Those days are over. As the CMO, the expectation is that your team provides a minimum of 25% of the revenue. This includes leads closed and in-year revenue recognized.
Based on the closure rate of the current sales process, how many sales qualified leads (SQL) do you need to make your number? Download the Lead Gen Calculator to determine how many leads you need.
We see more and more marketing executives carrying a bag (quota) these days than ever before. The reason for this; CEO’s require a return on marketing investment (ROMI).
No, I’m not referring to a brand awareness campaign for ROMI. Meaning we measured brand awareness before and after our campaign and celebrate the increased awareness. CEO’s and board members in B2B firms are looking for a more direct measurement of marketing spend. This measurement comes in the form of a direct line between marketing spend and revenue.
Some of the questions you may be asking yourself at this point are:
- Can I rely on sales to close the SQL’s marketing delivers?
- Is my team good enough?
- What is the right number of leads for my business?
Our focus will be on the last question. “What is the right number of leads?”
There are two primary approaches to calculating the right number of leads required: Top down and bottoms up. In both cases it requires you to have the ability to effectively measure the conversion rate from inquiry to SQL. For a more detailed description try Marketo’s recent Definitive Guide to Marketing Metrics.
Let’s start with a top down approach and the required fundamental data points you need:
- 25% of the company revenue plan
- Average deal size
- Sales process closure rate
- Conversion rates from Inquiry –MCL–MQL-SQL –Opportunity
Note: if you don’t have the conversion rates above, utilize the conversion rates provided on the Lead Gen Calculator or contact me at firstname.lastname@example.org and I’ll spend 30 minutes walking you through the process.
Example of the top down approach:
Let’s say 25% of revenue equals $7.5M and the average deal size is $85,000. That means you need at least 88 deals to hit the marketing revenue quota. Let’s assume you have the following conversion rates and peer group benchmarks: Inquiry –MCL –MQL-SQL –Opportunity. You can now work your way down the stack to identify where you may be missing the benchmark. This will also allow you to determine how many inquiries you need to make the number.
The opportunity exists to identify gaps throughout the process. Don’t assume it’s a lack of inquiries. As an example: You may be lacking content to convert your prospects from MQL to SQL and that is your gap. Completing the lead generation calculator will allow you to identify where the gaps exist.
Example of the bottom up approach:
In the bottoms up view, you’re looking at the number of inquiries being generated. Let’s again assume you have the following conversion rates: Inquiry–MCL–MQL-SQL –Opportunity. As you move up the stack you’ll be able to determine the conversion rate gaps. In addition, you’ll determine whether you’re supplying sales enough qualified leads to hit your quota.
The mistake here is to assume a large number of inquiries is the only metric that matters. The opportunity exists to identify gaps throughout the lead management process.
According to the Sales Executive Council (SEC), on average 57% of the buying process is complete before sales knows the buyer is in the market. This means you need content aligned to the buyer throughout the process. Without the ability to measure the lead management gaps, you have no ability to understand where to adjust your focus.
The first thing marketing teams think about in this situation is: I’m still relying on sales to close the deal. True, step 1 is understanding the baseline sales process close rate. Step 2; agree with sales on the definition of a Sales Qualified Lead (SQL). This allows you to have a fact based conversion with the head of sales
I recently sat down with a Fortune 100 company to walk through this process. They were very focused on the conversion rate from MCL to SQL and were at or near the benchmarks. The problem was the input (inquiries) and the total output (SQLs). Without enough inquiries the number of SQL’s combined with the closure rate equaled less than 1% of revenue.