Sales pipeline formula

While the sales pipeline is a cornerstone of B2B companies and their ability to monitor their financial health, it can be difficult to navigate. Yes, it helps teams visualize their sales process, track leads, and better understand lead generation, seller performance, and buyer behavior — but only if companies are able to effectively calculate their sales pipeline formula. And that can be tricky.

Read more about sales pipeline formula below.

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Sales pipeline formula

While the sales pipeline is a cornerstone of B2B companies and their ability to monitor their financial health, it can be difficult to navigate. Yes, it helps teams visualize their sales process, track leads, and better understand lead generation, seller performance, and buyer behavior — but only if companies are able to effectively calculate their sales pipeline formula. And that can be tricky.

First, sales pipeline calculations rely on a company’s sales pipeline stages being descriptive of the buyer’s typical journey. However, according to Gartner, today’s B2B customer journeys are complex and nonlinear — to put it lightly. Devising a sales pipeline that matches the complicated buying process is challenging. Second, organizations must consistently track and monitor data if they are to calculate the sales pipeline formula — which can be a time-consuming, error-ridden process if not done properly. Yet sales pipeline formulas are likely to be inaccurate without good data.

This article will explore various sales pipeline formulas companies can use to track their financial health and their sales team’s progress, in addition to how sales pipeline software driven by artificial intelligence (AI), such as Collective[i], can make determining sales pipeline calculations easier and more informative. But first, let’s explore what a sales pipeline is.

What is a sales pipeline?

At its most basic level, a sales pipeline comprises the actions taken by sales team members to drive prospects toward a sale — otherwise known as a conversion. The goal of every sales pipeline is to move prospects through the stages of the selling process as quickly as possible, either to the next stage or to the lost category so that sellers aren’t spending their time focusing on a deal they’re unlikely to win.

The term “sales pipeline” is also used to describe the stage of the buying process a prospect is in. It is important to note that the sales pipeline is grounded in the fundamental assumption that prospects go through a fairly typical set of stages on their journey toward buying. At each stage of the pipeline, these prospects learn more about the product or service and how it may (or may not) fit their needs, ultimately leading to a won or lost deal.

However, as Gartner points out, B2B buying has become less linear over time. In fact, B2B customers often engage in “looping,” or revisiting buying stages. As sales teams map out their typical buyer’s journey, identifying these loops and knowing how to account for them will be helpful in creating an accurate pipeline.

What are the sales pipeline stages?

A sales pipeline is not one size fits all. Instead, it varies from company to company based on the sales process used by sellers and revenue operations teams, internal data about a company’s typical buyer journey, and the level of nuance or detail a company wants its sales pipeline to contain. While some companies may swear by a five-stage pipeline, others may find more success with a six- or seven-stage pipeline.

No matter how many stages a company divides its pipeline into, the most important thing is that the pipeline realistically reflects the buyer’s typical journey. The accuracy and use of the sales pipeline calculations depend upon it.

Here is a list of general stages that companies can use as a starting point when creating or refining a pipeline.

Creating awareness and prospecting

The first stage in the sales pipeline is typically about drumming up attention and lead-generating tasks: e.g., marketing campaigns, cold calling, client referrals, social selling, and more. While responsibility for this stage used to fall almost entirely on sellers, that’s changing rapidly.

According to Gartner, when it comes to the B2B buying process, buyers spend approximately 45% of their time (27% online and 18% offline) researching independently without sellers. What this means for sellers is that they have less overall time to make an impression on a prospect, so their sales processes have to be top-notch.

Identifying interest and making an approach

In the second stage, prospects and sellers make contact. This typically happens one of two ways. First, sellers can make contact with potential buyers using the prospecting methods listed in the first stage. The primary directive here is to make contact with a sales qualified lead (SQL), aka those leads who have moved beyond general interest and are ready to talk to a sales team.

Alternatively, prospects can make contact with sellers themselves. Most often, this happens through contact forms on the company website or through social media sites such as LinkedIn. These leads may start as marketing qualified leads (MQL), after which they are connected with the sales team.

Identifying interest and prospecting leads has never been easier with digital tools that can provide insight into when and how to contact leads. For example, Collective[i]’s Intelligent InsightsTM provides every seller on a team with an optimized daily to-do list of the next and best actions to guide all sellers’ attention where it will make the most impact.

Handling objectives and making a decision

As deals have become more complex, so too has this stage of the sales pipeline. In fact, the typical B2B buying team has six to 10 people involved, all with their own opinions, needs, and pain points, according to Gartner. For sellers, this means managing objectives and opinions from several decision-makers all at once. Personalization and relationship building are key to successfully making it through this stage.

To help teams better address buyers’ concerns all at once, Collective[i] developed Virtual DealRoomsTM. With this tool, everyone involved in a deal can collaborate in a single digital space, making it easier for sellers to address big-picture concerns with the help of legal, marketing, customer success, and other teams.

Closing and taking action

In the final stage of the sales pipeline, deals are closed and prospects are converted into customers. While this is the objective, it’s not the end of the customer journey. Following a deal close is the potential need for training, implementation, ongoing support, and subscription renewals — and handling each of these things successfully can be the difference between customer retention and customer churn.

