Marketing and Sales SLA Template: Stage Definitions, Response Times and Handoff Rules

A marketing and sales service level agreement (SLA) template has four parts: stage definitions both teams sign, response times, handoff and rejection rules, and commitments with a review date. Marketing commits to a number of marketing qualified leads (MQLs) worked back from revenue. Sales commits to contact each one within 24 hours, or 4 hours for demo requests. Rejections come back within 48 hours, and both teams review the document quarterly.

What is a marketing and sales SLA and what goes in it

A marketing and sales service level agreement (SLA) is a written, two-way deal between the two teams. In HubSpot's framing, "Marketing promises a certain number of leads to sales, and sales promises to contact those leads within a certain timeframe." One side owns volume and quality. The other owns speed and follow-through.

The simplest version fits in one sentence. HubSpot's example reads: "Every month, marketing will deliver 1000 qualified leads to sales and sales will contact each of those leads within 24 hours of receiving it."

Where the volume number comes from

The lead commitment comes from the revenue target, worked backward. HubSpot's sales team used a per-rep figure: "Each of them needs a hundred marketing qualified leads each month, so you need to deliver a thousand leads per month for that team", across 10 salespeople. The arithmetic is 100 leads × 10 reps = 1,000 marketing qualified leads (MQLs) a month. To build your own version from conversion rates and deal size, the reverse funnel calculator runs the same math.

The four parts this template uses

We group the agreement into four parts (our method).

The Pedowitz Group puts the response-time standard plainly: "24 hours is the standard for B2B; 4 hours for high-intent actions like demo requests". It also sets a deadline for sales to send a lead back: "the timeframe for rejection (within 48 hours of assignment)".

How you know it is working

Compliance is measured, not assumed. The same source lists three checks to "Track three metrics in your CRM: average follow-up time on MQLs, MQL rejection rate and reason breakdown, and percentage of MQLs not touched within the agreed timeframe."

We think the four parts only hold if both numbers sit side by side on one page. A lead commitment with no response time puts all the accountability on marketing. A response time with no lead definition lets either team argue about what arrived.

Which stage definitions should both teams sign

Use the stage names your customer relationship management (CRM) system already stores, so the agreement and the reports describe the same thing. The definitions follow HubSpot's documentation: a Marketing Qualified Lead is "a contact or company that your marketing team has qualified as ready for the sales team," and a Sales Qualified Lead is one "that your sales team has qualified as a potential customer."

The Sales Qualified Lead row is where the two teams most need the same words. Sybill puts it this way: "The marketing-to-sales handoff lives at this transition, which is why both teams agree on definitions in writing."

Lead status values for the sales side

Inside the Sales Qualified Lead stage, HubSpot stores sub-stages in a separate Lead Status property. In the SLA, we map them like this:

• New: assigned, response clock running.
• Attempted to Contact: first touch logged, which meets the response-time promise.
• Connected or In Progress: the rep is working the record.
• Unqualified or Bad Timing: rejected, with a reason that goes back to marketing.

HubSpot's documentation gives one way to enforce the follow-up: a workflow that creates a task for the contact owner when the contact's Date entered Sales Qualified Lead is more than 5 days ago. Set that window to match whatever response time your agreement states.

The forward-only rule

Automatic updates only move a record forward. HubSpot states that default automatic updates will only move the stage forward. It also notes that you must clear the value manually or via a workflow before you can set an earlier stage.

This affects recycling. A Marketing Qualified Lead that sales rejects stays at that stage unless someone clears it. Name an owner for that workflow in the SLA. Note that Super Admin permissions are required to create or edit the stages themselves, so the stage list sits with one admin and both teams sign off on any change to it.

How to write an MQL definition sales will accept

An MQL definition gets accepted when a sales rep can test any single lead against it and reach the same answer marketing reached. The Pedowitz Group lists four parts: firmographic criteria, behavioral criteria, a scoring threshold and explicit disqualifiers. Its example of a usable definition reads: "A contact at a company with 500+ employees in financial services who has requested a demo or downloaded two or more bottom-of-funnel assets and has a lead score above 85."

