Financial Model for SaaS Product: 3 Ways of Customers Acquisition

The SaaS (Software as a Service) model has claimed leading positions in the IT product market, affirming its convenience for both users and product creators. The market size is projected to reach 197 billion USD in 2023 and is expected to continue growing at a minimum rate of 10% annually (or as ambitiously as 30% annually). Well-known SaaS solutions include products such as Salesforce, Microsoft 365, Zoom, Shopify, and many others.

The user’s journey to purchasing a SaaS product typically begins with visiting the company’s website through organic channels or advertising. This is followed by stages of product exploration, purchase, and usage. The customer can make the purchase independently, and in this case, the company incurs costs only for marketing promotion (and, of course, for ensuring a good UX on the website to guide the buyer to completion). However, the more complex and expensive the product, the more crucial the roles of sales teams, onboarding, and support become.

When launching a SaaS product, it is essential to approach pricing and customer acquisition cost calculation deliberately. In this article, we explore three ways to attract customers, each with its own economic dynamics. By constructing such a financial model for your SaaS project, you can understand which option or combination of options is suitable in your case and under what target values for pricing and expenses the product will be commercially successful.

The basic financial model we construct for any new business is the “3-Statements Model,” which involves forecasting movements across the three core financial statements: Profit and Loss (P&L), Cash Flow, and the Balance Sheet.
You can find the financial model at this link, with examples that we will be breaking down in this article.

Our first step is to calculate the profit and loss, beginning with revenue forecasting. The order of revenue generation is a key distinction among various business models. Therefore, in this article, we will delve into the calculation of customer numbers and revenue dynamics for different customer acquisition models for a SaaS product. The overall structure of the model and the forecasting method based on the project roadmap are extensively described in this article.

In building our financial model, we follow the user’s journey and describe it in numbers. For a SaaS product, the starting point in most cases is the number of website visitors. In the case of outbound sales, the website visit stage is replaced by the first contact between a manager and a potential buyer. We’ll explore this scenario in the section on customer acquisition through cold sales. For now, let’s examine how traffic is generated on the website, which is subsequently converted either into a self-purchase or a lead for the inbound sales department.

The user’s first direct interaction with the product occurs when they open the website. To get someone to visit the site, they must first learn about it. To achieve this, companies utilize various marketing channels, broadly categorized into organic and direct advertising. From a financial model perspective, we directly influence traffic from direct marketing channels through the advertising budget and CPC (Cost per Click) — the cost of a click. In this case, there is a direct correlation between expenses on direct marketing and the number of website visitors. It’s not feasible to directly link traffic from organic channels to expenses, but this doesn’t mean organic traffic is free. Costs for SEO, social media management, brand awareness marketing campaigns, content creation, and publication — all of these are necessary for organic traffic. Therefore, when making assumptions about organic traffic in the financial model and forecasting its growth, we must incorporate the costs that can support these figures into the expense section.

Organic Channels

Let’s dive directly into the financial model table and start inputting the initial data. We do this on a separate tab where all quantitative assumptions for the new business project are gathered. We begin with parameters for forecasting organic installations. Set the application launch date — in the example screenshot, the date is determined based on the event selected in the project roadmap. Assume the number of installations in the first month of operation, relying on your existing audience, competitor experience, and benchmarks for your industry. Next, set the monthly growth rates for organic installations. To prevent our forecast from soaring to astronomical figures, add a maximum limit at which growth stops.

This is a basic algorithm suitable for rough growth estimates in the first few years. For long-term planning, a scenario of reducing new installations as market capacity is exhausted may be considered. If your product is subject to seasonality, it’s better to base growth year by year and categorize months into high, medium, and low seasons.

Paid Channels

Now, let’s move on to parameters for calculating installations from paid channels. Determine the start date of direct marketing campaigns and the budget for the first month. The budget’s growth can be specified through a percentage of monthly or annual increase, limiting it to a maximum amount. However, in practice, we often increase the advertising budget at specific events and phases of product development. Therefore, I prefer selecting events from the roadmap that trigger budget increases and specifying the amounts of additional budgets.

The second parameter for calculating the number of installations from paid channels is CPC (Cost per Click) — the cost of a click, i.e., the transition from advertising to the website. The actual CPC for your application will only be known after launching your advertising campaign. Still, at the early stages of project development, you can find a suitable benchmark for the financial model. Benchmarks for CPC in various industries and channels are regularly published by both marketing agencies and advertising platforms. After product launch and test campaigns, remember to revisit the financial model and adjust the calculations.

Our goal is to create a dynamic model that facilitates calculations for different scenarios at the initial stages of project development. Therefore, we make monthly forecasts on a separate tab, setting all indicators through formulas.

Determining the First Month

To determine the month from which traffic appears in the model, we use the IF function.

If the date value for the column is greater than or equal to the launch date of the application or direct marketing campaigns, we start calculating the indicator using the formula; otherwise, the cell value is “0.”

In a general sense, this formula in Excel or Google Sheets looks like this:
=IF(E2 (month in the forecast) >= Projections! $E$13 (start date in input data); formula; 0)

Calculating Traffic

For Organic Traffic:
In the launch month, we set the number of installations equal to the specified number of installations in the first month on the input data tab. For subsequent months, we choose the minimum of the product of the number of installations from the previous month and the percentage of monthly growth and the maximum possible traffic.

For Paid Channels:
We divide the budget for direct advertising in this month by the CPC specified on the input data tab.

