How successful companies improve revenue planning by more accurately forecasting new bookings

Think of revenue planning like a game of chess, where every move impacts your chances of winning. Each new booking is a calculated move on the board—a contract that improves your recurring revenue and sets the stage for future wins. But just like in chess, success for SaaS companies doesn’t come from reacting move by move.

SaaS business leaders must think like grandmasters to forecast new bookings accurately so they can. Yet, building realistic assumptions around new bookings remains one of the toughest challenges for finance teams. Too aggressive, and you risk missing targets. Too conservative, and you may miss opportunities for growth.

Creating accurate revenue forecasts doesn’t have to be a guessing game, though. Using a data-driven approach will make your forecasts more reliable. Modern FP&A tools can help you project revenue by combining historical data, market trends, and the health of your current sales pipeline.

This article will help you more accurately forecast new bookings for your revenue forecasts, explaining the pitfalls to watch out for and how technology can help you get it right.

Significance of new bookings in revenue planning

For SaaS companies, new bookings represent the total contracted value from all newly signed agreements with new customers within a specific period. Upgrades and expansions also fall under new bookings as they introduce fresh terms and higher revenue commitments. 

New bookings represent future financial inflows rather than current revenue, making them an important forward-looking metric for cash flow forecasting and predicting future revenue growth.

Accurately forecasting new bookings helps finance teams in the following ways:

• Anticipate working-capital requirements: SaaS companies must make upfront investments in customer acquisition or operational expenses before revenue is fully realized. Accurate forecasting of new bookings predicts when the cash will arrive, helping to ensure liquidity and avoid financial issues.
• Indicate growth and financial health: SaaS investors use booking trends to assess pipeline health and sales performance. Accurate forecasting builds trust by showing proactive planning and readiness for different scenarios.
• Measure sales performance and market demand: By analyzing contract volume and value, SaaS companies can identify effective sales strategies, popular products, and shifts in market demand. A rise in bookings suggests high demand, while a decline may point to high competition and the need for strategic adjustments.
• Guide resource allocation: Projecting revenue from new bookings helps evaluate investment decisions. You may need to hire additional customer success staff, scale server capacity, or invest in product enhancements to support the growing customer base. Conversely, lower revenue might require cost-saving measures.

Integrating new bookings data into revenue planning helps SaaS businesses align financial goals with sales velocity to ensure growth and flexibility.

Timing and phasing of bookings and why they are important

Understanding the timing and phasing of bookings will help align revenue recognition with your operational plans.

Timing of bookings

Timing of bookings refers to when bookings are recognized for the purposes of forecasting and reporting. In forecasting specifically, it provides a preview of future revenue and cash flow based on committed contracts.  

For the purposes of revenue forecasting and planning, it’s important to note that bookings are not a standardized Generally Accepted Accounting Principles (GAAP) metric. So, when they are recognized as revenue can vary from company to company. 

Revenue—and when it can be recognized—is altogether different. Revenue is a GAAP metric that’s required for public companies (and generally followed by private companies) for financial reporting.

With specific rules/guidelines in place for SaaS revenue recognition, it’s important to consider the timing of bookings when forecasting revenue because how you do it has the potential to skew the results of your forecast.  

So let’s look at the different milestones at which a company might choose to recognize new bookings and the potential impact that might have on revenue forecasting and planning:  

• Commitment date: The commitment date is when the project has made a verbal agreement to buy and is ready to proceed to negotiations and/or contracting. Recording a booking on the commitment date provides a clear picture of sales performance in real-time, but for the purposes of revenue forecasting, leads to premature revenue expectations as payments or service delivery happen later (or not at all if for some reason, the deal falls through). 
• Contract signing date: Most SaaS companies recognize their bookings on the contract signing date. While this approach provides a more realistic view of sales performance, basing revenue projections on the contract signing date can bias the results because it “counts” revenue earlier than it can actually be recognized. This may not be as significant for companies that deliver services immediately upon contract execution because there’s less of a time lag between the recognition of bookings vs. the recognition of revenue.   
• Kick-off date: B2B SaaS companies usually have a formalized onboarding process for new bookings, and the kick-off date marks the beginning of that process. For these companies, contracts often include a one-time implementation or setup fee (professional services) before subscription billing begins, which is usually paid upfront. Some will use the kick-off date to create their revenue forecasts because payment of these fees upfront means they’ve started realizing revenue from the project. While this can help to mitigate the distortion in revenue trends that the previous two approaches creates, recognizing subscription revenue from this date still won’t be accurate unless the customer has started using the core product.
• Go-live date: The go-live date is when the customer starts using the product. Aligning revenue forecasts with the actual delivery of the subscription services for new contracts will always provide the most accurate picture of the revenue they will generate over time and a clearer picture of financial health. 

