sales-marketing-sla — independently scanned and version-tracked by SaferSkills.
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This skill builds the operational agreement between marketing and sales around lead quality and follow-up. The marketing-to-sales handoff is the most common source of revenue leakage in B2B SaaS. Marketing generates leads that sales does not work. Sales blames marketing for bad lead quality. Marketing blames sales for ignoring good leads. Both sides have data that supports their position. Neither side has a shared definition of what a good lead actually is.
The problem is almost never lead quality or sales effort in isolation. It is the absence of a written, agreed-upon, and measured definition of what marketing is responsible for delivering and what sales is responsible for doing with it. This skill builds that definition.
This skill works out of the box. For more specific output, provide:
sales works within the expected timeframe
Most MQL definitions fail for one of three reasons.
Reason 1: The definition was built by marketing without sales input.
Marketing defined an MQL based on what data they could track: a form fill, a content download, a demo request. Sales was told about the definition after it was built. Sales never agreed to it, never believed in it, and never prioritized MQLs that came from that definition.
Reason 2: The definition is based on activity, not fit.
An MQL defined as "any contact who downloads a whitepaper" captures students, competitors, and consultants doing research. It does not filter for the companies that can actually buy. Activity-based MQL definitions produce high volumes of low-quality leads and erode sales confidence in the MQL program entirely.
Reason 3: There is no enforcement mechanism.
A written MQL definition that lives in a slide deck and is not enforced by the CRM is not a definition. It is a suggestion. Without automatic lifecycle stage transitions, lead routing workflows, and SLA tracking in the CRM, the definition is aspirational rather than operational.
A good MQL definition has two components: firmographic fit and behavioral signal. Both must be present. Either alone is insufficient.
This defines the type of company that can buy. It should map directly to the ICP and should be specific enough to exclude companies that will waste sales time.
Questions to answer with sales input:
What company size range has the highest close rate historically? What verticals are in scope for this year's sales plan? Are there geographies or company stages that are explicitly out of scope? What job titles or seniority levels indicate a real buyer versus a researcher?
The output is a set of hard filters:
A contact is not an MQL unless the company meets: company size between X and Y employees, industry in [specific verticals], geography in scope, and the contact holds a title that indicates purchase authority or meaningful influence on the buying decision.
These filters should be applied automatically in the CRM. If a form submission comes in from a company with 10 employees and the target is 50-500, it should not become an MQL. It should become a lead that goes into a nurture sequence, not a sales queue.
This defines what the contact has done to indicate they are actively evaluating a solution. Firmographic fit without behavioral signal means a company that could buy but has not shown interest. Behavioral signal without firmographic fit means interest from someone who cannot buy.
Signal tiers by strength:
High-intent signals (auto-qualify if fit criteria met): Demo request or free trial signup. Pricing page visit combined with two or more additional page views in the same session. Repeated website visits from the same contact within a 14-day window. Direct inbound contact via phone or chat requesting information.
Medium-intent signals (qualify if combined with additional engagement): Content download combined with email open and click within 7 days. Webinar attendance with post-webinar follow-up link click. Case study or ROI calculator engagement.
Low-intent signals (nurture, do not route to sales): Single content download with no follow-up engagement. Newsletter subscription. Conference badge scan with no follow-up digital engagement.
The scoring model:
Assign point values to each signal based on observed correlation with pipeline creation. High-intent signals should be weighted heavily. Low-intent signals should be weighted minimally or excluded from MQL scoring entirely.
Set a threshold score. Contacts who exceed the threshold and meet the firmographic fit criteria become MQLs and route to sales. Contacts who meet firmographic fit but are below the threshold stay in nurture. Contacts who exceed the threshold but do not meet firmographic fit stay in nurture with a different track.
An important caution on scoring models:
Do not make the scoring model so complex that it cannot be explained in two sentences. If a sales rep asks "why did I get this lead?" and the answer requires a spreadsheet, the model is too complex. Sales needs to trust the model, and trust requires transparency.
The SLA is what sales commits to doing with every MQL. Without a defined SLA, marketing has no basis for accountability when leads are not worked, and sales has no agreed-upon expectation to hold themselves to.
The four elements of a functional SLA:
Response time: How many business hours from MQL routing to first sales contact attempt? Industry standard for high-intent leads is under 4 hours for demo requests, under 24 hours for other high-intent signals. Set the commitment based on what sales can actually deliver, not what the ideal would be. A SLA that is violated 80% of the time is worse than no SLA, because it establishes that the agreement does not matter.
Contact attempts: How many outreach attempts is sales required to make before a lead is marked as "worked and unresponsive"? Minimum recommendation is five attempts across at least two channels (phone and email) over a seven to ten business day window. A lead marked as "no response" after one call is not a worked lead.
