“You don’t know, what you don’t know.”

Strategy: In the pursuit of consistent revenue growth, for-profit organizations lean on sales and marketing to produce consistent results. However, the majority of organizations have these two organizational units siloed and working towards separate metrics effectively making it difficult to determine their impact on each other and ultimately revenue.

Of the 1,600 sales and marketing decision-makers surveyed in SugarCRM’s 2022 CRM Impact Report, over half reported difficulty quantifying marketing’s contribution to revenue. The ability to align sales to marketing results in more efficient sales and marketing teams that are incentivized to perform based on the same metrics.

This sounds all well and good but ultimately what does this look like?

1. What is the sales revenue target
2. How many sales do they need to hit that target
3. How many leads are needed to convert to a closed won
4. Multiply (Closed Won) by (Leads Needed)

By flushing out what is needed from both organizational units to drive revenue growth, it creates an approach that aligns metrics. Sales has a revenue target that it needs to hit. Marketing should mirror that revenue target in a capacity that supports sales to consistently, month over month, hit the mark.

Process: The metric that makes the most sense to align around is revenue. By assigning a $ value to all leads that are generated, marketing now has a numerical value that needs to be achieved to support sales to hit their number. To implement this process, the needed metrics boil down to:

• Average Deal Size
• Conversion rate of leads to close deals
• Standardizing both of these numbers to a set length of time (months)

By taking the total revenue against the average deal size, you understand how many deals will need to close. Then, based on the conversion rate of each lead to closed won, you now assign a $ value to every lead created. The leads can be further broken down across any number of metrics or types depending on how granular you want to be with the data. Some examples we have seen include:

• ICP characteristics of prospects (size, industry, revenue, etc.)
• Different products
• Lead types (eBook, webinar, demo requests, referral, etc.)
• Department
• Seniority Title

Example: ACME Company

$100,000 in revenue per month
$50,000 average deal size
Deals needed to close per month = 2

Layer 1:
In its simplest form, if leads convert to closed won at 1% then marketing will need to produce 200 leads per month while a 4% conversion rate will require 50 leads per month.

After the initial high-level calculations are done, you can begin to get granular and more defined with your data.

Layer 2: 
If leads requesting a demo close at 10% and eBook downloads convert at 1% then you need 10 demo requests and 100 eBooks or whatever combination of leads ultimately yields a lead-produced value of $100,000.

Note: Your lead-produced value should always equal or exceed your revenue target. We might be stating the obvious but this is a common occurrence we have seen in our engagements. Inspect what you expect.

Layer 3:
To take it one level deeper, lets focus on the quality of the lead. If a VP who requests a demo closes at 25%, a VP who requests an eBook converts at 5%, a Manager who requests a demo closes at 5% and a Manager who requests an eBook closes at 0.5% you now have different data points to pull from to get to your $100,000.

In this scenario you could have 2 VP demo requests, 10 VP eBook downloads, 10 Managers demo requests and 100 Managers eBook downloads. These numbers would get your organization to its 2 Deals averaging $50,000 to arrive at your total monthly revenue produced of $100,000.

Of course, with all that is being requested of marketing, sales should be held accountable to reach out to leads produced in a specified time period with a clearly defined process in place for assigning leads.

Ultimately, this alignment allows for both sales and marketing to be held against the same metric: revenue. This provides marketing with a clear understanding of the why behind the data they’re being held accountable for.

Let’s Get to Work: You can slice and dice this and get super granular on aligning the two business functions. If you’re just starting out, our recommendation is to put a $ value against your most basic metrics, run it for a month and digest the results. After this period of time, take it a level deeper and repeat the process. Rinse and repeat to the preferred level of detail. Here is an initial list of metrics to get started with:

• Leads generated by company segments:
  • Revenue range
  • Industry
  • Headcount
• Leads by product
• Leads produced by referrals
• Leads produced for cross-sells/upsells

Inspect what you expect for each of these buckets of leads by analyzing the conversion rates. You might be surprised by which leads convert at the highest rate and/or bring in the most revenue.