The same guide says to write the criteria in a table with specific values and have both vice presidents sign off "on the specific criteria, not the concept of criteria."

Start from the target account list

Firmographic rows should come from planning work both teams already did. Forrester defines targeted accounts as "the set of accounts that should contain one or more targeted opportunities." It says joint targeting should happen during each annual planning cycle. Its account fit step uses ideal customer profile (ICP) criteria specific to the product, such as the number of hospital beds for a healthcare target.

In our reading, the MQL's firmographic rows should be copied from that list. A lead outside the list then cannot become an MQL on behavior alone.

Fill-in table

The disqualifier row borrows from the rejection reasons the Pedowitz Group lists: wrong persona, no budget, competitor in evaluation, already a customer. We think reasons that marketing can detect before handoff belong in the definition as disqualifiers. Budget and competitor status usually surface only in conversation, so leave those as rejection reasons.

Sign-off sequence

1. Operations pulls the firmographic and ICP values from the target account list.
2. Marketing proposes the behavioral rows and the threshold.
3. Sales tests the draft against a sample of recent leads and flags any it would reject.
4. Both vice presidents sign the values in the table, not a summary.

Skipping step 3 has a cost. As the guide puts it, if sales does not help define the criteria, "they will not respect the resulting leads."

How to calculate marketing's MQL commitment from the pipeline target

The MQL number in the SLA should come from arithmetic both teams can rerun, not from last year's total plus a growth guess. HubSpot's podcast on SLAs names three inputs: the average conversion rate from lead to opportunity, the average conversion rate from opportunity to closed sale, and the average value of a sale. With those, you work backward from revenue to leads.

The formula

MQLs required = revenue target ÷ average deal value ÷ win rate ÷ SQL-to-opportunity rate ÷ MQL-to-SQL rate

Each division undoes one stage of the funnel. If your stages differ from the ones signed earlier in this template, add or remove a divisor for each stage, using your own CRM's trailing conversion rates. The funnel conversion benchmarks are useful for checking your inputs, not for replacing them.

HubSpot's own SLA guide gives a two-step version. A sales team must close $5,000 a month, each sale is worth $100, and the win rate on engaged leads is 50%. That gives 50 deals, divided by 0.5, so marketing commits to 100 qualified leads a month.

A worked example with every input named

These are illustrative figures for a hypothetical quarter. Replace each one with your own.

Marketing's quarterly commitment is 500 MQLs. To check the math in reverse, multiply: 500 × 0.4 × 0.6 × 0.25 × $40,000 returns $1,200,000. The reverse funnel calculator runs the same chain. Pull the win rate from closed opportunities in the same segment, and compare it with win rate benchmarks only as a sanity check.

Weight leads by value when the mix shifts

A flat MQL count invites gaming. In the HubSpot podcast, Mark Roberge described an ebook download from a mid-market vice president that converted to a customer 1% of the time on $100,000 of software, while a demo request converted at 3%. Multiplying gave a lead value: $1,000 per ebook download and $3,000 per demo request. The commitment became a target to generate $300,000 of lead value.

In our reading, a lead value target suits teams whose MQL sources convert at very different rates. Write the per-source values into the SLA so that sales can audit them each quarter.

Worked example from a 60-opportunity quarter to a monthly MQL commitment

Here is the method from the previous section applied to one quarter. The inputs are illustrative. Replace the two conversion rates with your own trailing two quarters of data, and keep the rounding rule: always round up, because a fractional MQL cannot be delivered.

The worked example runs from 60 quarterly opportunities down to a commitment of 53 MQLs a month and 53 follow-up touches per rep.