The fundamental pricing method for SaaS products is a subscription model — the customer pays a regular fee for using the solution for a month, a year, or another specified period. Within the subscription, different plans are typically offered, depending on specific packages such as the number of users, distinct features, and more. The second common option is the so-called pay-as-you-go model. Here, payment is based on the actual volume of product usage by the customer.

In this article, we are focusing on the process of calculating different customer acquisition methods. Therefore, to simplify the model in the example, we won’t introduce various plans and billing complexities; instead, we streamline the pricing to a single subscription price with monthly payment.

Setting Prices

Enter the subscription cost for one month in the corresponding cell. If you plan to have different-priced plans and offer discounts for annual subscription payments, describe that information here as well. In the example screenshot, the model is kept simple with only one plan and monthly payment.

Assuming Churn Rate

Now, determine the Churn Rate. In this case, the Churn Rate is the percentage of subscribers who will not renew their subscription for the next month. In the example, we assume that the Churn Rate will be the same regardless of the customer acquisition method. In practice, you can specify different Churn Rates for different customer acquisition methods if there are grounds to believe that the difference is significant.

If the SaaS product is targeted at a B2C audience and has a low subscription cost, the model can function without a sales department. The customer independently decides to make the purchase without prior consultation and pays for the product online. Lower-tier plans for more complex products can also be sold independently. In the case of B2B solutions, it might be appropriate to include expenses for an employee who will handle document processing for transactions with legal entities.

In the financial model, calculating the revenue stream from this channel will be as straightforward as possible. In the input data, you would need to specify the planned conversion rate of website visitors to purchases. If you offer a free trial or demo, you can add another conversion stage. Visitors will convert into users of the free period, and then those users will convert into purchasers.

On the monthly forecast tab, perform calculations using formulas, following the same approach as when calculating traffic at the beginning of the model.

Calculate the number of new subscribers by multiplying the traffic in the current month by the forecasted conversion rate. The number of lost customers is obtained by multiplying the number of customers at the end of the previous period by the Churn Rate.

The number of subscribers in the month will be:
Subscribers in the previous month + New subscribers — Lost subscribers
Multiplying this result by the monthly subscription price specified in the input data will give you the revenue from the self-purchase channel.

Inbound sales is one of the popular and effective (with proper setup) channels for all B2B products, and it is well-suited for SaaS solutions. This approach combines marketing and the sales department. Advertising generates interest in the product and prompts potential customers to contact the company. A sales manager provides consultation on the product’s features and its application for the specific buyer, ultimately closing the sale.

When a customer approaches on their own, it is generally easier for the sales manager to guide them through the purchase process. The deal-closing period is usually significantly shorter compared to outbound sales.

In the financial model for calculating metrics related to outbound sales, new steps are added compared to self-purchases. Here, both the formation of the revenue side and the impact on expenses need to be considered.

Firstly, set the forecasted conversion rate of website visitors to leads. Leads go to the sales managers, and after interacting with the customer, the sale occurs. Reflect this in the input data of the financial model by entering the target conversion value from lead to sale.

Moving on to the expense side, we need to account for salaries for sales managers. The efficiency of managers, and hence the conversion to purchase, will depend on their workload. A manager should handle a manageable number of leads that they can process and convert into sales. If there are too many inquiries, they will only be able to respond to calls. Therefore, in the financial model, we set a target number of leads per manager per month. Depending on the specific product and its sales cycle, the optimal number of leads per manager may vary.

In the forecast, we calculate the number of managers based on the growth of incoming leads and plan for regular hiring of new employees to ensure the quality processing of all incoming inquiries as the product grows.

On the monthly forecast tab, perform calculations using formulas, following the same approach as when calculating the previous revenue stream.

For outbound sales, marketing is no longer the determining factor. However, marketing and other expenses not related to salaries and bonuses of managers may still arise. For example, tickets to exhibitions and events where managers can build a contact database and conduct sales, or the purchase of databases of potential customer contacts. If such expenses are relevant for your product, don’t forget to include them in the expense section of the financial model.

In outbound sales, the process starts not from website traffic but from contacts that managers have with clients. Similar to inbound sales, for cold outreach, it’s essential to define target metrics for the number of initial contacts with managers and closed deals.

If, in the previous scenario, the volume of leads determined the number of managers and the frequency of their hiring, here, the size of the outbound sales department will determine the number of sales.

In the input data, set the number of managers at the start, the frequency of hiring new employees, and the maximum staff size of the department. Next, enter the target number of closed deals per manager per month.

This describes the basic version, sufficient for simplified financial modeling. If the sales cycle for your product exceeds one month, you can account for this in the model by delaying the appearance of a new manager’s first clients in the forecast for the required number of months from their hiring date. Another option, closer to reality, would be a gradual increase in the sales department’s or individual employees’ target metrics over several months. A newly created sales department, like a newly hired manager, needs time for training, integration, and reaching maximum productivity.

On the monthly forecast tab, perform calculations using formulas, following the same approach as when calculating the previous revenue streams.

Now you have a tool to assess how well a particular business model fits your product. Choose benchmarks that are realistic for your specific case, taking into account the results of marketing research (for the financial model, it’s crucial to consider competitor analysis, market size estimation, and surveys of potential customers). Play around with the figures in the input data. For convenience, you can add graphs and additional metrics.

To build a comprehensive financial model, determine the breakeven point, and estimate the required investments, it is essential to include all expenses in the calculations. In this article, we have only covered the basics of revenue generation with different customer acquisition models for SaaS products. For more information on other aspects of financial models, you can refer to my other articles on the blog.

A financial model template in Google Sheets or Excel, complete with all the formulas, can be obtained via the provided link.