Getting the timing wrong between new bookings and service delivery can disrupt revenue forecasts, cash flow planning, and financial reporting. Capturing booking timing accurately ensures your revenue plan aligns with actual business activity and stays compliant with regulations. 

Phasing of bookings

Phasing of bookings refers to how the revenue from new bookings is distributed over time and when it can be recognized. When a contract is signed, the full value of the contract is recorded upfront as a new booking, including recurring (subscriptions) and non-recurring (implementation fees) components. However, revenue is recognized gradually as the services are provided throughout the subscription period.

In standard subscription-based SaaS models, revenue is recognized only when the service is delivered. The same applies to usage-based models as well. While it can be a bit trickier to predict, phasing revenue according to customer consumption prevents overestimating revenue in slow months and highlights when costs to deliver services will spike. It ensures an accurate reflection of earned income and supports better margin management.

SaaS bookings usually spike at the end of months or quarters due to sales incentives. You may also notice seasonal fluctuations, such as slowing down in summer or during holidays. Failing to phase these peaks and valleys can result in misleading month-over-month growth rates and unexpected revenue recognition, which complicates budgeting and investor communication.

How to forecast new bookings for revenue planning

Forecasting new bookings for revenue planning requires analyzing data from sales, marketing, and operations teams. SaaS finance leaders can use the insights to plan headcount, budgets, and growth investments. Here is a structured approach to forecasting new bookings to help with precise revenue planning:

1. Analyze historical performance

Review booking data to identify trends, seasonal patterns, and growth rates. Analyze metrics like sales cycles, conversion rates, and average deal sizes to set a baseline for future projections.

‍2. Review the sales pipeline with weighted probabilities

‍Use pipeline-weighted forecasting to assess your sales pipeline. Assign a probability to deals based on their stage, like 10% for discovery or 60% for proposal, using past close rates. Multiply each deal’s value by its probability to get realistic outcomes.

3. Incorporate current market trends

Stay up-to-date on market trends like competitor moves, economic changes, and customer demand shifts. Use insights from research and reports to adjust forecasts and keep projections accurate. For example, a new industry regulation might increase demand for compliance-focused SaaS solutions.

4. Collaborate across teams

Collaborate across sales, marketing, and customer success teams to validate assumptions and get a holistic view. Sales share pipeline updates, marketing provides lead generation trends, and customer success highlights upsell potential and churn risks.

5. Factor in timing and implementation delays

Keep in mind the time lag between signing a contract and recognizing revenue. For example, if onboarding takes two months, January bookings won’t generate revenue until March. In usage-based pricing models, you must also consider ramp latency as customers may take time to fully use the service, which affects revenue timing.

6. Distribute bookings across the timeline

Distribute forecasted bookings across periods based on close dates or historical trends to align them with revenue schedules. This helps smooth out any fluctuations in revenue and provides a more accurate representation of the company's financial performance.

7. Update the forecast regularly

Revisiting your forecast regularly to update it with new data like changes in your pipeline or market shifts is one of the best ways to prevent missteps in your planning.

Importance of accurate assumptions when forecasting new bookings

As with any type of forecasting, predicting new bookings requires some assumptions. The more data you have to inform your assumptions, the more accurate they will be. To forecast your bookings, you’ll need the following:  

• Sales pipeline data, which tracks potential deal value and the time it takes to get from initial contact to closure, which helps to determine the timing and phasing. Historical data can help you calibrate your assumptions here. 
• Conversion rates, which measure the lead percentage that becomes customers, providing a critical metric for predicting bookings.
• Churn rates, which are important for predicting the impact that early contract  cancellations may have on the revenue that might be realized from new bookings.  
• Market data, which includes any information on your competition, economic conditions, and customer needs that can help you better quantify demand for your product.

The most important thing to remember about your assumptions is that they’re never going to be 100% spot on. No matter how well you know your customers and your business, there are external factors that can impact your forecast. 

That’s why you need to regularly revisit your forecasts and the assumptions you used when creating them. We get it, though. The larger and more complex your business is, the more data you have to consider. Working with different teams to gather and review all the data you need can make forecasting bookings a heavy lift. So, it may be tempting to simply ride out your forecast until it’s time to create the next one. If this rings true to you, your business has probably grown to the point where it’s time to consider investing in revenue planning software or a more comprehensive financial planning and analysis (FP&A) solution.  

‍Regularly re-evaluating your assumptions will always lead to more accurate predictions. This is true no matter what type of forecasting you’re doing. Revisiting your new bookings forecasts will help you avoid overestimating or underestimating the new revenue your sales team will win for your business and when the cash from those deals will  start flowing. 