Worked example: from a 60-opportunity quarter to a monthly MQL commitment

Item	Value
Opportunities (marketing share)	30 count per quarter
SQLs needed	55 count per quarter
MQLs needed	158 count per quarter

Source: Take the Market worked example (illustrative conversion rates)

The arithmetic, line by line

1. Sourced opportunities: 60 × 50% = 30.
2. SQLs (sales qualified leads) needed: 30 ÷ 0.55 = 54.5, rounded up to 55.
3. MQLs needed for the quarter: 55 ÷ 0.35 = 157.1, rounded up to 158.
4. Monthly commitment: 158 ÷ 3 = 52.7, rounded up to 53.
5. Load per rep: 53 ÷ 6 = 8.8 MQLs a month.
6. Follow-up capacity: 8.8 × 6 touches = 52.8, or 53 touches per rep per month.

The written commitment becomes one sentence: marketing delivers 53 MQLs a month that meet the signed definition, and each of the six reps completes six touches on every MQL they receive.

Why the capacity line belongs in the SLA

The first four lines bind marketing. The last three bind sales, and they are the lines most templates leave out. Fifty-three touches a month per rep is a small load. We think the low number is the point: when a rep has fewer than nine new MQLs a month, missed follow-up cannot be blamed on volume.

Write the sales side as checks a report can run. Mark Roberge described a dashboard at HubSpot called the "Don't Be on It Dashboard", where a rep's name appeared whenever a lead wasn't called within 24 hours. A second rule flagged a lead in the cycle for two weeks that wasn't called five times. For our example, the matching rules would be one touch within the agreed response window and six touches within the cadence period. Both can be read straight off activity data.

Swapping in your own rates

Change one input at a time and watch the monthly line. If the MQL to SQL rate drops to 30%, step 3 becomes 55 ÷ 0.30 = 183.3, rounded up to 184. That is 62 MQLs a month, so the commitment rises by 9 for a five-point change in one rate. Run your figures through the reverse funnel calculator, and check your opportunity target against pipeline coverage before either team signs.

How fast should sales follow up on an MQL

The sales half of the service level agreement needs three clauses: a response window by lead type, a number of contact attempts before the lead goes back to marketing, and a written test for "worked." The Pedowitz Group lists all three and gives the usual windows: 24 hours is the standard for B2B; 4 hours for high-intent actions like demo requests.

The case for speed is not new. In March 2011, Harvard Business Review published a study that found most companies were not responding nearly fast enough to online queries.

Response clause template

Attach a consequence to the window. Pedowitz puts it this way: if sales misses the follow-up window, marketing is not held accountable for conversion.

Split processing lag from rep lag

A missed window is not always the rep's fault. LeanData breaks the clock into two parts: Lead Response Time = Lead Processing Time + Representative Response Time. Processing covers enrichment, matching, territory assignment and routing, all before a rep sees the record.

Here is a worked example. A demo request arrives at 9:00. Routing assigns it at 11:30, and the rep calls at 15:00. Total time is 6 hours, so the lead misses the 4-hour window. The rep's share is only 3.5 hours. The other 2.5 hours went to processing. If the SLA measures only the total, the rep takes the blame for a routing delay.

Write both timestamps into the CRM system as separate fields: assignment time and first-touch time. Then the weekly review can tell which half failed.

Report the tail, not just the average

Averages hide the leads that miss the window. LeanData notes that a team with a 6-minute average can still have 20% of leads waiting 45 minutes or longer. Report the median and the 90th percentile next to the average.

Pedowitz adds a compliance metric that maps straight to this clause: the percentage of MQLs not touched within the agreed timeframe. To see how faster first touches change cycle time, run your numbers through the pipeline velocity calculator.

What happens to rejected and recycled leads

A rejection is the moment an MQL leaves sales without becoming an opportunity. The SLA has to say where it goes next. The reciprocal commitments in an SLA include a structured rejection process so that no lead simply disappears. Skipping it has a visible cost: one 2026 playbook reports that more than half of teams have broken handoffs where sales follows up on fewer than 35% of marketing-engaged prospects.

