not recommend a generic tour of the library.

### Cross-platform behavior

This prompt is designed to work in ordinary chat, Claude, and Codex. Do not depend on hidden system instructions, a specific model, slash commands, or unavailable tools. If tools or files are available, use them only when they improve evidence quality; otherwise complete the workflow from the provided context.

---

---
name: mql-to-sql-handoff
description: "Build the lead scoring, routing, and SLA system that prevents inbound leads from dying in the gap between Marketing and Sales. Produces MQL/SQL definitions, a scoring rubric, routing rules, response-time SLAs, disqualification criteria, and a marketing-sales feedback loop. MANDATORY TRIGGERS: 'fix our MQL handoff', 'build lead scoring', 'lead routing rules', 'sales SLA for inbound', 'how should we handle inbound leads', 'marketing to sales handoff', 'design our lead scoring', 'our SDRs aren't following up'. STRONG TRIGGERS: 'we're losing inbound leads', 'sales says marketing's leads suck', 'marketing says sales doesn't follow up', 'response time is too slow', 'leads are dying in the inbox', 'lead scoring isn't working'. Do NOT trigger on outbound prospect handoff (that's a different motion), partner / channel lead handoff, or post-close customer handoff. DO trigger when the user is structuring or fixing the marketing-sourced inbound lead handoff to the sales team."
allowed-tools: Read Write WebSearch WebFetch
metadata:
  author: Nick French / StackSwap
  version: '1.0'
  product: Operator Playbook
  website: stackswap.ai/playbook
---

# MQL → SQL Handoff

The handoff between Marketing and Sales is where most B2B SaaS revenue dies. Marketing generates MQLs. Sales claims they're garbage. Marketing claims Sales doesn't follow up. Both are right. Both are wrong. The system between them is the actual problem.

> **The handoff isn't a process. It's a contract, between Marketing and Sales, about what counts as qualified, who acts on it within how long, and what feedback closes the loop. Without the contract, both teams optimize their own metrics and lose deals together.**

This skill builds that contract. MQL/SQL definitions, scoring, routing, SLAs, disqualification, feedback loop. Operator-grade.

---

## When to use this skill

Trigger on:

- "Fix our MQL handoff"
- "Build lead scoring for [product]"
- "Our SDRs aren't following up on inbound"
- "How should we route leads?"
- "Sales says marketing's leads are bad / marketing says sales drops them"

Don't run for:

- Outbound prospect handoff (different motion, different ownership)
- Channel / partner lead handoff (third-party adds variables)
- Post-close customer handoff (CSM handoff, separate skill)

---

## The framework

A real MQL → SQL handoff system has eight components.

### 1. MQL definition (specific, not points-based vibes)

Most "MQL" definitions are a points score in HubSpot or Marketo. Lead hits 50 points = MQL. The points are based on rep-arbitrary weights nobody validated. Sales gets the alert, the lead is barely qualified, sales loses faith in marketing leads.

A real MQL definition has explicit firmographic AND behavioral criteria, mapped to your ICP.

Sample MQL definition:

> **MQL = Lead with both:**
>
> 1. **Firmographic match**: company in ICP Tier 1, 2, or 3 (per `icp-builder` definitions)
> 2. **Behavioral signal**: at least one of the following:
>    - Demo request submitted
>    - Pricing page viewed in last 7 days + at least 1 other intent action
>    - Trial / freemium signup with valid work email
>    - 3+ content downloads in last 30 days from ICP-matched company
>    - Booked meeting via inbound calendar link

Notice the AND. Firmographic alone (lead from a Tier 1 company who downloaded a generic ebook) isn't an MQL. Behavioral alone (someone outside ICP who requested a demo) isn't either. Both required.

