Top 5 Sales Forecasting Definitions Every Salesperson Should Know

You need to forecast sales if you want to set goals and plan for the upcoming financial year. Leaders use data analysis to predict future sales because they can’t predict the future. Let’s be honest; forecasting is tough, especially when dealing with complicated sales situations with many factors to consider. Unfortunately, there are no magic wands to solve this issue, but some basic foundations need to be established.

Firstly, forecasters and all data collectors must agree on the same definitions for different forecast categories. Unfortunately, people often forget to do this simple task, which can cause confusion and inaccurate predictions. This article will talk about a framework that works well for creating precise sales forecasts. Knowing the top 5 sales forecasting definitions outlined in this article can help salespeople predict the performance of their sales team with more accuracy next year.

Definition # 1: Sales Forecast

This is the very bones of sales forecasts definition, also known as Intuitive Forecasting. It involves salespeople making informed assumptions about how much business will be done in a certain time frame. 

Let’s pretend you’re trying to predict your new company’s revenue. You lack any kind of historical information due to your company’s short lifespan (three months). However, two salesmen are at your disposal, so you consult them for an intuitive six-month sales projection.

Each sales rep evaluates their current transactions and future prospecting potential for the next months. They did the math and expected sales of $50,000 in the next six months.

When using Intuitive Forecasting, you put your faith in your salespeople. The first question you ask is when they expect the deal to conclude and how sure they are that it will. It considers the thoughts and feelings of the salespeople in the most direct contact with the customers and has the best idea of how things are progressing.

The drawbacks of this approach are obvious. It depends on the individual. Salespeople tend to be too optimistic, so expect them to provide high estimations. However, verifying this evaluation would require reviewing all communications between your sales representative and the customer, which is unnecessary additional labor.

Definition #2: Opportunity Pipeline

The sales forecasting approach known as “opportunity pipeline” considers where individual deals are in the buying cycle. Deal’s chances of success increase as it progresses in the pipeline.

You might report monthly or annually, depending on the sales cycle and team quota. Then, multiply each transaction’s value by its closure odds. 

Once you have done this for all the pipeline deals, you can get an overall estimate.

This sales estimate method is easy, but the outcomes are usually inaccurate. This is because the technique doesn’t consider the importance of seizing an opportunity promptly.

That is to say, as long as the closing dates remain the same, your salesperson doesn’t care whether a transaction has been in the pipeline for a week or three months. Therefore, it’s not always realistic to count on your sales team members to clear up their pipelines consistently.

Only relying on past data to predict future sales is a risky move during the opportunity stage. If you tweak your message, goods, sales funnel, etc., the percentage of successful offers at each stage will shift.

Usually, a company’s pipeline includes these stages:

  1. Lead generation
  2. Sales-accepted leads
  3. Sales offer/Deal proposal
  4. Deal finalization
  5. Closed/won

Now, let’s talk about lead scoring. 

Definition #3: Lead Scoring

In lead generation-driven forecasting, each lead source is evaluated and given a value based on the historical performance of leads with comparable characteristics. Putting a monetary value on each lead generator can help you estimate how likely they will become paying customers.

You’ll need to track the following KPIs to use this technique:

  • Prospective customers throughout the last month
  • Rate of source conversion to customer
  • Cost of goods sold on average

While this prognosis is based on facts, it is still subject to change. Your lead-to-customer conversion rates, for instance, may shift if your marketing team adjusts its approach to lead generation to reflect contemporary trends, resulting in a different total number of leads. These varied outcomes may be reduced by keeping up with developments and including them in forecasts.

Definition #4: Conversion Rate

The sales conversion rate measures how many leads are turned into actual customers. It’s a vital indicator in the sales process since it can tell you how well your marketing is doing, why transactions are falling, and how much customers value your products.

Although the primary emphasis of the sales conversion rate formula is on closed-won transactions, the residual percentage provides insight into the number of closed-lost deals. In addition, analyzing when leads enter the closed-won or closed-lost stage (at the top, middle, or bottom of the funnel) can provide insights to help sales and marketing make informed decisions about strategy and efficiency.

So how do we go about doing that? 

Naturally, we put in a new equation:

The value is calculated by taking the total number of conversions times their per-customer lifetime value.

You may be wondering what factors go into calculating the conversion value. That will need a little more arithmetic, but don’t worry; I’ve got you covered.

Look at how much money is being made of each lead to get an idea of the conversion value.

Five leads generating $5,000 in income work out to $1,000 in revenue per lead.

The calculation for this is as follows: 750 times $1,000 gives us $750,000.

It translates to an estimated value of $750,000 for this supply.

Definition #5: Sales Cycle

In order to estimate when a given opportunity is likely to close, the sales cycle duration is often used.

Using this method, you won’t have to worry about getting an overly generous prognosis since it is based entirely on objective facts rather than the rep’s comments.

Imagine a scenario in which a salesperson schedules a demo with a lead before they are prepared to receive it. The approach may conclude that the prospect is not ready to purchase just yet, even though the salesperson has been in contact with them for a while.

It’s also possible to use this method throughout many sales cycles. For example, sales cycles for various types of leads may vary widely, from a few weeks for a referral to many months for leads acquired at a trade show. In this way, you can categorize deals based on their typical sales cycles.

Tracking the timing and method by which leads are added to the pipelines of your salespeople is essential for obtaining reliable data. In addition, there will be a lot of double-entry if your CRM doesn’t sync with your marketing platform and automatically register interactions.

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