The table below is our template. Copy it into the SLA and require a reason code on every rejection, with no free-text-only option.

Make the CRM do the routing

In our reading, most CRMs resist moving a record backward, so the recycle path needs explicit build work. In HubSpot, the default Lifecycle stage property can only be moved forward by HubSpot tools. You must clear the value manually or via a workflow before using these tools to set an earlier value in the Lifecycle stage order. The recycle workflow should therefore clear the stage, set the nurture status and stamp the reason code in the same step.

Two more settings keep recycled leads visible:

1. Track total time in a stage across repeat visits. HubSpot's cumulative time property is described as helpful if contacts re-enter a stage multiple times and you want to track their total time in the stage.
2. Catch stalled records. For records still sitting in a stage, HubSpot says your trigger criteria should be Lifecycle stage not updated in last x days and Lifecycle stage is any of stage. Set the window to the review period your SLA names.

Treat rejections as definition data

Report rejections by code every month, split by source and by campaign. In our reading, each code points to a different fix. R1 points to form and enrichment problems. R2 and R3 point to scoring that rewards activity before intent.

Bring the counts to the definition review. Neither team edits the definition between reviews because of one bad week.

How to enforce the SLA with routing rules and a weekly review

An SLA holds only when the system routes every lead to a named owner and the two teams look at the same numbers every week. Write the rules into the CRM system first, then run the review.

Routing rules that leave no lead unowned

In Salesforce, only one lead or case assignment rule can be active at a time, so every SLA path has to sit inside that single rule as ordered entries. Build it in this order:

1. Catch junk first. LeanData's example sends leads containing the word "test" to an Unassigned queue, which keeps them out of rep queues and out of your response clock.
2. Route by segment. In the same example, leads from enterprise accounts (>$100M revenue) go to an Account Executive, and demo requests go straight to a sales development representative.
3. Add a fallback owner for every entry, including after hours. LeanData warns that without fallback rules for after-hours inbound, you're creating systematic delay.
4. Force imports through the rule. For event lists, check the box Assign using active assignment rule.
5. Turn on field history tracking so ownership changes leave an audit trail.

This matters because, by LeanData's account, one in four leads is routed incorrectly. A misrouted lead looks like a slow rep in the report.

The weekly review: 30 minutes, same agenda

Marketing operations runs it; one sales manager and one demand generation owner attend. Pull every line from the demand gen dashboard.

End with three decisions written down: what changes in routing, in lead scoring, or in follow-up.

Three traps we see

• Vague definitions. If "engaged" or "worked" has no field value behind it, the review turns into opinion. Tie every term to a CRM field.
• Unrouted leads. Leads that miss every rule entry sit with no owner. The fallback entry and the Unassigned queue line fix this.
• Volume with no quality check. An MQL count alone rewards cheap leads. Keep the SQL rate on the same scorecard.

Where the SLA goes next

Forrester's B2B Revenue Waterfall describes a practical framework for shifting from managing individual leads to identifying, prioritizing, and advancing opportunities with connected buying groups. We think the practical step is to add buying-group coverage on target accounts as a scorecard line next quarter, then rewrite the handoff around accounts. The one-to-few ABM playbook covers that model.

What this page does not cover

This page does not cover account-based handoffs in detail, sales compensation tied to the agreement, or setup steps for CRM systems beyond the HubSpot and Salesforce settings named here. The figures in the worked examples are illustrative, so replace them with your own conversion data. An internal SLA between teams is an operating document, and this page is not legal advice.

Related on Take the Market: Lead Scoring Model Template: Fit and Engagement Scores, Decay, and a Threshold Set from Closed-Won Data; Demand Generation Dashboard Template: 15 Metrics, Formulas, CRM Fields and the Weekly Review; Pipeline coverage calculator: the ratio you need from your own win rate and slippage.