Like a crystal ball, sales forecasting will surely not show you an exact view of the future. However, it will do give you some predictive insights into what is likely to happen in a specific time frame in context to your sales. Based on those predictive insights, you will be able to make well-informed decisions for achieving better sales outcomes.
Thus, sales forecasting is essential for any sales-driven organization. Yes, an exact view of the future isn’t possible, but there needs to be some accuracy in your forecasting.
Providing a forecast of $100M in revenue for next quarter to the board and delivering a $40M result leads to disappointment.
With inaccurate forecasting, you end up putting your job and reputation on the line.
While forecasting, you cannot depend on your gut on bad data; it will lead to misinformation and unmet expectations.
Unfortunately, many sales managers and reps struggle to get accurate sales forecasting results.
So what can be done to turn the ship around and forecast effectively? We’ve created an in-depth guide that will help you increase the accuracy level and forecast effectively.
In this blog, you will read about the following things-
Sales forecasting is a data-focused assessment of possibilities. It is an indicator projecting the level of sales the company can expect to attain within the planned period. It is a source of valuable information that can be used to create new strategies, set targets, and identify opportunities and risks in real-time. Accurate forecasting can help a sales team function more efficiently and achieve as well as excel sales expectations.
When we have a slight idea of what’s ahead, we can create a course of action to achieve success. Sales forecasting leads the sales reps in the right direction. It helps in sales planning.
A forecast build on a solid ground minimizes the guesswork and helps allocate resources effectively.
A sales forecast even helps the financial team of a company understand how much cash will flow into a business. It gives a clearer understanding of how to use the capital and makes it possible to calculate the profit for a given period.
Sales forecast helps in measuring a company’s health. A company’s success can be measured by how well the sales team meets the sales forecasts and contributes to revenue growth.
For instance, if the sales team is only achieving 20% of the estimated sales figure, it is a matter of concern. More efforts and performance improvements will be required to take the company on a lucrative path.
Here are a few internal factors that can affect your sales forecasting.
Internal organization changes bring a certain level of uncertainty and affect the numbers. Changes in prices, advertising, quality of products, etc. can greatly affect future sales. So if your organization is set to go through any changes, you must factor them in your forecast.
When a business expands into new territory, assigns different territory to a sales rep, or a new territory management plan is introduced, there are possibilities of a temporary dip in sales. These changes will impact sales forecasting. It takes time for sales professionals to adapt to a change and adjust to the new territory. However, once they explore and familiarize themselves with a new territory, you can expect the sales to rise to an even higher point.
Pay close attention to different policy changes, and even they can affect sales forecasting. Internal policies like sales promotion policy, advertising policy, pricing policy, profit policy, etc. are vital factors that influence an organization’s estimated sales.
Oh! There are even a few external factors you need to pay attention to
When the economy is strong, buyers will show interest in your product and invest in it. However, during a crisis where the economy is affected, this would seem difficult.
For instance, the 2020 COVID-19 crisis, that has crippled the global economy. Many businesses are affected due to this sudden pandemic. So, the sales forecaster must consider the general economic situation- inflation or deflation, which can affect the business favorably or adversely.
The changes that the competitors implement might capture the potential buyer’s attention and affect the estimation to a great extent. For instance, if the competitor suddenly uses the price reduction strategy to increase the product’s demand, that might affect your win rate. You need to keep an eye on the competitor and act instantly. If they slash the price, you will have to offer discounts to stay in the game.
The changes happening in your industry can have a great impact on your forecasting. So stay abreast of the industry’s know-how. Your industry’s growth rate, advanced technological improvement, changing Government policies, etc. must be carefully observed. You need to stay alert of the new players who are entering your industry and offer a similar solution at a cost-effective rate.
Through time-based forecasting, you can predict sales for the next few months or even next few years.
Short term forecasting is also popularly known as operating forecast. It can be calculated monthly, quarterly, bi-annually, or annually. Short-term forecasting helps set realistic quota, make smart hiring decisions, and estimate the profit over the sources used. Short-term forecasting is ideal for projecting sales and revenue for businesses experiencing rapid changes in market or demand.
Long-term forecasting focuses on the overall goals of the company. The sales projection periods are generally 5 to 6 years or more. In-depth knowledge of the performance and current industry trends are required to predict the company’s growth in the coming years.
An accurate sales forecasting process can help in pulling more revenue for your company. There are several methods used for sales forecasting. The selection of a method depends on different factors like the forecast’s context, the specific period to be forecast, the availability of historical data, etc.
Here are a few sales forecasting methods used by most of the sales team. I have even given some sales forecasting examples that can help you in implementing the method.
Using the lead value method, you can measure how much a lead is worth, based on the potential revenue a lead represents and its probability of converting into sales.