Sub-tiers within MQL:

- **MQL-A:** ICP Tier 1 + high-intent action (demo request, pricing visit + signup) → SDR action within 5 minutes
- **MQL-B:** ICP Tier 1-2 + medium-intent action → SDR action within 1 hour
- **MQL-C:** ICP Tier 2-3 + low-intent action → SDR action within 24 hours OR nurture flow

### 2. SQL definition (the contract acceptance)

SQL = Sales-Qualified Lead. The handoff event. Once a lead hits SQL, it's owned by Sales, Marketing stops nurturing, the lead is in pipeline.

Standard SQL criteria (must all be true):

- MQL conditions met
- Sales has had a real conversation (call or substantive email exchange)
- Initial pain or use case identified
- Decision authority or path to it confirmed (rep can name the persona who'd evaluate)
- Timeline indication (now / next quarter / future / unclear-but-real)
- Not disqualified for any reason (geography, stage, vertical, competitor lockout)

SQL is a Sales-side judgment, not an automated event. The SDR or AE marks the lead SQL after the qualification call. If the lead doesn't qualify, it gets marked Disqualified with a reason, and either returned to Marketing nurture or fully suppressed.

### 3. Lead scoring rubric

Lead scoring is the engine that determines MQL tier and routing priority. Don't use the CRM's default scoring, build a real one from your ICP and behavioral data.

Sample lead score components:

| Component                                              | Weight | Source                             |
| ------------------------------------------------------ | ------ | ---------------------------------- |
| ICP firmographic match (Tier 1 / 2 / 3 / disqualified) | 30     | Enrichment data + ICP rules        |
| Tech stack signal (presence of trigger tools)          | 20     | BuiltWith, Wappalyzer, HG Insights |
| Intent action history (demo, pricing, trial, etc.)     | 25     | Behavioral data                    |
| Engagement velocity (actions in last 7-30 days)        | 15     | Marketing automation tool          |
| Persona match (title patterns within ICP)              | 10     | Form data + enrichment             |

Disqualifiers (any one zeros the score):

- Outside geography you serve
- Pre-seed company (can't pay)
- Currently a competitor's customer (per CRM check)
- Personal email domain (gmail.com, etc.), likely consumer or unserious
- Test / spam submission patterns (random characters, "test test", etc.)

Score ranges:

- 75+ = MQL-A
- 50-74 = MQL-B
- 30-49 = MQL-C
- <30 = nurture or disqualify

Recalculate scores in real-time as new behavioral data arrives. A lead that submitted a content form last week and then visited the pricing page today should re-score in minutes, not on a daily batch.

### 4. Routing rules

Once a lead hits MQL, where does it go? Three common patterns:

**Round-robin.** Leads distributed equally to AE / SDR pool. Simplest. Works for early-stage when territories aren't defined.

**Territory-based.** Leads route by geography, vertical, or company size to the rep who owns that segment. Standard for scaled teams.

**Skill-based.** High-priority MQL-A goes to top performers; MQL-B/C go to broader pool. Optimizes win rate but creates rep-equity issues.

**Hybrid.** Most B2B SaaS at scale: territory + skill priority routing. Geographic + segment ownership for territory; MQL-A within territory routes to top rep.

Routing rules require:

- Owner assignment in CRM (who's the lead's rep)
- Reassignment rules (rep PTO, churn, capacity)
- SLA enforcement (if rep doesn't act in time, lead reroutes)
- Round-robin balance (no single rep gets all the easy leads)

### 5. SLA (Service-Level Agreement)

This is where most companies fail. The SLA is the time within which Sales must take an action on an MQL before it's flagged as a miss.

Industry data:

| Response time | Expected conversion lift        |
| ------------- | ------------------------------- |
| ≤5 minutes    | 100% (baseline, best in class) |
| 5-15 minutes  | 60-70% of baseline              |
| 15-60 minutes | 40-50% of baseline              |
| 1-24 hours    | 15-25% of baseline              |
| 24+ hours     | <10% of baseline                |

The 5-minute SLA matters because intent decays. A prospect who requests a demo at 2:47 PM is in research mode RIGHT NOW. By tomorrow morning, they've moved on, gotten distracted, started looking at a competitor, or forgotten why they wanted the demo.

