How do I create an SLA when I don’t know conversion rates?

[JonPayne]

Not all of us have access to a complete data set to be able to calculate our conversion rates to set an SLA between marketing and sales. Join the discussion to get advice on how to create your SLA based on industry estimates.

*To learn more about this, check out the Holding Your Teams Accountable With an SLA lesson via HubSpot Academy. 

[JEisen1994]

I enjoyed learning about SLAs.  I was interested in the part that elaborates the connection bewteen sales and marketing.  I also liked the part that mentiones when you have to contact a customer, how soon is subjective.

I have a question regarding the worksheet on creating a sales and market SLA.  Are we provided sales data to enter into the worksheet, or do we make up our own data? 

[ISingh48]

I don't always have complete data, so I estimate conversion rates using industry benchmarks and small sample data, then refine the SLA as more real data becomes available.

[KHassan5]

I find ensuring you have CRM and/or analytics access (which correctly tracks all lead engagements down to the conversion point and beyond) is the only real answer here. Industry estimates often miss the mark!

[LArthur1]

I can definitely take some of these lessons aand start to seed them into conversations

[RBlackman7]

Great session on SLA especially the judicial element.

[Nancy_J]

I do know my conversion rates - but not when I first started. So, to get me started, I worked with a Sales and Marketing consultancy to help me with average ratios. That was my starting point. However, what I have not done a good job of is measuring the conversion for my content strategy. I am looking to optimize my content strategy to create more of an inbound system. So, am looking forward to getting that in place as I work through this certification.

[Sobhy]

Not all of us have access to complete data sets to calculate accurate conversion rates—and that makes setting an SLA between marketing and sales a real challenge.

If you're facing the same problem, you're not alone.

Many teams operate with partial data, outdated CRMs, or inconsistent tracking.
But you can still build a strong, realistic SLA using:

• Industry benchmarks

• Historical estimates (even if incomplete)

• Pipeline modeling based on average conversion ranges

• Input from Sales, Marketing, and Ops

• Assumptions you refine over time

I’d love to hear from this community:

How did you build your first SLA when your conversion data wasn’t fully reliable?
What benchmarks or methods helped you define lead quality and response time expectations?

[Jaycee_Lewis]

Hi, @Sobhy 👋 Welcome to our community! We're so glad you are here. Make sure to check out our community learning paths. We made them to help you be successful faster 🏎️ — Jaycee 

[CKSAHOO]

Assuming it's a new sales and marketing steup, and we do not have historic data to support or decisions, then I would look at the industry. What are their rates? I might even bring in an external consultant within our industry so we can do solid projections.

[Jaycee_Lewis]

Hey @CKSAHOO 👋 thanks for your post. Every so often it's better to pay for expert help rather than “wing it” when you have no or low data to work with in the beginning. Hope to see you around the community!  – Jaycee

[KNair4]

When you don’t know the numbers, build your SLA around process, effort, and responsiveness — then update it later with actual performance data.

[dyg]

Currently working on trying to get internal data to give us internal performance data. Mostly now, I am creating the infrastructure so that we can collect good data and begin looking at insights. For now, using 3rd party sources to create benchmarks. What I like to do in my analysis is look at 3 things:

1.  Once our internal data is cleaned and synthesized, I'll be able to look at how our current companies compare to our companies all time data
2. Then I will compare on a shorter scale, which can be month over month, quarter by quarter, year over year.
3. Then I compare that data to industry standards.

[Allieatom]

Ask questions and do research. What is the company goal and overall vision? Once you have this you can come up with actionable SLA for marketing and sales teams. 

[aguerrau90]

I do not know my conversion rates.

[Jaycee_Lewis]

Hey, @aguerrau90 👋 This thread has a lot of great suggestions, but one easy one to get started with is looking up the benchmarks for your industry or vertical. — Jaycee

[HLee8]

On the Marketing end, the benefit you have with digital Marketing platforms is the ability to speak to the reps and get an idea of average click-through rates. Conversion rates can vary with the business (B2C will vary by product and will again be different from B2B) but you can get good ballpark figures by asking reps for high-level benchmarks, consulting Gen AI tools and perhaps talking to one or two people who have hands-on experience with the channel you're working with.

Then it comes to determining your internal funnel which is going to be more complicated. Hopefully by the time you're scaling, you have some data on your first batch of leads. Remember, your first leads are always going to be the most qualified because you got them through high-touch methods and they're probably your most bought-in set of customers. People who come in through paid digital channels or syndicated content marketing are likely to be less qualified, but you can take a percentage haircut from your historical rates to get at the right ballpark to benchmark these. They may also need a different nurturing approach, so consider building out your CRM (customer relationship management) channel to ensure that leads who come from sources that aren't necessarily bought into your brand get nurtured in a way that's scalable for you.

[Abdulk]

Assuming it's a new sales and marketing steup, and we do not have historic data to support or decisions, then I would look at the industry. What are their rates? I might even bring in an external consultant within our industry so we can do solid projections. 

[OLiu]

That’s such a relatable challenge, many teams don’t have perfect conversion data when they first try to create an SLA. What I’ve found helpful is:

1. Start with industry benchmarks 

2. Use internal historical trends (even partial) 

3. Set directional targets, not fixed numbers 

4. Focus on accountability metrics you can control 

This way, you’re still able to build an SLA that aligns teams and reduces friction, while leaving room to refine it once your reporting improves.

[Atush_Sharma]

That’s such a relatable challenge, many teams don’t have perfect conversion data when they first try to create an SLA. What I’ve found helpful is:

1. Start with industry benchmarks – Even if you don’t have your own numbers yet, you can look at average conversion rates by industry as a starting point. For example, typical lead-to-MQL or MQL-to-SQL benchmarks can guide expectations.

2. Use internal historical trends (even partial) – If you don’t have full data, use whatever you do have—maybe from a single campaign, quarter, or region—as a baseline.

3. Set directional targets, not fixed numbers – Frame your SLA as “initial assumptions” rather than absolutes. This way, both marketing and sales agree to revisit it every quarter as more data becomes available.

4. Focus on accountability metrics you can control – Instead of just conversion rates, you can align on things like response time to leads, number of qualified leads handed over, or follow-up consistency. These create accountability even without full conversion visibility.

This way, you’re still able to build an SLA that aligns teams and reduces friction, while leaving room to refine it once your reporting improves.

[KAgarwal06]

With limitation in our raw data, we can assume the industry standards, for example, a B2B SAAS company has a conversion rate of 10% for lead-to-opportunity and 35% for opportunity-to-deal. Basis these assumptions, we can plan our quarterly targets for the respective teams and review them on monthly basis identifying our delta and planning the next quarter on the basis of the actual data. However, this exercise also helps in identifying the gaps if any and adopting the GTM frameworks which enables us to improve the negative delta.