# MQL-to-SQL Handoff — Standard Operating Procedure

> Source: https://b2bprocess.com/mql-to-sql-handoff
> Last updated: 2026-07-08. Adapt owners, tools, and thresholds to your organization.

## 1. Purpose

The MQL-to-SQL handoff is the process governing how leads qualified by marketing (MQLs) are delivered to, accepted by, and worked by sales until they either convert into sales-qualified opportunities (SQLs) or are returned with a reason. It comprises the definitions both teams have agreed to, the routing and notification mechanics, the follow-up SLA, the acceptance/rejection protocol, and the feedback loop that recycles rejected leads and recalibrates qualification upstream.

## 2. Scope & prerequisites

Needed wherever marketing generates leads that a separate sales function works — from the first SDR hire onward. Prerequisites: a lead scoring or qualification model producing the MQL signal, routing that assigns an owner, and CRM stages that distinguish MQL, accepted/working, SQL, and recycled.

## 3. Roles & responsibilities

| Role | Responsibility |
| --- | --- |
| Marketing Operations | MQL production quality: scoring, context delivery, recycle paths, nurture. |
| SDR / BDR | Works MQLs to the agreed standard within SLA; dispositions honestly with reasons. |
| Sales leadership | Enforces the working standard and SLA; co-owns definitions and calibration. |
| Marketing leadership | Co-owns definitions; accountable for MQL quality and source mix, not just volume. |
| Revenue Operations | Neutral referee: routing, SLA instrumentation, funnel reporting, definition governance. |

## 4. Procedure

### Step 1: Agree the definitions in one document

**Owner:** Marketing + Sales leadership (RevOps facilitates)

Define MQL (the qualification bar and scoring threshold), SAL (what acceptance means and how fast it must happen), and SQL (the criteria a real opportunity meets — e.g., need, authority, timeline confirmed). Write them with entry/exit criteria, examples, and edge cases; both leaders sign; RevOps publishes it as the single source of truth.

- [ ] Define each stage with objective criteria and required fields
- [ ] Enumerate edge cases: existing customers, open opps, partner leads, event badge scans
- [ ] Version the document; changes require both signatures

### Step 2: Deliver leads with context, not just a name

**Owner:** Marketing Operations

Every MQL arrives with why it qualified: score and score reasons, source and campaign, key behaviors (pages, content, event attended), firmographics, and suggested talking point. A lead without context gets a generic first touch, which converts worse and teaches sales the leads are low-effort.

- [ ] Surface score reasons and behavior history on the CRM record and in the notification
- [ ] Include campaign context so the rep's outreach can reference it
- [ ] Flag high-intent signals (pricing page, demo request) distinctly

### Step 3: Route instantly with a two-sided SLA

**Owner:** Revenue Operations

MQLs route to an owner in minutes (see lead routing) with an SLA clock: sales must make first touch within the agreed window (commonly 1 business hour for high-intent, same-day otherwise) and must disposition — accept or reject — within the agreed period (commonly 24–48 hours). SLA breaches re-route automatically and are reported.

### Step 4: Enforce disposition with reasons

**Owner:** Sales (SDR/AE); RevOps enforces

No silent graveyard: every MQL ends in an explicit state — accepted and working, converted to opportunity, or rejected with a structured reason (bad fit, no response after N attempts, timing, bad data, duplicate). Rejection reasons are picklist values, not free text, so they aggregate into fixable patterns.

- [ ] Make disposition a required field to exit the MQL stage
- [ ] Keep the rejection taxonomy short (5–8 reasons) and mutually agreed
- [ ] Auto-flag leads sitting undispositioned past SLA

### Step 5: Define the working standard before rejection

**Owner:** Sales leadership

Agree what 'worked' means: e.g., minimum 4–6 touches across two channels over 10 business days before a no-response rejection is valid. This is the sales side of the contract — marketing commits to quality, sales commits to effort — and it's auditable from activity data.