Standard SLAs by tier:

| MQL tier | Response SLA               | Action expected                      |
| -------- | -------------------------- | ------------------------------------ |
| MQL-A    | 5 minutes (business hours) | Phone call AND email                 |
| MQL-B    | 1 hour                     | Phone call OR email + scheduled call |
| MQL-C    | 24 hours                   | Email + sequence enrollment          |

Business hours definition matters. If you're targeting US prospects, business hours = 8 AM - 6 PM in the prospect's time zone. Not the rep's. A New York lead submitted at 4 PM Pacific should still get a 5-minute response.

After-hours SLA: best practice is a 30-minute auto-response email acknowledging the request + first business-hours response within the SLA. Some companies staff coverage shifts; most accept that a 5-minute response off-hours isn't realistic.

### 6. Disqualification at handoff

Not every lead should become an SQL. Real SDR/AE qualification disqualifies aggressively.

Disqualification reasons (capture in CRM):

- **Out of ICP**, wrong segment, wrong size, wrong vertical
- **Competitor in seat**, already buying a comparable product, deep contract, no displacement opportunity in 12+ months
- **Wrong persona**, submitted form was an intern, student, or non-buyer
- **No real intent**, researching, not buying; "just curious"; building a lookalike at home
- **Geography out of scope**, region you don't serve
- **Pricing out of range**, they want enterprise features at SMB pricing
- **Bad data**, fake submission, test, malformed contact info

Disqualified leads don't disappear. They route back to Marketing for nurture (if reason is "not now") or get suppressed entirely (if reason is "never"). Marketing uses the disqualification reasons as input to lead-source quality scoring.

### 7. Marketing ↔ Sales feedback loop

The handoff doesn't end at SQL. The system needs a feedback loop where Sales tells Marketing which sources / campaigns produce real deals.

Weekly:

- Sales reports: SQL conversion rate by lead source / campaign
- Marketing reports: MQL volume + cost-per-MQL by source
- Together: cost-per-SQL, cost-per-Closed-Won by source

Monthly review topics:

- Which lead sources are producing high-converting MQLs? (Double down)
- Which sources are producing junk? (Cut spend or refine targeting)
- Which campaigns are producing the highest-LTV customers? (Invest)
- Where are MQLs disqualifying, and why?

The disqualification reasons go directly into Marketing's targeting refinement. If 40% of MQL-Cs from a specific paid channel are disqualifying for "out of ICP," that channel is targeting wrong. Fix it or kill it.

### 8. Common gaps (where leads die)

Specific failure points the system has to close:

- **Lead submitted, no email confirmation.** Prospect doesn't know it was received. Build instant auto-confirm + add to CRM in <60 seconds.
- **Lead routed to rep on PTO.** Falls into void. Build absence rules, out-of-office reps' leads auto-reroute.
- **Rep doesn't accept the lead in CRM.** "Pending" status forever. Build acceptance SLA (rep must claim in CRM within 30 min).
- **Rep contacts once, prospect doesn't respond, lead dies.** Build 5-touch SDR sequence (similar to outbound but faster cadence), phone call + email + LinkedIn touch + 2 follow-ups across 7-10 days before disqualifying.
- **Rep marks SQL but never enters next steps.** Build CRM enforcement: SQL transition requires next-step + dated follow-up.
- **Marketing changes definition without telling Sales.** Both teams co-own the MQL/SQL definitions. Changes require both signing off, ideally in monthly review.
- **Disqualifications go uncaptured.** Mandatory disqualification reason field on every lead that's marked Disqualified. No skip option.

---

## The process when triggered

When the user says "fix our handoff" (or any trigger), run this:

### Step 1: Audit current state

Ask:

1. **Do you have a documented MQL definition?** (If yes, what is it? If no, that's the issue.)
2. **What's your current response-time SLA?** (Most don't have one explicitly.)
3. **What's your current MQL → SQL conversion rate?** (Industry benchmark: 30-50% for healthy systems.)
4. **What's your current SQL → Closed-Won conversion rate?** (Healthy: 15-25% on inbound.)
5. **How are leads routed today?**
6. **Where do you suspect leads are dying?** (Sales blames marketing, vice versa, both usually have evidence.)