How do you calculate sales pipeline formulas?

There are a number of ways to track the growth and health of a sales pipeline, all with their own specific uses and purposes. Two of the most popular sales pipeline formulas are pipeline value and pipeline conversion rate. Additionally, basic sales metrics can also provide useful insights into a company’s pipeline.

What is pipeline value?

One of the best ways to understand the overall health of the pipeline is to track pipeline value — a numerical value that accounts for the overall estimated revenue size of all qualified prospects in the pipeline. To calculate pipeline value, simply add the estimated deal size for every deal in the pipeline, regardless of what stage it is in. More granular results can be calculated by filtering by region or sales representative, for example.

Alternatively, some companies choose to apply a weighted value to their pipeline. In this method, companies apply a probability percentage to how likely a deal is to close based on what pipeline stage it is in. For example, deals in stage one may have a 10% chance of closing, while deals that make it to stage three may have a 70% chance of closing. Companies use the weighted method to calculate pipeline value by multiplying estimated deal sizes by the probability of it closing.

No matter which method companies employ, pipeline value must be tracked long-term and continuously to uncover pipeline trends; only then can companies see whether the pipeline value is trending up or down, operating high or low during certain times of year, or rising or dropping based on the sales rep or region. All of this can help companies track their overall pipeline growth and health.

What is a pipeline conversion rate?

A pipeline conversion rate aims to measure the percent of leads that move from one pipeline stage to another in a given period of time. To calculate a pipeline conversion rate, two key pieces of data are needed. First, teams need to know the total number of prospects in a given time period in a given pipeline stage. Second, teams need to know how many of those prospects moved to the next stage in the pipeline after a certain amount of time. The sales pipeline conversion rate formula, then, is the number of remaining prospects at a stage divided by the total number of prospects at that stage in a given time period.

Pipeline conversion rates are tremendously helpful in sales pipeline management. By tracking the conversion rate, leaders can better identify areas for improvement in the pipeline and fine-tune sales processes to achieve better outcomes.

What are sales pipeline metrics?

One of the best ways to track the sales pipeline is to make use of a variety of key performance indicators (KPIs) tied to the pipeline. These metrics are designed to provide sales teams and leadership with a deeper understanding of the sales process and buyer journey, with the ultimate goal of identifying where there is room for growth and improvement. Some of the most useful sales pipeline metrics include:

  • Number of deals in the pipeline: This basic metric accounts for all of the qualified deals in a pipeline at a given time. Simply count the number of current prospects in the pipeline. Leads who are still in the early stages of marketing or awareness should not be included in this metric.
  • Number of deals in each stage of the pipeline: A company needs a firm understanding of the number of stages in the pipeline to accurately measure this metric. Using the stages laid out above, a company would measure how many prospects are in each of the four stages. Some companies may wish to measure how many of the leads are SQL versus MQL in this stage for more granular detail.
  • Average deal length: This metric measures how long it takes, on average, for a deal to move through the entire sales pipeline from open to close. To calculate average deal length, simply add the amount of time every closed deal took to win and divide that number by the total number of closed deals. Average deal length can be of particular use when developing sales forecasts and helps sellers understand when to phase out prospects who are dragging through the pipeline.
  • Average deal size: This metric measures how much revenue the average win generates. To calculate this, add up the total value of won contracts and divide that number by the total number of won contracts.
  • Win rate: This metric measures the amount of qualified leads that convert to wins over a given period of time. Essentially, this number measures how many prospects become paying customers. This is another metric that can be quite helpful in sales forecasting. To calculate the win rate, simply divide the total number of wins by the total number of qualified leads.
  • Deal probability: Deal probability informs how likely a deal is to close based on where it is in the pipeline. Essentially, deal probability provides a weighted percentage, so the further along a deal is in the pipeline, the higher the likelihood that it is to close. To calculate deal probability, determine the percentage of sales that close at each stage of the pipeline by dividing the number of closed deals in that stage by the total number of deals in that stage.

How can sales pipeline software improve this process?

Each of these calculations and metrics can be tracked the old-fashioned way, with spreadsheets, manual data entry, and annual updates in the form of a sales pipeline report. However, there’s a faster, more accurate way. Sales pipeline software can make quick work of each of these calculations, providing teams with actionable information. Additionally, advanced AI-enabled sales pipeline tools can help companies adapt more readily to market changes and better support buyers through their complex journey.

Collective[i]’s suite of tools is designed for busy sales teams who want to take the guesswork out of selling and free up more of their time to, well, sell. Collective[i]’s Predictive PipelinesTM provides sales leaders with on-demand inspection capabilities and pipeline health assessments. Sales managers can review pipelines and deliver critical information to agile sales teams without diminishing selling time. What’s more, analyses are augmented with coaching recommendations to help sellers improve their tactics — leading to more effective, higher-performing sellers.

If you’re ready to see the difference Collective[i] can make in your sales pipeline, get started today.

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