A Marketer’s Guide to Forecasting When Everything Has Changed
In the world of COVID-19 forecasting demand is even more challenging given the New Marketing Landscape and the rapidly evolving environment. Now more than ever, it’s critical for SaaS ScaleUp marketing leaders to adopt a more agile approach to demand generation. To be agile, marketing leaders must be able to quickly understand the ramifications of reallocating resources on the company’s ability to achieve booking targets – and change direction if needed as the crisis evolves. The only way to do this is to implement a granular, by channel, bottoms-up approach to demand gen to capture how shifting market dynamics will impact your business across products, territories, and sales motions.
A Basic Approach: Top-down Forecasting
Many ScaleUp companies take a top-down approach to lead generation forecasting, not only to set quarterly lead targets, but to measure marketing’s progress towards its goal. Usually, due to limitations in their reporting, marketing leaders will simply use the prior year’s per stage funnel conversion rates or even worse, they will use plug and play assumptions to make the pipeline math work. While this streamlines the forecasting process, this approach is inherently flawed for the following reasons:
- The key drivers of demand generation vary by marketing channel. Your cost, conversion rates, and average deal size will always vary by lead source. By using one-size-fits-all assumptions to solve for a pipeline target, your lead gen projections will most likely be inaccurate since the program mix is constantly changing.
- The program mix will constantly evolve and need reassessment. Startup companies that find initial product-market fit generally grow through organic website direct traffic in the early years. As the organization transitions to a ScaleUp growth phase, it continues to add new paid acquisition channels which will perform very differently (especially versus organic). Top-down projections which use “muddled” assumptions do not provide enough granularity to model out marketing spend performance.
- The company may test new markets, launch new products, and/or experience shifts in existing target market dynamics. Companies are constantly evolving. At this very moment, there’s a good chance you’re moving up-market, targeting a new vertical, expanding internationally, and launching new product features. New opportunities and changes will continually arise, and a top-down projection model lacks the flexibility to incorporate how these will impact your numbers.
Despite these pitfalls, top-down forecasting can be helpful as a quick and easy gut check to see if the current in-period pipeline targets are achievable or not. However, relying solely on a top-down model for lead gen projections is sub-optimal, especially in the current environment of COVID-19.
A More Advanced Approach: Bottom-up Forecasting
A bottom-up approach to demand gen forecasting is better suited for an agile marketing organization due to its granularity. Unlike a top-down approach, the bottom-up approach creates:
- Projections based on planned activities across marketing channels to better align expectations of what future performance may look like.
- Visibility across marketing channels to better understand the different levers at your disposal to hit your numbers.
- Flexibility to update your assumptions based on actual performance data to better identify opportunities so that you can quickly shift tactics and reallocate resources.
Many marketing leaders will shy away from using a bottom-up model because it is difficult to build and maintain, especially if your company lacks basic reporting infrastructure to quickly pull the detailed numbers. Additionally, establishing a process to collect timely pipeline-level data from the sales team can be time-consuming and require organizational alignment. Setting up this infrastructure now is foundational to evaluating your demand gen programs and providing an accurate assessment of how you are tracking to your quarterly goals.
Key Considerations for your Bottom-up Model
When building your bottom-up demand gen model, you need to incorporate the following key levers:
Acquisition Channel: As you scale your demand generation program, it is important to build a portfolio of different acquisition channels to diversify sources for your leads. Your model needs to deliver clarity about the primary sources of lead acquisition and the different levels of performance you can expect. You can then analyze trends and performance data per acquisition channel to improve your decision making about where to optimize and where to reallocate spend.
Cost: While you should be working to hit your lead and pipeline targets, you shouldn’t achieve those numbers at an unsustainable level of spend. Different channels carry a different range of average CPLs. Note that while CPLs are the easiest cost measure to get, we caution against only using CPL. As we’ve pointed out in our past post on marketing KPIs, it’s important to also factor in conversion rates and average deal size by channel. This helps you get true visibility into where you are generating the best ROI.
Conversion Rates: Each lead source will carry a different conversion rate; organic/direct is the best, while awareness channels such as display ads are on the lower end. A common mistake in top-down lead forecasting is applying one-size-fits-all conversion rates, for example from your organic funnel, across all marketing channels. An effective bottom-up model should help you understand the ranges of conversion rates by channel to invest in higher performers.
Average Deal Size: Just like conversion rates, each lead source will also carry a different average deal size. Without factoring in average deal size, you will not have an accurate picture of the channel performance. For example, when comparing two channels, you may think that one performs better because it generates a larger number of deals, not considering a different channel that may generate fewer deals but larger average deal sizes. Implementing a consistent feedback loop with the sales organization is key to having relevant data to continually update your target buyer profile.
Velocity: Pipeline creation depends on factors such as your company’s average deal size and sales cycle, so your lead gen forecasting should incorporate variances in timing for both opportunity creation and deals won. Insight’s best practice is to measure marketing activities on a cohort basis to better understand exactly when pipeline will be created and deals will close.
Putting the Pieces Together
By looking at your demand generation through these key levers, you can now create your own granular bottom-up forecasting model. Specifically, when creating this model in Excel:
- Create a sheet for your planned marketing activities and map your acquisition channels
- Create a sheet by acquisition channel to map your spend (e.g., Organic, Virtual Events, Paid Search, LinkedIn – the more granular, the better)
- Decide your assumptions for Cost Per Lead, conversion rates, average deal size, and velocity
- Allocate your planned spend for each campaign by acquisition channel
- Estimate the number of leads created based on historic CPL data or a conservative estimate
- Estimate the resulting opportunity and new booking dollars (i.e., CPL x Conversion Rate x Average Deal Size)
- Project out when those opportunity and new booking dollars will occur given each channel’s velocity
- Roll-up your projections across the acquisition channels into a summary sheet
- Collect your actual results across marketing, partner and sales and use the performance data to reevaluate your assumptions
- Track results against your organization’s targets
The critical piece to maintaining accuracy in your projections is logging your actuals and updating your assumptions as new performance data comes in. Additionally, make sure to note outliers in the data, such as higher ASP deals, as these will skew your channel performance numbers. This is especially important as you test new channels because it will take time for the performance to normalize.
Key Insight: A Blended Approach
Ultimately, best-in-class marketing leaders should use a blended approach. A top-down model can provide a simple gut check to see how marketing is performing overall relative to its targets, while the bottom-up model will provide clarity on how the department can deliver leads and pipeline.
With all this said, your projections are only as good as your access to current data. For your organization to be truly agile, you need to be able to update your model regularly with data from your analytics and/or BI tool (ideally on a weekly basis). Additionally, you should implement a regular review of marketing leads with the sales organization to collect qualitative feedback to better assess lead quality. For any ScaleUp business, creating a functional framework to measure performance weekly and reevaluate your assumptions is critical to success, regardless of the current economic environment.