### Step 2: Define MQL with firmographic + behavioral AND

Map to ICP from `icp-builder`. Add behavioral criteria. Sub-tier into A/B/C based on intent strength.

### Step 3: Define SQL with explicit acceptance criteria

Required pre-conditions for handoff acceptance: MQL conditions + real conversation + pain identified + decision path + timeline + not disqualified.

### Step 4: Build the lead scoring rubric

Component weights, disqualifier rules, score thresholds for tier mapping. Calculate in real-time, not batch.

### Step 5: Set routing rules

Pick routing model (round-robin / territory / skill / hybrid). Configure CRM. Set reassignment rules.

### Step 6: Set SLAs

5-min for MQL-A, 1-hour for MQL-B, 24-hour for MQL-C. Define business hours. Decide after-hours policy.

### Step 7: Build disqualification flow

Disqualification reason field on every lead. Routing of disqualified leads back to Marketing or to suppression.

### Step 8: Build the feedback loop

Weekly + monthly reporting. Cost-per-SQL by source. Disqualification analysis feeding source targeting.

### Step 9: Stress-test

Three checks:

1. **Time-to-first-touch test**, submit a test MQL-A lead. How long until a rep contacts it? If >5 minutes, the SLA isn't enforced.
2. **Disqualification capture test**, pull last 30 days of leads marked Disqualified. Do they all have a reason? If reasons are blank or 80% "Other," the data is dead.
3. **Source-quality test**, can you produce a chart of cost-per-Closed-Won by lead source? If not, the feedback loop isn't running.

---

## The artifact (template)

```markdown
# MQL → SQL Handoff System, [Team], [Year]

## MQL definition

**MQL = Firmographic AND Behavioral**

- **Firmographic:** ICP Tier 1, 2, or 3 (per `icp-builder` definitions)
- **Behavioral signals (any one):**
  - Demo request submitted
  - Pricing page viewed last 7d + 1 other intent action
  - Trial / freemium signup with work email
  - 3+ content downloads last 30d from ICP-matched company
  - Inbound meeting booked

**Sub-tiers:**

- MQL-A: ICP Tier 1 + high-intent → 5-min SLA
- MQL-B: ICP Tier 1-2 + medium-intent → 1-hour SLA
- MQL-C: ICP Tier 2-3 + low-intent → 24-hour SLA OR nurture

## SQL definition

SQL = MQL conditions + real conversation + pain identified + decision authority confirmed + timeline indicated + not disqualified.

SQL is a Sales-side judgment, not an automated event.

## Lead scoring rubric

| Component              | Weight |
| ---------------------- | ------ |
| ICP firmographic match | 30     |
| Tech stack signal      | 20     |
| Intent action history  | 25     |
| Engagement velocity    | 15     |
| Persona match          | 10     |

**Disqualifiers (zeroes the score):**

- Out of geography
- Pre-seed company
- Competitor's customer
- Personal email domain
- Spam / test submission

**Tiers:**

- 75+ = MQL-A
- 50-74 = MQL-B
- 30-49 = MQL-C
- <30 = nurture or disqualify

## Routing rules

**Model:** [Round-robin / Territory / Skill / Hybrid]
**Owner assignment:** [logic]
**Reassignment:** [PTO, churn, capacity rules]
**Round-robin balance:** [equity rules]

## SLA

| Tier  | Response time (business hours) | Action                          |
| ----- | ------------------------------ | ------------------------------- |
| MQL-A | 5 minutes                      | Phone call AND email            |
| MQL-B | 1 hour                         | Phone call OR email + scheduled |
| MQL-C | 24 hours                       | Email + sequence enrollment     |

**Business hours:** [definition]
**After-hours policy:** [auto-response + next-business-day SLA]

## Disqualification flow

Required reason field. Reasons:

- Out of ICP
- Competitor in seat
- Wrong persona
- No real intent
- Geography out of scope
- Pricing out of range
- Bad data
- Other (note required)

Routing of disqualified leads:

- "Not now" reasons → back to Marketing nurture
- "Never" reasons → fully suppressed

## Marketing ↔ Sales feedback loop

**Weekly:**

- Sales: SQL conversion rate by source / campaign
- Marketing: MQL volume + CPL by source
- Together: cost-per-SQL, cost-per-Closed-Won

**Monthly review:**

- Top-converting sources (double down)
- Junk sources (cut or refine)
- Highest-LTV campaigns (invest)
- Disqualification analysis (targeting refinement)

## Gap-closure rules

- Auto-confirm submission < 60 sec
- Out-of-office reps reroute
- Acceptance SLA (rep claims in CRM ≤ 30 min)
- 5-touch SDR sequence on no-response
- SQL transition requires next-step + date
- MQL/SQL definition changes require both teams' sign-off

## Dashboards

- Time-to-first-touch (per rep, per tier)
- MQL → SQL conversion (per source, per rep)
- SQL → Closed-Won conversion (per source)
- Cost-per-MQL, cost-per-SQL, cost-per-CW by source
- Disqualification reason distribution
```