Disposition requirement: After working a lead, what dispositions are available? Common options: converted to opportunity, disqualified with a specific reason (budget, timing, not a fit, wrong contact), or unable to reach after required attempts. The "unable to reach" disposition should trigger a marketing re-engagement sequence, not a permanent archive.
Feedback loop: When sales disqualifies a lead, they must provide a specific reason. "Not interested" is not a specific reason. "Company is too small, under 50 employees" is a specific reason that marketing can use to tighten the MQL definition. The feedback loop is how the MQL definition improves over time.
This is where most SLA initiatives fail. Marketing builds the definition, presents it to sales, and is surprised when sales does not adopt it.
The right process:
Do not present a finished MQL definition to sales. Facilitate the conversation that produces the definition together. Run a session with the sales leader and two or three reps. Start with the question: "Tell me about the last three marketing leads that converted to pipeline. What was different about those leads compared to the ones that went nowhere?"
The answers to that question, collected from sales, become the foundation of the MQL definition. When sales helped build it, they own it. When marketing built it and handed it to them, they tolerate it at best.
The minimum viable agreement:
If the full MQL definition process is too slow or politically complex to complete, start with the minimum viable agreement: a written list of the three things that disqualify a lead from ever being routed to sales. Get sales to agree to those three disqualifiers in writing. That is the floor. Everything else is refinement.
The SLA is only operational when it is enforced by the CRM. Everything else is a policy document that depends on individual compliance.
Required CRM configuration:
Automatic lifecycle stage transitions: When a contact meets both firmographic fit and behavioral signal threshold, the lifecycle stage should automatically update to MQL without manual intervention. If a rep has to manually change a lifecycle stage for a lead to be counted, the data will be incomplete.
Automatic lead routing: When a contact becomes an MQL, the CRM should automatically assign it to the correct owner based on territory, company size, or vertical. Do not rely on a daily manual review of the MQL queue.
SLA timer: Track the time between MQL creation and first sales activity. This can be done with a custom date field in HubSpot or a workflow that stamps a "first activity date" and calculates the gap. Without this measurement, you cannot report on SLA compliance.
Disposition tracking: Create a required field that sales must complete before moving a lead out of the MQL stage. No lead should be able to move to "disqualified" or "no response" without a reason selected.
SLA reporting requirements:
Build a weekly report that shows: MQL volume by source, MQL to SQL conversion rate, median time to first sales contact, disposition breakdown for disqualified MQLs, and the number of MQLs aged more than 72 hours without a sales contact attempt.
This report should go to both the marketing leader and the sales leader at the same time. It is a shared accountability document, not a marketing report card.
Output in this format:
SALES-MARKETING SLA DESIGN
[Company or team name if provided]
Built: [today's date]
CURRENT STATE ASSESSMENT
[What the existing handoff process looks like based on what the user
described. Where the friction points are. Whether this is a definition
problem, an enforcement problem, or a trust problem.]
MQL DEFINITION
Firmographic fit criteria (required, applied automatically):
- Company size: [range]
- Industries in scope: [list]
- Geographies in scope: [list]
- Qualifying titles: [list]
- Disqualifiers (immediate exclusions): [list]
Behavioral signal scoring:
- High-intent signals [point value each]: [list]
- Medium-intent signals [point value each]: [list]
- Low-intent signals [do not score or minimal weight]: [list]
- MQL threshold score: [number]
- Score + fit = MQL: [confirm logic]
SALES SLA
Response time commitment: [hours for each signal tier]
Contact attempt requirement: [number, channels, timeframe]
Required dispositions: [list with definitions]
Feedback requirement: [what sales must provide when disqualifying]
CRM CONFIGURATION REQUIRED
1. [Specific workflow or field to configure]
2. [Specific workflow or field to configure]
3. [Specific workflow or field to configure]
[Continue as needed]
SLA REPORTING DASHBOARD
Weekly metrics: [specific metrics with data source]
Who receives it: [both marketing and sales leadership]
Review cadence: [recommended meeting cadence to review together]
GETTING SALES BUY-IN
Session structure: [how to run the definition session with sales]
Minimum viable agreement: [what to get signed off on if full process stalls]
Who needs to be in the room: [required attendees and why]
RISKS
[The two or three most likely reasons this SLA will be built but not
adopted. Based on what the user has described.]specific to the company's ICP, deal size, and sales motion as described by the user.
building the definition. A definition without ICP context is a template, not an SLA.
trust failures, not technical failures. Acknowledge that and address the process for getting genuine sales buy-in, not just sales compliance.
explained in two sentences. Complexity destroys adoption.
A sales leader can agree to an SLA in a meeting and reps can still ignore it. The CRM enforcement configuration is what closes that gap. Make sure the output includes specific workflows that require rep action rather than allowing leads to age passively.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.