Sales forecasting has become an increasingly common element of the site selection process and is often the focus of real estate modeling projects. Given the wide variety of forecasting options available, what is sales forecasting in a site selection context and how does it differ from other forecasting methods?
Common Approaches to Sales Forecasting
Sales forecasting involves using past performance to inform future performance. In real estate, there are two primary approaches for forecasting sales.
In a time-series forecasting approach, the analyst uses the existing sales history of a location to extrapolate likely sales performance at that location in future quarters. The goal is to identify trends in store performance and to set goals. This approach is commonly used for existing locations but cannot easily be used for new locations since it requires prior sales history.
Forecasting sales for a location with no prior sales history is more challenging. The analyst first compares the performance of existing locations to measurable characteristics of the trade area to quantify relationships between variables and performance. Those quantifiable relationships are integrated into a sales forecasting model that can be applied on a go-forward basis to new sites when there is no sales history to leverage. The model can also be applied to existing locations to forecast what sales “should” be given the underlying factors in the trade area/site.
The Maturity Factor
In any sales forecast, one of the factors that must always be considered is the time that it takes for sales at a new location to stabilize – or reach maturity. Some brands reach sales maturity quickly, while others take much longer. By studying the sales stabilization patterns in prior locations, the analyst can determine the average length of time it takes to reach maturity and whether the sales forecast should be based on anticipated sales in the first year of the new location’s operations or on annual sales at the date when the location has reached maturity.
Sales Forecasting Error
No matter how solid the sales forecasting model, there is always a margin of error. Some error is due to the fact that it is impossible to perfectly measure all factors that influence sales performance. Since forecasting models rely on variables that can be quantified, a certain level of error is inherent. Knowing this, it’s important to avoid overfitting the model to the factors that you are able to measure because those factors ignore what you aren’t able to measure.
How can you make decisions with confidence given the fact that all models will have a certain level of error? Consider this:
- While imperfect, the sales forecast allows you to narrow the list of possible outcomes and reduce risk. If you open just one store based on the model, the performance may or may not be an outlier, but over time the performance of stores opened based on the model should even out. Consider how your sales average over time when evaluating the effectiveness of a sales forecasting model.
- Manage the margin of error by factoring it into your evaluation. Don’t put yourself in a position where the forecast must be perfect in order to break even on the investment. Incorporate some margin for error into your decision making.
The Bottom Line
While no sales forecasting method is perfect, sales forecasting models are helpful tools in the site selection process and can help real estate professionals to reduce risk.
Explore our blog to learn more about common types of site selection models.