We have just gone through the time of year when startups present their 2011 plans to their boards for approval. In many ways, these meetings are very similar to the meetings we have with new startups that have projections for how they believe their revenue will grow.
What I always find interesting in this process is looking at how the management team came up with the bookings forecast, and what steps they took to validate the number. In a lot of cases, the bookings target is determined using some rough top down logic like “We should be able to easily double the business this year” or “We’re similar to successful startup XYZ, and they hit $8m revenue in their third year, so we should be able to do the same.” What is surprising is how few companies do the work to validate their top down forecasts. Not surprisingly these are usually the companies that miss their forecast.
The smart companies will have built a bottom up model that shows how making certain investments in sales and marketing will lead to the top line number that they are looking for. To build that model, they will need the key conversion metrics for their customer acquisition funnel, or educated guesses as to what these will be.
(For an example of how a model like this might work for a SaaS business, take a look at the model included with this blog : SaaS Economics).
To help you prepare for your investor meetings, I’ll talk about how I, as a board member (or potential investor), would go about questioning you to validate your 2011 revenue forecast. Asking these questions will help me understand the implications it has on sales hiring, marketing spend, etc. For me, the trick to validation is to work backwards from the bookings number, looking at the various conversion rates in your customer acquisition funnel. (Nothing in this process is earth-shatteringly new or revolutionary, but it is surprising what insights it can produce.)
By going through this process, I am looking to validate the following items:
- Does the sales hiring (or channel recruitment) plan support the forecasted bookings number?
- Does it take into account the success/failure rate of sales hires?
- Are the sales hires made far enough in advance to allow for the ramp to full productivity?
- Is it reasonable to believe that the company can grow Trials/PoCs, Opportunities, MQLs, Raw Leads, etc. at the rate required?
- Are the current lead sources likely to scale to the levels required? If not, has the company identified and tested new sources that will support the lead growth required?
- Is there enough marketing budget to support the lead growth required?
- Has the forecast taken into consideration the time taken to move prospects from one stage in the funnel to the next?
Let’s look at a three examples to see how this works:
Example 1: A SaaS Company
Imagine a SaaS company that has a fairly simple funnel process:
- Drive visitors to their web site
- Drive site visitors to a free trial
- During the free trial use support people to help ensure success during the trial
- Convert the trials to a paid subscription
Note that the above diagram shows example conversion rates that have been averaged across all the lead sources. In practice these will vary by lead source, and it is important for marketing to track these numbers by lead source to judge the overall cost effectiveness of each lead source. However for the purposes of my validation exercise, the average number is usually good enough.
For a SaaS company, I would start by looking at the MRR (Monthly Recurring Revenue) at the end of the prior year, and then ask:
- What is the rate at which the company is projecting to increase MRR (Monthly Recurring Revenue) every month? (This will come from New Bookings minus Churn.)
- How many new customers are required in that month to support that bookings number?
- Does the rest of the funnel make sense to deliver that number of new customers? (See worksheet below.)
The above spreadsheet can be downloaded to see the formula here.
If you are doing this for the first time, and don’t yet know your conversion rates, I recommend taking educated guesses at these numbers based on your sector, and documenting where guesses have been made to highlight the risks to the plan.
The hardest part of this process is driving enough lead flow into the top of the funnel. What we have seen is that many lead sources tap out at a certain point, and finding new lead sources often costs more money.
So my questions would then focus in on what lead sources are expected to generate the traffic, and whether the costs per visitor take into account the possibility of higher costs for additional lead sources.
Example 2: An Enterprise Software company
Assuming the following sales cycle, with average conversion rates as shown:
For an enterprise sales model, I like to look quarter by quarter, as that provides just the right level of granularity.
Here is how my questions will go, (using Q4 for the example):
The above spreadsheet can be downloaded to see the formula here.
If the company has done its homework, it will be able to show you a bottom’s up model that shows all the logic and assumptions that they used to build their forecast.
Example 3: A Channel Sales Model
In the channel sales world, it is not uncommon to see three (or more) classes of resellers: highly productive, productive, and occasionally productive. For the purposes of discussion, let’s call these High, Medium, and Low. (Note that this naming convention reflects the level of productivity by the channel partner, not the level of certification achieves (e.g. gold, silver, bronze). As we all know well, it is uncommon to see many channel partners sign up for your top partner level, e.g. Gold, yet produce only at the low level .
What we are looking for here is:
- What are average number of deals per quarter, and average deal sizes for productive Gold, Silver and Bronze resellers?
- Is the bookings forecast supported by reasonable growth in the numbers and productivity of each reseller category?
- Is that growth rate supported by the appropriate number of channel salespeople?
- Are there channel marketing programs in place to support any growth in productivity levels that are projected in the High and Medium categories?
Dealing with unproven assumptions
Where there are many unproven assumptions involved, I recommend inserting a range of values from high to low into each assumption to see the effect on the model. It then makes sense for management to present two or three forecasts to the board including a projected, pessimistic, and possibly optimistic forecast.
From the above exercises, you will have probably seen that there are three ways that I am looking to validate the forecast:
- By sales resources (sales people, channel partners, etc.): Are there enough productive resources in place to support the bookings number?
- By Lead flow: Are there enough leads being driven into the top of the funnel, and then through the middle of the funnel to support the forecast?
- By timing: is the timing of how leads will convert to closed deals consistent with the duration of an average sales cycle?
Forecasts that are developed from the top down, without the validation of a bottom up analysis, are highly likely to fail. Building a detailed bottom up model has the following benefits:
- Uncovers where the problems lie in the sales and marketing funnel
- Highlights the key assumptions needed to drive growth. If these assumptions are untested, it shows where the risks lie in the forecast.
- Show the levels other resources required to support the funnel growth (e.g. marketing program spend, sales hiring, etc.)
- Highlights the places where attention should be focused early in the year to have a chance of hitting the bookings numbers later on.
- Focuses attention on the top of the funnel, and the importance of driving raw lead flow. Frequently this will be an area of high risk. Understanding that risk early on will help drive thinking about how to solve that problem.
Regular readers of my blog will likely recognise the key message here: sales and marketing is a numbers game, and in order to manage it well, it pays to break the sales process down into discrete funnel components and understand the metrics and conversion rates at each stage. They represent the key to forecasting, managing and improving your business.