With host Darrell Alfonso
Developing a demand waterfall is a critical exercise for your marketing organization. You’re likely already using this methodology to refine your approach to lead follow-up and ensure no interest generated falls through the cracks.
By reviewing the historical conversion rates between these highly defined stages, you can provide accurate forecasting based on data instead of intuition.
Here’s where you might be missing something.
What you might not be doing to reap real benefits is reversing your waterfall. Marketers can also leverage conversion rates to determine how much demand your team must create to hit the company’s revenue targets.
While every organization varies in terms of how their demand waterfall should look and the specific categories and language to use, yours probably includes at least the following categories:
For at least as long as you’ve had your demand waterfall in place, you should be able to see how the numbers have corresponded to those categories. How many inquiries turn into MQLs in a typical quarter? What percentage of those eventually make it all the way to the bottom of the waterfall to become customers?
Let’s say your organization generates 1,000 inquiries per quarter and that an average customer represents $10,000 in revenue. Based on best practice conversion rates you might see conversions equivalent to:
By multiplying each of these conversion rates (.10*.85*.60*.30) we can determine an overall waterfall conversion rate of 1.53% across all stages. This means that our 1,000 inquiries generated are likely to result in 15 new customers worth just over $150,000 for the quarter based on historical averages.
1,000 INQs * 1.53% = 15 customers
15 customers * $10,000 avg deal size = 150,000 in revenue
Seldom are marketing departments given free rein to generate demand hoping to touch down softly in the land of milk and honey at the end of the quarter. More likely is a scenario where your organization is tasked with generating $200,000 for the quarter. If we are going to get there, how much interest do we need in order to succeed? Lucky for us, our conversion rates work in reverse.
Based on our average deal size, $200,000 in revenue (the 33% growth that we’ve been tasked with) means we need to land 20 customers. If we divide our goal of 20 by our 1.53% conversion rate, we yield a total of 1,300 Inquiries needed.
$200,000 = 20 customers
20 / 1.53% = 1,300 INQs
Now, marketing has a quarterly goal based on data that will, if historical values hold true, allow us to accomplish our goal. This, of course, assumes a short sales cycle for the purposes of simplicity.
If you have a prolonged sales cycle, you may want to dig even deeper to understand how much demand needs to be generated in advance of revenue targets to ensure goals are met. For example, if you have a three-month sales cycle, you should be estimating at least one quarter out.
The longer a demand waterfall is deployed, the more refined these stage conversions will become. Therefore, while implementing a waterfall methodology for the first time will provide valuable insights, the added volume of INQs to CW over time will serve to provide increasingly effective conversions for revenue estimation.
If you already know your leads have decreased for the quarter, then the reverse waterfall will help you gauge the expected decrease in revenue. As a corollary, if you manage to increase those numbers, or if you expect to based on investing more in marketing channels that your data tells you are paying off, then you can calculate the likely increase in advance.
In either scenario, the reverse waterfall calculations allow you to set realistic goals and do more accurate marketing planning for the months and quarters to come.There’s so much your data can tell you when you start to do the work of translating it into insights. Your reverse waterfall can open your eyes to the results you can expect from your current waterfall and any expected changes to it.
Uptempo enables you to understand the predicted performance impact of your plans—in real time.