How to make a sales forecast (5 simple strategies)

An accurate sales forecast helps you get your goals straight, keep your planning tight and optimize your risk management. It also allows you to make better decisions for your business. Making a sales forecast takes quite some time and effort , though there are ways to make it easier.

For companies, drawing up a sales forecast is useful to determine their short and long term strategy. Businesses use sales forecasts

• To predict and manage their cash flow.
• For risk management and to anticipate problems.
• To determine and manage budgets.
• To estimate costs and make smart investments.
• To determine and predict their market position.
• To improve their sales process.
• To determine medium- and long-term objectives.
  To evaluate whether their company has a sustainable future.

There are various strategies to create an accurate sales forecast. You can base yourself on sales figures from previous years, supplementing them with other data such as future campaigns, general market trends, actions planned by your competitors, new products or services you are planning to launch, etc. Furthermore, you can determine the chance of conversion based on your lead’s position in the sales funnel or the intuition of your sales team.

For each lead in your sales funnel you estimate the likelihood of them becoming a customer. The most common logic is: the further a lead has advanced in the funnel, the greater the chance of conversion. That percentage should be multiplied by the value of the deal.

Let's say these are your conversion averages at each stage of a sale:

First contact: 10% of the leads in this phase eventually become customers

1. Follow-up call: 20%
2. Product demo: 50%
3. Proposal phase: 75%

A € 2000 deal in the proposal phase becomes € 1500 (2000 x 0.75) in your forecast.

A € 1000 deal where you have just given a product demo becomes € 500 (1000 x 0.50).

Add up all the deals in each phase of your sales funnel, and you will come to a fairly accurate estimate of the revenue you can expect.

The drawback of this strategy is that the average duration of a sales cycle is not taken into account. Some leads may postpone their decision for over half a year after they had a product demo. In that case, you probably wouldn't estimate this lead at 50%. While this strategy is accurate if you want to forecast your total revenue, it is less precise in predicting how long the sales process will take.

To make more accurate predictions about when you expect to close a deal, you can use the sales cycle. That is the average period between the first contact and the closing of a deal. If a total sales cycle takes 4 months, a lead has a 25% chance of becoming a customer 1 month after the first contact.

To apply this method properly, you will need to keep track of your communication history, starting from the very first contact. A tool like Teamleader automatically saves and links your communication to the right lead or customer. The Pipeline overview tells you how many leads are currently in your pipeline and which contact moments have taken place.

The first two strategies are based on average success rates, making it difficult to make predictions if you don’t have many historical data. That’s why for young businesses and start-ups it can be useful to make a forecast based on the intuition and insights of their sales team. What’s the potential of a lead, how specific is the problem your product or service will have to solve, which course did the conversation take, did they schedule a second appointment, …

This method is not very specific and often difficult to quantify. So, if you have more data, other strategies will be more efficient.
Do you want to follow-up your sales process more accurately? Managing customers and contacts with Teamleader is a piece of cake.

Companies that have been in business longer can base their sales forecast on historical data, comparing sales figures in the same period over several years. Large seasonal differences should be taken into account when defining the reference period. A dealer in swimming pools shouldn’t compare his order book of July with that of November last year.

If you can go back several years, you can even use the average growth figures. Use this benchmark to determine your average sales figures and set realistic targets for the upcoming period.

The most accurate forecasting method combines all of the previous strategies. The more data you have, the more accurate you can predict the future. For example, you can use the sales figures of previous years as a benchmark, then add the number of leads in the pipeline and multiply them by a probability percentage. That percentage can be calculated based on an average of three factors: the intuition of your sales people, the stage in the sales process and the average time it takes to convert a lead.

Simplified example of a quarter:

Lead X received a product demo and has been in contact with your sales team for 3 months. Typically, a lead will convert after 4 months. However, the sales rep thinks the lead is leaning towards the competition because of a difference in price and estimates a 25% chance of conversion.

Sales estimate: 25%

Phase

Product demo: 50%

Cycle

3 months: 75%

Based on these three factors, a lead has an average success rate of 50% (75+50+25 / 3).

Total number of leads

Suppose you have 20 leads in a quarter:

10 leads with a 75% success rate (=7.5)

5 leads of 50% (=2.5)

5 leads of 25% (=1.25)

Then you can expect about 11.25 conversions in this period (7.5+2.5+1.25).

To calculate the expected revenue you should also take into account the amounts of these deals. For example:

7.5 leads of €1,000 (€7,500)

2.5 leads of € 2,000 (€ 5,000)

1.25 leads of 3000 euro (€ 3,750)

Your expected turnover will be € 16,250 (7,500+5,000+3,750).

The combination of these strategies leads to a very accurate model, although it requires some complex calculations. If you are not using any strategy at the moment, it is best to start with one. If you already have enough data to apply one or two strategies, combine them to make your forecast more accurate and to gradually build a forecast strategy that helps you make better decisions.