Both sales value and conversion rate should be considered to calculate the lead value.
Sales value is basically the amount of money you stand to make from a sale. Leads come from different sources; therefore, they are of different types.
So the sales values of the leads are also often different as per the source.
You may find that leads that requested a demo closed at $3000 per customer while the leads from paid advertising closed at $1000 per customer.
Lead-to-sales conversion rate refers to the percentage of leads that pass through the entire sales pipeline and convert into paying customers. Just like the sales value, this metric will vary depending on the lead source you are looking at.
You may find that the leads that requested a demo have a 40% conversion rate, while only 10% of paid advertising leads convert into customers.
Once you know both the sales value and conversion rate of a lead coming from a specific source, you can just multiply those numbers to calculate the formula.
Lead Value Formula
Lead Value = Sale value x Lead-to-sale conversion rate
You can use the value assigned for each lead to estimate revenue results for your current sales pipeline and identify necessary adjustments need.
You have 30 paid advertising leads valued at $600 each and 200 demo leads valued at $100 each. If you add up the lead value for every lead in your pipeline together, you can find the forecast sales of $38000
Lead value sales forecasting example
30 paid advertising x $600 lead value= $18000
200 demo leads x $100 lead value= $20,000
$20,000 +$18000= $38000 is the projected sales.
B2B sales isn’t as simple as a customer walking into a store and picking his/her choice of shoes. Each sale in B2B from beginning to end goes through various stages within a sales cycle before the deal is closed and the product is purchased. The sales forecast here is determined based on the outcome of each deal.
While using the opportunity stage forecasting, the entire pipeline is broken down into various stages. Well, the opportunity stages will differ from company to company.
You just need to determine what will the journey of your customer be in the buying process.
Basically, the stages should reflect the number of interactions you will have with a customer.
Prospecting-discovery call-appointment setting-presentation-proposal-Negotiation-closed won/loss
The purpose of each stage is to hold different weights within the sales process.
More weight is given to the opportunities stages that are further along in the sales pipeline as the weight determines the likelihood that the deal will convert into a sale. This helps you in identifying which leads will become opportunities. You simply need to multiply each deal’s value with the likelihood of closing the deal to create a sales forecast for a specific period.
Opportunity stage forecast example
Suppose you’ve created the following likely-to-close percentage based on your pipeline.
Prospecting – 10%
discovery call – 20%
appointment setting – 40%
Presentation-proposal – 60%
Negotiation – 80%
closed won/loss – 100%
Apply the opportunity stage forecast formula
Deal value x likelihood of closing = expected sale
As per this forecasting model, a $2000 deal at the appointment setting stage is 40% likely to close. The forecasted amount for the deal would be $800.
The past, without a doubt, has a wealth of information. It can be an excellent base for forecasting. In historical forecasting, you just need to look back at your past performance within a certain time frame and assume that your future performance will be equal or superior to it.
Historical forecasting is a simple forecasting method, but it is cent percent safe to use as it assumes that buyer demand will be constant, which is no way a given. There are risks of overestimating your sales statistics and operating using an inaccurate sales forecast.
Historical forecasting is ideal for businesses looking for a simple and quick way to project how much sales they will make in a given period.
Historical forecasting example
Suppose your team collectively made $60000 sales in monthly recurring revenue(MRR) in January. So you can assume that the team will make $60,000 more in February also.
There is even another way of projecting sales using historical forecasting. You can reflect on the past sales data and look at each month’s growth. If you consistently increase sales by 5-6% each month, then you can estimate 63000 to 63600 sales for February.
Sales reps deal with clients daily. They have an idea of how much time it takes to close a deal. So most sales managers prefer to ask the sales rep to estimate the sales amount they can achieve in a month and accordingly set the target. Using this sales forecasting method often helps boost the conversion ratio as a sales rep knows which deals have the potential of closing and accordingly puts the number forward and tries to achieve it.
However, there can even be a problem if the sales rep is too optimistic by nature and gives over-generous estimates.
This method is suitable for the early stages of a product or for a startup with no historical data that could be analyzed to create a sales forecast.
Intuitive forecast example
Let’s say you have just started a new business and hired a sales professional. You’ve just been operating for the last five months, so you don’t have any historical data. You ask the sales professional to forecast the sales for the next four months.
This will help you in setting an achievable target for your new sales rep. The sales rep mulls over the prospecting opportunities and even evaluates every deal in the pipeline. Based on that, analyze s/he provides a forecast of $10000 for next quarter.
For using this effective sales forecasting method, you need to have a closer look at every opportunity in your sales pipeline. Based on your average win rate and the opportunity’s value, you need to calculate the chances of closing each deal.