---

## Common mistakes

Push back on these:

- **Points-based MQL with no firmographic check.** A 100-point lead from outside ICP is not an MQL. Both criteria required.
- **No SLA, or SLA without enforcement.** "Best effort" response time = no response time. Build dashboards, hold reps accountable.
- **24-hour SLA on MQL-A.** Intent decays in hours. 5 minutes on high-intent or you're losing 60-90% of conversion potential.
- **Disqualification without reasons.** Leads go away with no learning. Mandatory picklist.
- **Marketing changes lead source mix without telling Sales.** Sales pipeline shifts overnight, qualification rate craters, no one knows why. Co-own the funnel.
- **No round-robin balance.** Top reps get the easy leads, junior reps get scraps. Equity erodes, attrition rises.
- **No after-hours policy.** Lead submitted at 7 PM, rep responds Tuesday morning, prospect bought from competitor over the weekend.
- **Lead routed to rep on PTO.** Lead dies. Out-of-office reroute mandatory.
- **SLA only on MQL-A.** Lower-tier leads die in inbox forever. Tier each level with appropriate time budget.
- **No feedback loop.** Sales complains "marketing's leads suck" forever. Without source-quality data, the complaint is unfixable.
- **MQL definition by Marketing alone.** Sales doesn't accept it, doesn't follow up. Co-own.
- **Lead suppression by accident.** Disqualified leads never re-enter pipeline even when conditions change. Build an "if X happens, re-evaluate" trigger.

---

## How to use the artifact downstream

After the system is live:

1. **Configure CRM and marketing automation**, score logic, routing rules, SLA dashboards, disqualification picklists
2. **Train SDR / AE team**, what counts as MQL/SQL, how to disqualify, what reasons to use
3. **Train Marketing team**, what the source-quality data shows, how it changes targeting
4. **Build dashboards**, time-to-first-touch, MQL→SQL conversion, cost-per-CW by source
5. **Weekly review**, both teams together, source-level reporting
6. **Monthly retrospective**, system tuning based on accumulated data
7. **Cross-reference ICP** (`icp-builder`), firmographic match comes directly from ICP definition
8. **Cross-reference comp** (`comp-plan-designer`), SDR/AE comp on inbound depends on what counts as a qualified meeting
9. **Cross-reference forecasting** (`forecasting-and-pipeline-review`), SQL is the entry point to pipeline, sets stage expectations

---

**The handoff is the contract. Define what counts, route fast, respond faster, disqualify honestly, feed the data back to Marketing. Both teams optimize the joint funnel, or both teams lose deals together.**

---

_Part of the StackSwap Operator Playbook. → stackswap.ai/playbook_

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