From Prospect to Close | A model to forecast your sales pipeline
I have been meaning to create a sales pipeline model model for a while. How many of us forecast increases in software bookings based on the number of sales reps, their quota, and achievement levels? I can raise my hand to this question.
# of Sales Reps x Quota x % Achievement Level = Forecasted Bookings
Not that this method is bad; it’s a place to start lacking other data on your sales pipeline. However, I really wanted to be able to support the assumptions behind our long-term forecasts and also help the sales team with their sales pipeline forecasts.
You can download the the pipeline model below.
The Basic Premise
It is hard to have confidence in long-term bookings numbers if you have no visibility on the beginning or top of the funnel. If we are not contacting prospects and turning them into qualified leads at a specific time rate and conversion factor, how do I know that we can hit our bookings number at the end of the funnel?
I based the stages of the funnel on a book Aaron Ross and Marylou Tyler. If you support your sales organization and work in software or SaaS, I highly recommend reading Predictable Revenue and From Impossible to Inevitable (written by Jason Lemkin and Aaron Ross). These books provide great insights into building and scaling sales organizations and include real life metrics and “how-to,” not just high-level stuff.
What does the Sales Funnel model do?
The sales funnel Excel model starts at the top of funnel (prospects) and pushes the prospects through each stage of the sales cycle based on time spent at that sales stage (based on weeks in my model) and a win percentage.
For example, if I contact 500 prospects this month, I expect 10% to respond and a duration of four weeks to accomplish this. The 50 prospects who respond then move to the next sales stage and at the correct time in the funnel. This continues through each sales stage until you close X% of these deals.
Prospect numbers are driven by the number of sales development reps (SDR’s) that you have on your team and how many new prospects the SDR’s add to the funnel each month.
I also added functionality to recycle non-responsive prospects though the model. After all, you took the time find the contact information for these ideal prospects, so you will probably continue to reach out to them until they buy or tell you to stop.
Once you complete this model, you can then take the output and complete the SaaS Revenue Forecast model. Please let me know what you like and don’t like about this model. Do you currently model your software bookings starting with the top of the sales funnel?