B2B SaaS Sales Model

B2B SaaS sales modeling

Our third blog focuses on a common challenge that we have identified as a recurring theme in our current and potential investments. How to model new customer acquisition in B2B SaaS sales, and what we have noticed is often neglected while modeling. The blog’s goal is to provide insight for sales organizations to improve their sales budget planning. If you can include all the presented factors (and the missing ones / your own), we believe you are on the right track in improving your sales organization.

Multiple parameters are missing from our model and this article. We realize that a single post cannot provide a tailor-made solution for every organization, and thus the model is a generalization. However, with some creativity and adding your parameters, you can get realistic estimates of the future.

Before moving on

We want to address four crucial matters that might be very obvious but at times forgotten. First, when doing budget planning, try to base your assumptions on concrete numbers as much as possible. For many, this might mean taking historical averages. When you cannot use historical data, try to justify each assumption realistically. Second, plug in your actual numbers and compare them with your model’s estimates. Third, always build a model bottom-up instead of top-down. Fourth, exercise caution and apply the principle of prudence while modeling, just like in accounting.

Useful acronyms: AD — Account Director, AM — Account Manager, KAM — Key Account Manager, SDR — Sales Development Representative.

Average Employment Tenure

The first essential parameter is the average employment tenure of sales staff. Employers often mention the desired tenure in the job advert. This usually ranges from three to ten years. While that is somewhat optimistic, let’s start with 36 months. To account for sales staff’s average tenure, we have to “churn” the sales staff each month, i.e., if you have one account manager and your typical tenure is 36 months, you must churn your salesforce by 1 / 36 every month.

This might seem unrealistic at first, but it makes sense when applied to a larger organization. There is constant leakage of staff getting headhunted, changing industry, parental leave, etc. spanning before and after the x + 36 months. Furthermore, all budgets should consider that around 10–25% of recruits will leave after their trial period.

Ramp-Up Time

Models have the amount of AM’s, KAM’s, or AD’s for their budgeting but often miss the ramp-up time of new sales staff. This causes models to show overly optimistic levels of sales per sales staff. When ramp-up is included, you account for the new staff’s learning curve: knowing the company and building confidence in the product, team, management, and the ability to close deals.

Salesforce & SDRforce

Organizations should distinguish between sales staff and salesforce. Sales staff is how many people you have; salesforce is the sales capability of those people. Take your existing sales staff and start “churning” them by the average lifetime of your staff. Once a new recruit joins, assume that within x months he will perform like a “full-time” employee, and that y percent of recruits leave after their trial period. If you have different types of sales staff, normalize one of them and give relative weights to the others (e.g. AM = 1, KAM = 1.7).

Capacity, Conversion & Net Signed ARR

Using salesforce and SDRforce, you can estimate the capacity of your sales organization — how many calls and meetings it can handle each month. Distinguish hot and cold leads from your previous data, and use past conversion rates to estimate future ones. Before calculating Net Signed ARR, consider two missing factors: lagged sales and sales lost during the trial period.

Cost Estimation

Direct costs (salaries, salary-related expenses, commissions) are usually included. Indirect costs — recruitment, software, and layoff costs — are often missed. As employees churn, recruitment and dismissal become ongoing costs. If you aim to hire two new sales staff for a new expanding market, hire four: two will leave within 3–6 months.

Comparing Actuals to Estimates

Track actuals every month and plug them into your model. Create 5–15 parameters you follow monthly to see how actuals and estimates compare. Do not change estimates to fit actuals — your estimates are long-term averages, and the parameters are a mean-reverting process. Reconsider expectations only once you have enough new data.

Essential KPIs for any sales department:

• Number of meetings & deals
• Pipeline ARR & Signed ARR
• Salesforce and Sales Headcount
• ARR per salesforce unit
• Gross Sales Efficiency
• Potential Market Size
• Times market is cycled through in a year (anything more than 2.5 is way too fast)

If you wish to have the model or consultation regarding the subject, please email sami.aho@trado.fi.