### Step 6: Recycle rejected leads deliberately

**Owner:** Marketing Operations

Rejected ≠ deleted. Timing rejections enter nurture with a re-qualification trigger; bad-data rejections get re-enriched; no-response leads get a different channel or later wave; bad-fit rejections feed back into scoring weights and targeting. The recycle path is where MQL economics quietly double.

### Step 7: Hold the joint funnel review

**Owner:** Marketing + Sales leadership (RevOps presents)

Bi-weekly or monthly: both teams, one dataset. MQL volume and quality by source, acceptance rate, SLA attainment on both sides, rejection reasons, MQL→SQL→won conversion, and the arguments those numbers settle. Definitions get recalibrated here — threshold changes, scoring adjustments — by agreement, with a changelog.

- [ ] Review acceptance rate and rejection reasons by source/campaign
- [ ] Audit a sample of rejections for working-standard compliance
- [ ] Agree calibration changes and log them

### Step 8: Close the loop to revenue

**Owner:** Revenue Operations

Report the full chain — source → MQL → SAL → SQL → won — cohorted by month and segment, so marketing optimizes toward pipeline and revenue rather than MQL counts, and sales sees which sources deserve fastest response. This reporting is what eventually retires vanity-MQL incentives on both sides.

## 5. Metrics to monitor

| Metric | Definition | Formula | Target |
| --- | --- | --- | --- |
| MQL acceptance rate (SAL rate) | Share of MQLs sales actively accepts — the headline health metric of the handoff. | Accepted MQLs ÷ delivered MQLs | > 80% |
| MQL-to-SQL conversion | Share of MQLs becoming sales-qualified opportunities. | SQLs ÷ MQLs (cohorted) | 10–25%, motion-dependent |
| Speed to first touch | Time from MQL creation to first sales activity. | First-touch timestamp − MQL timestamp (median, p90) | < 1 hr high-intent; same-day otherwise |
| Disposition SLA attainment | MQLs accepted/rejected within the agreed window. | Dispositioned in SLA ÷ delivered MQLs | > 90% |
| Working-standard compliance | Rejected-for-no-response leads that actually received the agreed touch pattern. | Compliant rejections ÷ audited no-response rejections | > 90% |
| Recycled-lead conversion | Share of recycled MQLs that later become SQLs — the measure of the recycle path's value. | SQLs from recycled leads ÷ recycled leads | track and grow; often 5–15% |

## 6. Known failure modes

| Failure | Symptom | Corrective action |
| --- | --- | --- |
| Definitions by assumption | Marketing's MQL is sales' junk mail; every funnel meeting is a definition fight. | One signed document with objective criteria; RevOps as custodian; changes only by joint agreement. |
| The silent graveyard | MQLs neither worked nor rejected; funnel reports show a stage where leads simply vanish. | Mandatory disposition with reasons, SLA timers, auto-escalation, and public attainment reporting. |
| Volume-comped marketing | MQL targets hit every quarter while acceptance rate slides; sales builds a shadow funnel. | Shift marketing's north star to accepted MQLs, SQLs, and sourced pipeline; report cohorted source→revenue. |
| Cherry-picking sales | Reps work referrals and demo requests, reject everything else 'no response' after one call. | Auditable working standard before rejection; compliance sampling in the joint review; comp SDRs on SQLs, not selective activity. |
| Leads delivered naked | Reps open records with a name and an email; first touches are generic; conversion underperforms the same leads with context. | Score reasons, behaviors, and campaign context on every record and notification. |
| Rejected means deleted | Timing and data rejections evaporate; the same buyer re-enters cold six months later. | Reason-specific recycle paths with re-qualification triggers; measure recycled-lead conversion. |
| No neutral referee | Reporting lives in marketing's tool or sales' tool; each side distrusts the other's numbers. | RevOps owns the instrumentation and presents one dataset both leaders receive simultaneously. |

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