The Essential Go To Market Math for Beating Your SaaS Startup's Growth Targets

How big is your SaaS startup’s sales pipeline? How big does it need to be to achieve next month’s bookings target? What is the ratio of the sales pipeline to bookings? What should it be?

When asked these questions during a fundraising pitch, one CEO responded with the number of demos per account executive per day to attain next month’s bookings, impressively conveying his command of his business. A startup’s leadership should know the number of customers, sales and marketing qualified leads to meet or exceed plan at all times. If you haven’t performed this exercise this before, use the interactive worksheet below. Change any of the text boxes and the figures will update. If you’re reading this post by email, please click through. Some email clients don’t allow JavaScript for security.

Let’s examine a hypothetical company with a bookings plan of $250k, an Average Revenue per Customer of $20k. The typical account executive at this company owns a $500k ARR quota, and on average achieves 75% of quota. 20% of Marketing Qualified Leads (MQLs) convert to Sales Qualified Leads (SQLs). And 20% of SQLs convert to customers.

Monthly Bookings Target, $ARPC, $AE Quota, $ AnnualQuota Attainment, decimalNumber of AEs Required
8
MQL to SQLSQL to Customer
Conversion Rates, decimal
Leads and Customers Required to Attain Bookings Goal
MQLSQLCustomers
Per Rep7982
Total6256413

The worksheet tells us quite a bit about this company. To attain next month’s bookings number, the business needs 8 fully ramped account executives. Each of these account executives must sell two contracts. To close these two customers, the company must generate 8 sales qualified leads, and 79 marketing qualified leads. In total, the company must generate 625 MQLs and 64 SQLs. Note, I’m rounding up in each of the calculations to be conservative, which is why the numbers may not divide evenly as integers.

These figures should inform sales and marketing hiring plans. The company requires a certain number of account executives to close customers and a certain number of marketers or sales development reps to generate leads. The data also provide a basic estimate of marketing costs. Multiplying the lead requirements by cost per lead provides a base level estimate for marketing spend in a given period. From which a business could compute cost of customer acquisition, and many other figures.

All of these elements to the plan, whether account executives or leads, have a latency. Account executives must be hired and they must be trained. This takes time, perhaps 3-4 months for very efficient sales teams. Then they must be provided leads, which require time some time to produce. And of course, the sales cycle introduces latency to bookings. While this worksheet doesn’t include any of those important factors, they must be considered.

Returning to the first set of questions, the ratio of the pipeline has to be 5x the bookings target, or the inverse of the SQL-to-customer ratio which is 0.2 for our hypothetical company. This makes sense. Only one in five leads will convert to a paying customer.

There are often questions around what is lead. As long as you’re measuring success rate from whatever point you call a lead a lead or an SQL an SQL, then the definitions don’t matter for this analysis.

Last, this concept can also be applied at an individual level. Different account executives will have varying conversion rates. These vary as a function individual skill, experience, region, geography, industry and other factors. Therefore, the required pipeline to enable each sales person to achieve their quota is again just the inverse of their lead to close rate.

Understanding the go-to-market requirements of a business is an essential skill at every stage of a SaaS company, and with just a few basic measurements, founders and CEOs of SaaS companies can understand precisely what the company must achieve each month to exceed its goals.

Published 2015-10-05 in Sales  SaaS 


I'm a partner at Redpoint. I invest in Series A and B SaaS companies. I write daily, data-driven blog posts about key questions facing startups. I co-authored the book, Winning with Data. Join more than 18,000 others receiving these blog posts by email.


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