How to use pipeline-weighted techniques for better sales forecasting

Sales forecasting helps predict new revenue and make informed decisions. However, without the right methodology it can lead to wrong estimates and wasted resources. 

Among the various sales forecasting methods, pipeline-weighted forecasting – a simple yet effective technique that factors in the likelihood of closing deals – stands out for its precision.

Assigning "weights" to each lead based on its probability of success helps businesses focus efforts where they matter most instead of relying on every lead to succeed. It helps identify high-potential opportunities and provides a realistic view of potential sales.

This article will help you understand pipeline-weighted sales forecasting and its benefits. We will also provide the actionable steps to implement it in your sales process.

What is a weighted sales pipeline?

A sales pipeline represents the progression of deals through the sales stages, from initial contact to closing. Pipeline forecasting helps predict sales based on the position of leads in the sales cycle. It looks at the entire sales cycle during a specific time period to estimate upcoming sales.

A weighted sales pipeline allows you to take your sales forecasting a step farther by assigning a probability of closing to every lead based on where it sits in the sales funnel. This method doesn’t just look at what’s in the pipeline but also how likely each opportunity is to turn into a win. 

This score is calculated considering the following:

• Deal progress: Each stage in the pipeline has its own probability. For example, a deal in the negotiation stage might have an 80% chance of closing, while one in prospecting might only have a 10% chance.
  
• Past data: Your sales history is key for predictions. If 75% of similar deals in a particular stage of the pipeline closed before, that can guide your expectations for current opportunities.
  
• Decision-maker influence: The decision-maker's authority matters. For instance, a deal led by the CEO will likely close faster than one stuck at lower approval levels.

Weighted vs. unweighted sales pipeline

The choice of whether to use an unweighted sales pipeline or a weighted sales pipeline can make a big difference in your forecast. So, let’s look at a few of the key differences between these two approaches. 

Unweighted sales pipeline

An unweighted pipeline is a simple approach that assumes every deal in the pipeline has an equal chance of closing. It calculates the total value of all deals without considering how likely they are to turn into actual sales.

Pros: 

• Quick and easy to calculate
• Provides a clear overview of total deal value
  

Cons: 

• Can be overly optimistic
• Doesn’t factor in the likelihood of deals closing

Weighted sales pipeline

A weighted pipeline assigns a probability to each deal based on its stage in the sales process, historical win rates, and the decision maker’s intent. Instead of assuming every deal will close, it provides a more realistic forecast by adjusting expectations.

Pros: 

• More accurate revenue forecasting
• Helps prioritize high-probability deals

‍Cons: 

• Requires historical data
• Probabilities need to be updated regularly to ensure reliable results

Here’s a quick comparison of using an unweighted sales pipeline vs a weighted sales pipeline in your forecasting:‍

SaaS businesses with longer sales cycles typically use a weighted pipeline to focus on deals that are more likely to close. Quota-driven sales teams can optimize resource allocation and improve lead conversion rates by focusing on high-value prospects as opposed to wasting time on low-probability leads.

‍Using forecasts created with weighted pipelines also help SaaS finance teams in their headcount planning and strategic budgeting. A weighted pipeline helps finance teams make more accurate predictions and thus help reduce budget variances as overly optimistic projections can lead to overspending if sales revenue falls short. 

‍Given the differences shown above, it’s easy to see how using a weighted pipeline for sales forecasting makes good sense. So, let’s look now at the key elements needed to implement a weighted pipeline method in your sales forecasting. 

The 3 key elements of a weighted pipeline

A weighted pipeline for sales forecasting begins with building a reliable framework for tracking and evaluating opportunities throughout the sales cycle that includes the following elements:

1. Deal stages

Most companies with a dedicated sales team use the pipeline model to guide their sales process. A sales pipeline includes all the stages that reflect the buyer's journey, such as prospecting (for outbound sales), lead qualification, the proposal or demo stage, deal negotiation, and closing. 

As deals advance through stages, their likelihood of closing increases, which when weighted, ensures a clearer view of the sales process.

While these stages shown above can vary a bit from company to company, the basic design and benefits of a weighted sales pipeline is the same – each stage represents a milestone that helps track progress, prioritize deals, and identify bottlenecks.

2. Probability assignment

Assigning probabilities to deals at each stage of the sales cycle is a key component of a weighted sales pipeline. Probabilities should be based on historical data and industry benchmarks where available. 

A weighted pipeline uses these probabilities to reflect the likelihood of closing, ensuring projections are data-driven and accurate.

We should note here that determining the right probabilities to assign at each stage can be difficult for early-stage startups that don’t have a lot of sales data. However, using a weighted pipeline is still preferable and they can refine their probabilities over time to make them increasingly more accurate. The important thing is to start.  