This method is highly dependent on the quality of your data. If you use imperfect data, then you won’t get an accurate sales forecast. So it is better to use the best CRM software and update it regularly to ensure your data is reliable.
Pipeline forecasting example
Suppose you close a deal worth between $1000 to $3000 within 30 days, so all the deals in your pipeline within that value can be closed in the next month. So like that, you can forecast monthly or quarterly sales.
Sales forecasting can get complicated at times. As the team’s head, you must have a structured plan for forecasting to ensure seamless success.
Here a few tips for better forecasting:
Most of the companies aim to deliver more profits and sales than the previous year. However, the problem is that they try to do that without understanding what the key drivers of the performance are, and this affects their decisions. So it is important to measure the impact of actions and circumstances that have contributed in the past.
Establish a baseline that is structured around the relative changes in the activities. This baseline creates a start point understood by all. By this approach, it is possible to overlay new or extended activities that can be prioritized to deliver the required budgeted sales growth.
Percentage probability is an effective technique used to manage the uncertainty inherent in sales forecasting. It is also popularly known as weighted probability. The concept recognizes that not every deal will convert into a sale and assigns a probability percentage to each estimated value. It calculates the percentage by weighting the particular characteristics of a deal. When the estimated value of each deal is adjusted by the weighted probability, the pipeline’s total value gives the estimation of what the outcome will be.
Too complicated? Well, let’s look at a hypothetical situation to get a better understanding.
You calculate your team, as a whole, wins 3 of every 10 deals. If there are 30 deals for next quarter you can forecast to win 9 of them. If the average sales value in the pipeline is $5,000, then your forecast for the next quarter might be 9 deals at an average of $5,000, which is $45,000
In this above example, every deal is assigned a weighted probability of 30% at $5,000, which is $1,500.
Percentage probability gives you more clarity and helps you get more accurate forecasts, not only for individual deals but also for the pipeline.
Get a commitment from the team
For getting cent percent positive results, your team’s commitment is necessary. If the deals forecasted to close get little or no attention, that might affect the estimated sales. So ensure your team pays equal attention to each and tries to close them in real-time.
Even point out the stalled opportunities that your team has in the pipeline. Ask them to actively work on either reviving them or purging them from the sales pipeline.
Marinating accuracy while forecasting can help you improve your win rate. Here are a few things that you must do to improve your forecasting accuracy.
Keep track of your sales cycle. There are chances its length would change with the economy, industry shifts, and customers’ demands. A fluctuating cycle impacts forecasting accuracy. So regularly evaluate the length of your sales cycle. Doing so makes it easier to predict how many deals you’ll be able to close in next month or quarter,
CRM is a powerful tool that can help in forecasting sales. You can see the win probability of the deals and strategize accordingly. However, this tool needs to be used in the right way. If your data in the software is bad that you cannot even expect close to accurate results.
So keep your CRM updated. Don’t let a deal relax in one stage for too long. Take real-time action and remove deals that won’t convert at the right time. As your conversation proceeds with any prospect, keep updating it in the CRM system. Sloppy record-keeping will blur your sales forecasting image.
The more actions a prospect takes, the faster the deal will progress and close. So move the deal from one stage to another based on the prospect’s action rather than the other way around.
Most sales reps set criteria and move the deal forward when they meet the criteria instead of moving it forward when the prospect meets the criteria. For instance, a sales rep shouldn’t move a deal forward when s/he is about to set an appointment(and disrupt the forecasting), The deal should move forward when the prospect agrees to meet.
Consistency is pivotal in sales. Once you find a useful forecasting model, stick to it. Do not change it every month. If you received close to accurate results for two months but couldn’t get the same positive result in the third month, then do just instantly think about changing the forecasting model. Try to find the reason for the failure. There could many reasons, as I mentioned earlier, that could affect your sales forecasting. When you stick to one model, you get a standardized format that is easier to review.
Sales forecasting isn’t an easy game to play. You need to gather a lot of data, set goals, choose a method, and analyze it regularly. Besides, you even need to stay abreast of the internal and external factors that can affect your sales forecasting. If something isn’t working, don’t directly jump to another forecasting method. Ponder over the reasons and see where you are going wrong. Find out what needs to be changed in your current process.
For a high level of accuracy in sales forecasting, you need a good quality of that. For that, you can rely on smart CRM like Salesmate that allows you to store all your data in a centralized repository. It makes sales forecasting easier for you. You can easily see the target achieved by your team in the last quarter or the deals that are about to close. You can quickly get the predictive insights to make informed decisions. As I told you Salesmate is a “smart” CRM so it allows you to do a lot more besides forecasting. You can create a sales report, manage your sales pipeline, create email sequences to follow up in real-time, automate most of the time-consuming processes.