What is Sales Forecasting? & 6 Methods of Forecasting SalesPublished on July 25, 2018
Sales forecasting refers to the process of making an educated guess about the probability of future sales. You can do this by making utility of historical data and logic to estimate sales over a given period. The time frame maybe weekly, monthly, quarterly or yearly-based.
Understandably, many people fail to draw a distinction between sales forecasting and goal setting. To differentiate the two, you need to think of sales forecasting as a process of conceptualizing a realistic representation of what an individual or team can earn in a given window period. In contrast, goal setting majors on the ambitions of the unseen best-case setup.
Sales forecasts are important because they allow companies to spot issues before they occur. In doing so, companies are able to plan strategies to counter specific shortfalls and cope. Early detection also means that they don’t have to wait until the very end of a quarter before making corrective adjustments.
For employees, sales forecasting has intrinsic importance in terms of attaining set targets. Making sales forecasts on a regular basis helps motivate employees. It also ensures that they are always on their feet around the workplace. To streamline the process, an accord needs to be reached on how to count leads getting into the sales funnel.
Having a CRM system at the ready also ensures that all interactions are tracked for better estimates. When properly utilized, CRM can help reveal funnel analytics, aid in lead tracking, call cadences and report generation.
Methods of Forecasting Sales
1. Buyer Survey
To get started on this particular sales forecasting method, you need to compile a list of all prospective buyers. After that, you should prepare a face-to-face interview with a particular group of willing buyers. Questions about brand preferences, product pricing, desired features and probable purchase can be freely asked.
From the interview, you will be able to find out the level of interest prospects have in your products and/or services. This data is important since it will help you know for sure the volume of products you can offload through sales. Many salespersons reckon that among the methods of forecasting sales, this one offers a more practical approach. Industrial marketers with physical products also prefer this approach. The reason being that it gives them tangible estimates.
2. Opportunity Stage Forecasting
When it comes to forecasting sales, you need to have an idea of just how further along the sales process prospects are. By making use of opportunity stage forecasting, you obtain the odds of an opportunity to close based on their progression through the sales process.
Since this is a logical technique, you can make estimates about the chances of a prospect to close a sale by using mapped out data. From your data, you can derive a mean sales cycle of a product and compare that to the sales process. Typically, the sales process ranges from early-stage awareness to the final point where a decision is reached. All you need to do is locate where along the sales journey a prospect is and make a comparison to the mean estimate.
This technique of sales forecasting is not exactly accurate. This stems from the fact that it doesn’t take into account the individual traits of a particular deal. Obviously, repeat clients are going to have a different graph compared to new ones. For a more accurate estimate, you should use CRM to contrast between the deal value and close date.
3. Age of the deal
As a salesperson, you need to have your numbers game on lock. In contrast to the aforementioned sales forecasting methods, this one assesses the probability of a deal going through based on the length of the sales cycle. This means that you need to have the mean length of the sales cycle beforehand.
Given the fact that the mean age can vary depending on the type of deal, this particular method supports algorithms. The computerized tabulation can give you insights on various sets of numbers for a typical repeat customer. You can also learn a great deal about leads who come from website queries.
4. Intuitive Sales Forecasting
New establishments employ this particular method of forecasting sales. Its effectiveness is heavily dependent on the sales rep in question. Most salespeople tend to be optimistic and may offer optimistic estimates about business. Managers thus need to rely on their sales reps making the right judgment calls.
Since this sales forecasting method is dependent on non-numeric takes, there’s no scalable way to verify statements made. The closest one can get to validating assumptions is by checking the inventory of a rep’s meetings, listening in on calls made and perusing conversations. While this technique is not the best, it can be quite helpful for new startups. This is because new establishments usually have almost zero historical data.
5. Historical Sales Forecasting
Salespersons use this method to make estimates about the future based on past experiences. You can review a specific timespan and project that to the future. Ideally, you need to make a call and decide whether you expect to outperform or record similar sales. For a more comprehensive report, you should take into account historical growth. If the company increased monthly sales by a percentage, you can introduce a multiplier effect.
This system is a bit flawed because it doesn’t account for seasonality. In the sales process, there are always going to be some months where sales are up, others down. This method also assumes that demand is at a constant rate. When forecasting sales, you should use this technique as a stepping stone to get a feel for what to expect. This should not be the sole basis for your reasoning.
6. Mathematical Regression
This method of forecasting sales is more math-centric. To achieve success using this technique, you need to have a good comprehension of statistics. An understanding of all the vagaries that influence your company’s sales performance is also of the essence.
The process involves the calculation of the relationships between various phenomena. Then, a relationship is developed on how they impact sales. Some of the variables could concern the nature of demo meetings and the number of sales calls made. Another oft-overlooked variable is the total number of inquiries received from leads.
This sales forecasting method is considered the most accurate. This is especially true when it comes to accounting why specific variables led to a sale. The only downside is the amount of mathematical prowess necessary. Other than being a salesperson, you also need to hold at least a Ph.D. in mathematics.