3. Deal value

Deal value represents the potential revenue from an opportunity and is essential for assessing its impact on overall revenue. 

SaaS companies calculate deal value using factors like contract length, subscription type, and potential user count. Standard subscriptions are simple to calculate, but custom pricing or multi-year contracts may need more detailed forecasting. 

When combined with probability, deal values help estimate the potential revenue in your pipeline.

Key metrics in a weighted pipeline

Tracking key metrics in a weighted pipeline provides insights into sales health and identifies areas to improve for better sales performance and ultimately increased revenue. The key metrics to track when using a weighted sales pipeline are:

• Deal value and probability: The deal value shows the monetary potential of an opportunity, while probability indicates the chance of closing it based on its stage and past data. Combining these two pieces of data for each deal helps sales teams estimate potential new revenue more accurately.
• Forecasted sales: This metric estimates the dollar-value of future sales by factoring in the probabilities associated with pipeline opportunities. It offers realistic projections and guides sales managers to set achievable targets.
• Total weighted sales: This is the sum of all weighted deal values in the pipeline and is used to calculate potential sales. Total weighted sales is a probability-adjusted metric that helps sales leaders evaluate the entire sales pipeline's effectiveness and prioritize resources.

Benefits of a weighted pipeline

A weighted sales pipeline provides realistic revenue expectations by improving visibility, forecasting, and resource allocation. Here is how it benefits SaaS businesses:

• Increased visibility into the progress of the sales pipeline: A weighted pipeline helps SaaS companies understand their sales pipeline and processes more clearly including where bottlenecks occur, and which stages need improvement. The insights gained can help handle pricing objections, refine sales strategies, and tailor demos, among other benefits. A quantifiable view of deal progression enables tracking of individual rep performance, providing insights into their strengths and weaknesses.
• More accurate forecasting: A common mistake in sales forecasting is assuming every deal will close. A weighted pipeline minimizes the uncertainty and improves accuracy by using historical close rates and deal probabilities to predict wins. Analyzing past forecasts vs. actual results helps refine probability assignments, making future predictions more accurate.
• Higher close rates and revenue growth: Focusing on the most promising opportunities leads to more successful sales outcomes. A weighted pipeline helps sales teams improve close rates by prioritizing high-value deals. Identifying roadblocks early helps sales reps to address them proactively to win more sales and ultimately generate more revenue.
  
• Efficient use of resources: Instead of chasing every lead with the same energy and effort, sales reps can prioritize deals with a higher probability of closing soon. Streamlining sales operations reduces wasted effort and speeds up deal closures, improving outcomes.
  
• Improved sales planning: Sales teams that rely on guesswork are likely to miss their targets. A weighted pipeline helps by enabling strategic, data-driven sales planning. It provides a clear view of deal progress, expected revenue, and possible challenges, allowing managers to set realistic goals and adjust strategies as needed.
  
• Improved efficiency and effectiveness in sales operations: Tracking deal progress, conversion rates, and sales in a weighted pipeline improves decision-making across the sales process. Sales managers can spot stalled deals and take corrective action, while reps can prioritize the deals they’re more likely to win.

How to use the pipeline-weighted method for revenue and sales forecasting

Here we provide a step-by-step guide on how to apply the pipeline-weighted method for accurate sales forecasting. 

Note that sales forecasting becomes much easier once you set up your weighted pipeline (Step 1). If you maintain it on an ongoing basis, promptly moving deals to the next stage as they progress, the weighting of individual deals (Step 2) will already be covered by virtue of where each one sits in the pipeline. 

Step 1: Identify stages and assign probabilities

The first step is to define the stages of your sales. It is important to note that vaguely defined pipeline stages can erode the benefits of using a weighted pipeline. So, your pipeline definitions should be specific enough that all sales reps know exactly where a deal stands at any given time. 

Once you’ve defined the stages, it’s time to assign each one a probability. Here, you’ll use your CRM data to evaluate historical close rates and use the insights to set realistic expectations. It’s also a good idea to look at industry benchmarks if available to help calibrate your thinking here.  

The probabilities you assign should indicate the likelihood at each stage of the pipeline that a deal will reach a successful close. Again, the basic idea here is that the more deeply engaged a prospect becomes in the sales process (i.e. the further down the funnel the prospect goes), the greater the likelihood that prospect will become a customer. 

Here’s an example of how you might define the stages in your pipeline and assign probabilities:

Step 2: Evaluate individual deals

Each deal in your pipeline has a potential dollar value. In this step, you’ll review all active deals in your CRM to assign a sales stage based on its current status. Then, assign a deal value based on the expected sale amount for greater accuracy. 