Common pitfalls in developing assumptions 

Mistakes in forecasting new bookings impact your bottom line. Here are common pitfalls to avoid:

• Poor data quality: We’ve all heard it at one time or another: Garbage in, garbage out. It’s always important to validate your assumptions with data, but it needs to be good data. Inaccurate, incomplete, or inconsistently tracked data weakens forecast reliability. Using an FP&A platform like Drivetrain eliminates this problem by eliminating the need for spreadsheets (which are notoriously prone to human error) through automated data consolidation and validation.
  
• Confusing bookings with revenue: Mistaking new bookings (future revenue potential) for revenue (money already earned and flowing into the business) distorts financial projections by artificially inflating performance.
• Ignoring early churn: Overlooking patterns in contract cancellations overestimates future revenue, which can lead to overstaffing or excessive spending. Churn always impacts long term growth, but not factoring it into revenue forecasts is particularly damaging for companies that deal in multi-year contracts.
• Biased projections: Unrealistic assumptions can lead to forecast errors, causing over-hiring, overspending, or missed opportunities. For example, it’s not uncommon for sales teams to be overly confident in their ability to close deals. So, when forecasting new bookings, it’s important to not only critically evaluate your own assumptions but also any pipeline assumptions for potential bias.   
• ‍Overlooking variance: Variance in service delivery leads to distorted projections and poor decisions. Pessimistic assumptions with positive variance can result in missed opportunities. Optimistic assumptions with negative variance may result in cash flow issues due to overstaffing and overspending. If you’re regularly reviewing your forecasts vs. actuals and conducting a revenue variance analysis, you’ll probably catch these patterns early on.  
• Neglecting seasonality and market trends: Not all businesses have a seasonality component but every business can be impacted by market trends. Failing to account for seasonal trends in new bookings or market shifts that might impact them will decrease the accuracy of your forecast overall and mess up your predictions regarding cash flow, which can have serious operational consequences.   
• Lack of collaboration: Forecasting without input from sales, marketing, or customer success misses key insights. While it’s probably easier to simply request the data you need for your forecasts, failing to ask for and incorporate the insight and information from teams closer to the action that’s creating the data you’re using is shortsighted. Actively collaborating with them will give you a better understanding of the limitations of the data and surface additional information you might not otherwise be aware of that could impact your forecast. 

Best practices for effective forecasting of new bookings

The following best practices will help improve the reliability of your new bookings forecast:

• Ensure data sanctity: The data used will impact your forecasts, so you must use robust systems to maintain accurate and consistent data across departments.
• Leverage historical data for scenario analysis: Use past booking trends to create realistic assumptions and test them with various scenarios for reliability. Scenario planning software makes this easy. 
• Account for timing and seasonality: Consider seasonal surges and booking phases to align forecasts with business cycles and ensure proper resource allocation.
• Regularly review and adjust: Compare forecasts with actual performance to update assumptions based on new data and market trends to maintain accuracy.
• Avoid overly complex models: Use a forecasting model that strikes the right balance between complexity and the accuracy you need in your forecast. Generally, the more  straightforward your forecasting model is, the less error-prone it will be. With any model, it’s important to document assumptions for transparency and future reference.
• Collaborate: Actively involve sales, marketing, and customer success teams in your revenue planning processes to validate assumptions for a well-rounded approach.
• Monitor metrics: Make sure you have systems in place to track all the data you need for forecasting, including key metrics like new bookings, MRR, churn, and conversion rates, to refine forecasts.
• Leverage technology: Use an FP&A platform or other software capable of integrating with all the different systems that contain the data you need, so you can jump straight into your modeling instead of spending days consolidating and cleaning up the data from multiple spreadsheets before you can even begin to create your forecast. 

Turn assumptions into accurate revenue plans with Drivetrain

Accurate revenue planning begins with robust assumptions and reliable financial forecasting. From monitoring new bookings metrics to handling the complexities of timing and phasing, there are several key components to forecasting new bookings. 

Drivetrain streamlines financial planning and improves forecasting accuracy with more than 800 integrations that can automatically consolidate and validate the data you need from any system it resides in, including CRMs, accounting systems, ERPs, and billing platforms. 

Using Drivetrain makes tracking new booking metrics effortless. Once you integrate your systems, you’ll have real-time insights into how the numbers are changing so you’re never caught off-guard by an emerging trend. 

Reviewing your forecasts and making adjustments is easy in Drivetrain because your data is always instantly available and always up to date. When the data changes, your models are updated, too. And its powerful multi-scenario analysis tools help you stress-test the accuracy of your assumptions to root out any bias and refine your forecasts. 

You can also monitor implementation timelines and align forecasts with revenue recognition schedules to improve cash flow forecasting, to help ensure smooth operations. 

Explore Drivetrain today to see how easy it can be to create accurate revenue models for your SaaS business as new bookings roll in.