Best Practices: Sales Forecasting for B2B SaaS Start-Ups
Liquidity or cash flow forecasting is crucial for fast growing VC-backed B2B SaaS ventures. With normally a high burn-rate, predicting a designated cash run-rate is important for financial planning, risk management and the success of a start-up. In the B2B SaaS space, costs can be managed pretty easily. However, the revenue side is hard to forecast. Therefore, I would like to give some insights into best practices of revenue forecasting, which we learnt from 25+ investments into B2B SaaS start-ups during the last decade. This article is written for all founders, CEOs, CFOs, CRO, CSO and whoever is responsible for a sales team and sales forecasting. But also sales managers might get some interesting insights how to become more precise in their own sales forecasting.
Some Definitions beforehand
In order to precise the focus of this blog post and give a general context to potential non-sales experts, few definitions are important to be made regarding the typical stages and process in sales and marketing. It is also illustrated in the graphics below.
A typical marketing and sales process is structured as followed:
1. The marketing department (with the help of marketing development representatives, MDRs) brings in potential customer leads which are qualified into MQLs (marketing qualified leads).
2. Sales or business development representatives (BDRs/SDRs) further qualify these leads by doing research, first calls etc. Out of the relevant leads, SQLs (sales qualified leads) are filtered.
3. Sales manager (often also called account executives, AEs) drive these ones (hopefully) until contract signing, where the SQL becomes a paying customer.
4. Product implementation and customer onboarding is mostly done by the customer success department. This is also responsible for churn prevention and upselling. Upselling can also be the task of the sales managers depending on the individual corporate structure. The graphic below illustrates a typical marketing and sales process with the relevant stages and people involved.
Moreover, conversion rates (CR) represent the conversions of a potential customer from one stage to the other (in percentage, i.e. shifting of a prospect to the next sales stage). Conversion rates can be also summarized from the first to the last stage and so on.
Finally, sales quotas and achievements represent the target of sales per sales manager and the individual achievement in percentage.
I will focus on pure sales forecasting, and not give advice or a playbook on how to plan your sales and marketing budget in order to achieve certain year-end revenue targets. This can be elaborated based on historic conversion rates and budgets used. While doing so and comparing last year’s plan and outcome, you will realize how important sales forecasting itself is.
B2B SaaS Sales Forecasting & my 10 Key Learnings
First of all, revenue or sales forecasting is a process, not a simple gut feeling. The further you are “away” from your customer as well as your sales managers, the harder it is to predict revenues. For example, predicting revenues of a sales partnerships with external companies attempting to sell your product is much harder than sales forecasting with your internal sales team. Therefore, I want to focus on direct sales channels and the forecasting of sales revenues done by sales managers or key account managers. Moreover, I do not consider the forecasting of marketing qualified leads accomplished by the marketing department. Main reason is that this kind of forecasting is often very software and budget driven, like online performance marketing, where capabilities of human judgement have a lower impact.
When it comes to good sales forecasting, I believe most of it relies on mutual learning and consistent assessment as well as coaching.
Why mutual learning? Every product, market and customer segment is different and might change over time. Therefore, it is very important that you learn as much as possible in the shortest time possible by and through all your team members. Do weekly sales forecasting meetups where colleagues present their sales forecast and why they expect certain closing dates. The entire team learns why and when customers might slip in the respective month or quarter. Moreover, you learn a lot about customer segments, markets and industries. Each segment (i.e. in terms of size), markets (i.e. in terms of regions or countries), as well as each industry has specific purchase criteria, buying personas and processes. Especially as a start-up entering a new market or industry, your learning curve regarding forecasting will be very steep.
Why consistent assessment and coaching? With assessment I mean consistently assessing (learning from) the team in terms of human judgement and biases. The average sales manager I met in my life was very optimistic and when it comes to his or her projections on sales quota achievements, judgement was poor. Of course, in general, optimism is a good character trait. However, when it comes to sales forecasting, the forecast numbers should be as precise as possible. Therefore, consistently assessing the individual sales manager’s forecast is crucial. The more you, as a founder or CSO or VP Sales, are in exchange with your sales team, the better you can judge and trust the individual forecasting capabilities. But just knowing if one team member is not good at forecasting is not enough. You must act as a coach and partner in order to improve his or her own capabilities.
So how to achieve this? The 10 key learnings that I observed in order to accomplish a successful sales forecasting are as follows:
1. If you promote a new product or enter into a new market where you do not know the sales conversion rates yet, rather set the sales quotas low in order to incentivize and motivate your salespeople. Then, they will probably do a more realistic sales forecasting.
2. Make every SDR or sales manager responsible for his or her sales forecast. Don’t let them hide behind a sales controlling or BI manager.
3. Follow-up and incentivize sales forecast accuracy by implementing it into the variable sales bonus.
4. Do not focus on the “closed won” forecasting capabilities only, look at the entire movement of the sales funnel. Consider where and why certain customers are dropped out of the process.
5. Get rid of inactive deals fast and re-activate them only if there is a real new interest coming from the prospect or an actual movement to another stage is happening.
6. Continuously learn from the reasons of “closed lost” deals and integrate the insights in your sales forecasting process.
7. Do your HR sales planning on a pessimistic basis, i.e. hire more sales managers. If they all perform, they will pay off eventually. If they do not perform, you do not jeopardize your sales planning and forecasting.
8. Challenge everyone’s sales forecast together within your entire sales team. Sales managers will learn from good as well as bad forecasting capabilities of their colleagues.
9. Do not only show sales achievements of each individual sales managers, i.e. closed won, on a big screen within your sales office. Promote and foster sales forecast capabilities. This will increase your prediction capabilities and make people feel more responsible for accurate forecasting.
10. Consider weighting the prospect revenues based on forecasting period, not only sales stage. I.e. the longer the forecasting horizon, the lower the probability of a closed won deal at the specific month.
I hope you enjoyed the reading. As always, I am happy to receive comments and questions on this very relevant topic on B2B enterprise SaaS sales forecasting via email@example.com.