Sales forecasting is more than just predicting your sales volume over a future time frame. It’s a powerful tool that organizations use to tailor their entire sales strategy to. From budgeting expenses, to human resources, and even to the employment process, it’s a way to set immediate and long-term goals.
On the other hand, not having a sales forecasting process in place can damage your overall business strategy due to your inability to hit quota, identify and fix sales pipeline issues and much more.
What is a Sales Forecast?
Sales forecasts are tools used by organizations to predict weekly, monthly, quarterly, and annual sales volumes. Sales forecasting tools use historical data to predict future trends. Such tools use predictive analytics and data inputs from different sources for increased accuracy. Predictive sales forecasting enables businesses to make better decisions based on complete and accurate data points, and even takes into account factors such as seasonality and current sales performance.
What Do You Need For Accurate Sales Forecasts?
Successfully predicting future sales volumes depends on several factors:
- Data. Data is the main requirement for creating sales forecasts. Organizations can collect relevant information from different entry points, such as marketing, sales, customer service, and other relevant departments. Third-party data can also contribute to creating accurate forecasts. Compiling internal information with data from third-party sources can offer a more complete view of your sales pipeline and correctly predict sales volumes.
- Sales forecasting solutions. Such solutions collect and analyze data and generate accurate forecasts. The more data enters the system, the more accurate the predictions will be. These tools use predictive analytics and artificial intelligence and can often generate real-time insights for more strategic control.
- Accurate sales forecasting processes. Design a cohesive and consistent sales process for your reps to follow. Process consistency generates consistent data, which is more likely to result in accurate forecasting.
Sales Forecasting Examples
There are different sales forecasting methods used by companies. Below is a short selection.
Intuitive forecasting is mainly used by new companies that lack historical data. In such cases, companies need to find other data sources than customer information to model predictions. Intuitive forecasting relies on different components to tailor financial planning strategies:
- Seasonality of sales.
- Market trends analysis.
- Internal monthly sales reports.
- Although this method is preferred due to the lack of historical data, quality is not guaranteed as it relies more on sales reps’ subjectivity.
Below are other methods that heavily rely on analytics that you can use in your organizations.
This forecasting method uses past data from specific time frames to make future projections about similar time frames. For example, companies can predict yearly revenue growth by looking at the median annual growth.
Length of Sales Cycle Forecasting
The length of the sales cycle can influence overall budgets. If a customer takes too long to make a purchase, the amount spent on marketing and nurturing will surpass the amount spent by the customer, making it a losing deal. In B2B settings, the length of the sales journey will most likely be more extensive, as this process involves more approvals.
Opportunity Stage Forecasting
This is the simplest method used by companies who want to learn how likely an opportunity closing is. Variables like the ones below are usually taken into consideration:
- Time passed since the opportunity has been created.
- The number of prospect interactions.
- The amount of money spent on the opportunity.
By looking at all the factors above, companies can predict how likely a conversion is.
This forecasting method predicts future sales based on more data sets: current sales, previous sales, and so on. This method considers different elements: deal size, number of opportunities, close rates, and lead number in the pipeline. This method is believed to deliver some of the most accurate forecasts.
This forecasting method looks closely at the number of opportunities a company can expect to close in its pipeline. First, companies need to calculate the win rate of each stage in the sales funnel, going back as much as data allows. Then, a high-performing CRM or sales analytics tool should enable users to get the amount of open pipeline, including the period they are trying to generate a report, per stage. The last step is multiplying the pipeline per stage by the win rate for that stage and adding the numbers up.
Contact SugarCRM For Assistance In Your Sales Forecasts
Sales forecasting can uncover hidden revenue opportunities when done correctly. Sugar Sell, our sales automation platform, helps sales teams generate accurate forecasts, shorten sales cycles, and meet customers where they are. Sugar Sell’s extended capabilities offer a comprehensive automation solution:
- Lead, opportunity, account, and contact management capabilities.
- Pipeline management.
- Intelligent lead prioritization.
- Advanced forecasting and pipeline insights.
- Business process management capabilities.
- Subscription management.
- Guided selling capabilities.
Want to learn more about sales forecasting and how can Sugar Sell help you get on top of your sales pipeline? Get in touch with us! Or, you can watch our No Blind Spots: Build the Ultimate Sales Forecast with CRM webinar for a deeper understanding of what sales forecasting is and how SugarCRM can help.