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What is a cash flow forecast?
A cash flow forecast for a B2B (business-to-business) or SMB (small and medium-sized business) SaaS (Software as a Service) business is a financial planning tool that projects the company's inflows and outflows of cash over a specific period, usually one year. It helps the business owners and stakeholders understand the company's liquidity position, anticipate cash shortages, and make informed decisions about investments, cost control, and growth strategies.
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What goes into a Cash Flow Forecast?
Here are the key components to consider when creating a cash flow forecast for a B2B or SMB SaaS business:
- Revenue projections:
a. Recurring revenue: This includes monthly or annual subscription fees paid by customers for using the software.
b. New customer acquisition: Project the number of new customers you expect to acquire and their associated revenue.
c. Churn rate: Estimate the percentage of customers who cancel their subscriptions, impacting your recurring revenue.
d. Expansion revenue: This comes from existing customers upgrading to higher-tier plans or purchasing additional features.
- Cost of Goods Sold (COGS):
a. Hosting and infrastructure costs: Expenses related to cloud computing, data storage, and network bandwidth.
b. Third-party software costs: Expenses for using third-party tools, services, or APIs that are integrated into your SaaS product.
c. Support costs: Salaries and benefits for customer support staff, as well as any costs associated with support tools and software.
- Operating expenses (OPEX):
a. Research and development: Costs related to product development, including salaries for software engineers, designers, and product managers.
b. Sales and marketing: Expenses for customer acquisition, including salaries, commissions, advertising, and marketing tools or services.
c. General and administrative (G&A): Expenses for running the business, including rent, utilities, office supplies, insurance, and salaries for non-product
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What types of revenue line items go into a cash flow forecast?
In a cash flow forecast, various types of items are recorded as revenue, depending on the nature of the business. For a B2B or SMB SaaS business, typical revenue items include:
- Recurring revenue: This is the primary source of revenue for SaaS businesses and refers to the regular subscription fees paid by customers for using the software. Recurring revenue is usually based on monthly or annual billing cycles.
- New customer acquisition: This represents the revenue generated from newly acquired customers during the forecast period. This item takes into account the number of new customers expected to be acquired and their associated revenue, based on the chosen subscription plans.
- Expansion revenue: Expansion revenue is generated when existing customers upgrade their subscription plans, purchase additional features or services, or add more users to their account. This type of revenue indicates that customers find value in the SaaS product and are willing to spend more on it.
- One-time revenue: This includes any non-recurring payments from customers, such as set-up fees, training fees, or fees for custom development work. While these revenue sources may not be consistent, they can contribute to the overall cash flow.
- Churn (negative revenue): Churn represents the revenue lost when customers cancel their subscriptions. It is typically expressed as a negative value in the cash flow forecast, as it reduces the total revenue.
Remember that the specific revenue items in a cash flow forecast may vary depending on the business model, pricing structure, and the company's growth stage.
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What types of algorithms are used to produce a cash flow forecast?
Cash flow forecasts can be generated using various algorithms and methodologies, ranging from simple statistical methods to more advanced machine learning techniques. Some of the most common algorithms and techniques used for generating cash flow forecasts include:
- Historical Averages: This simple method involves calculating the historical average of cash inflows and outflows for each period (e.g., monthly or quarterly) and using these averages to project future cash flows.
- Exponential Smoothing: Exponential smoothing assigns exponentially decreasing weights to past data points to forecast future cash flows. Methods like Simple Exponential Smoothing (SES), Double Exponential Smoothing (DES), and Triple Exponential Smoothing (also known as Holt-Winters method) are commonly used, depending on the presence of trends and seasonality in the data.
- Autoregressive Integrated Moving Average (ARIMA): ARIMA is a time series forecasting method that combines autoregression (AR), differencing (I), and moving average (MA) components to model and predict future values based on past observations. ARIMA models can be useful in capturing the underlying patterns in cash flow data, such as trends and seasonality.
- Seasonal Decomposition of Time Series (STL): STL decomposes a time series into its trend, seasonal, and residual components, allowing for better understanding and forecasting of the cash flow data. This technique is particularly useful when dealing with seasonality in cash flows.
- Machine Learning Techniques: Machine learning algorithms like Random Forests, Gradient Boosting Machines, and Neural Networks can also be used to generate cash flow forecasts. These algorithms can capture complex relationships between various factors affecting cash flows and provide more accurate forecasts when trained on large datasets.
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What does a cash flow forecast look like?
A cashflow forecast contains a table of items in the revenue forecast category, cost of good sold category, and operating expenses category. It can be 12-months or longer depending on the predictability of your model.