This step ensures that only qualified deals are included in the forecast and highlights deals that need extra effort to progress.

Note that deal values can change as the prospect moves into later stages of the pipeline, particularly in the negotiation stage. So, it’s important to update the deal values when needed to more accurately reflect the opportunity.  

Step 3: Calculate weighted values for each deal

The formula for determining the weighted value of an individual deal is:

Let’s say your SaaS sales team is managing three active deals, each at different stages of the sales pipeline. Using the values from our pipeline stages and probabilities table, you can apply a probability to each deal in the pipeline to estimate the expected new ARR they will generate for the company.

Suppose the deals are:

Now, applying the weighted value formula for each deal, we get the following weighted values:

This example shows how a weighted pipeline provides visibility to improve sales forecasting accuracy. As deals move through stages, their closing probability changes, so it’s important to regularly review and adjust these probabilities.

Step 4: Aggregate forecasted revenue

In this set, you’ll create a comprehensive sales forecast by adding the weighted values for all the deals in your pipeline, across all your sales teams and reps.

This provides a realistic sales forecast for the given period and helps finance and leadership teams make informed decisions.

In our example, based on current deals, your sales team can reasonably expect to generate $42,500 in new revenue: 

It’s useful to call out here that if you weren’t using a weighted pipeline, you would arrive at a much higher value ($80,000), leading to a potentially false sense of security that could result in falling well short of your targets. 

Step 5: Monitor and adjust

A sales pipeline is always changing, with deal stages and probabilities shifting over time. It’s critical to regularly update deal stages, adjust probability percentages, and recalculate forecasts to keep your pipeline accurate.

For example, if a deal moves from the Proposal (50%) to the Negotiation (75%) stage, its weighted revenue increases, improving the forecast. However, if a deal is delayed, its probability may drop, reducing expected revenue. This situation underscores the importance of defining your pipeline stages in a way that accurately reflects the realities of your sales process. 

Step 6: Analyze for trends and resource allocation 

Collect data over multiple sales cycles to make strategic improvements such as:

• Identify bottlenecks: If many deals stall at the proposal stage, it could be an indication of pricing concerns or a lack of follow-up.
• Refine probability estimates: Regularly compare forecasted vs. actual sales to adjust probability percentages for more accuracy.
• Allocate sales resources efficiently: Identifying high-probability deals helps allocate resources better by dedicating time, budget, and effort to the deals most likely to close.

For example, if you find that only 20% of deals move from proposal to negotiation, you can increase the conversion rate by improving demo presentations and handling customer objections.

Pain points of using the weighted pipeline approach for sales forecasting 

The weighted pipeline approach provides a structured and data-driven method for sales forecasting, but its accuracy relies on a few factors: 

• Data quality: A reliable weighted pipeline needs high-quality and up-to-date sales data. Incomplete, outdated, or inaccurate data impacts the forecast accuracy. The lack of historical data in early-stage startups makes probability assignments difficult.
• Subjectivity in probability assignment: Probability assignments in sales pipelines, though based on historical close rates, can still be subjective. Sales reps may inflate probabilities to appear more successful, while inconsistent assignments across teams and unaccounted external factors like market shifts can lead to forecasting inaccuracies.
• Potential for overestimation: A common issue with the weighted pipeline approach is that companies often overestimate their sales performance by assuming deals will progress as expected. This can lead to budget misallocation, over-hiring, and financial shortfalls when deals fail to close. The model also doesn’t factor in risks such as competition, budget cuts, and decision-maker turnover. Stalled deals may also stay overvalued because sales reps hesitate to downgrade them.

Forecast your sales revenue accurately with Drivetrain

CRM and sales forecasting tools help improve sales pipeline forecasting with real-time insights and automated probability calculations. With an FP&A tool like Drivetrain, you can take your sales forecasting even further to inform pipeline management and more accurate planning. 

Drivetrain enables you to:

• Automate calculations: Eliminates manual updating of formulas or consolidating spreadsheets. Drivetrain automatically calculates weighted values for each deal in the pipeline.
• Easier management of complex sales pipelines and processes: Drivetrain provides deep visibility into even the most complex pipelines and sales processes. Companies with multiple sales teams operating in different regions can easily bring them all together and drill down deeply into the data to extract key insights for better forecasting and sales territory planning. ‍‍
• Track progress visually: The easy-to-use Drivetrain dashboard shows current and projected revenue from all deals in the pipeline. It also helps identify potential bottlenecks and areas for improvement.‍
• Integrate with your CRM: Drivetrain integrates seamlessly with popular CRMs like Salesforce, HubSpot, and Zendesk, allowing you to import deal data directly into the tool for more accurate forecasting.

Try Drivetrain today to make your sales forecasting accurate and efficient.