The Three Main Sales Forecasting Techniques Explained
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October 22, 2024
Table of Contents
Summary:
There are three main techniques used in sales forecasting: qualitative techniques, time-series analysis, and causal models.
Qualitative techniques rely on expert judgment, market research, and feedback to forecast sales when historical data is limited, such as during new product launches or market expansions.
A time-series analysis uses historical sales data to identify trends, patterns, and seasonality. This is helpful for predicting future sales in stable environments based on past performance.
Causal models account for external factors like economic conditions, competitor activities, and market trends to build a model that predicts how these variables will impact future sales.
Using PhoneBurner’s reporting, analytics, and disposition tracking features can make it easier to apply these forecasting techniques and improve the accuracy of your sales predictions.
Sales forecasting is a critical tool for phone sales teams looking to plan ahead, optimize resources, and achieve consistent results. By predicting future sales, you and your team can:
Understanding and applying the right forecasting techniques is the key to ensuring that your predictions are accurate. Below, our team at PhoneBurner shows you how we make forecasting easier, explains the three main types of forecasting techniques, and gives you guidance on when to use each one.
In addition to helping you reach up to 4x as many contacts, PhoneBurner’s dialing platform also includes reporting tools and other features that can improve your forecasting process no matter which of the techniques in this article you use.
Monitoring & coaching (for qualitative models): PhoneBurner’s Listen In, Whisper, and Barge features give you a front-row seat to actual conversations your sales agents are having in real-time. This helps you predict sales outcomes by learning who your customers really are and what they really want.
Custom reports with historical data (for time-series analyses): Our reporting tools can be configured to provide all kinds of useful metrics—including call volume, answer rates, call outcomes, and more. This can help you identify patterns and predict future sales trends.
Custom disposition buttons (for causal models): Clarify your prospects’ intent to buy, then integrate this data into a model that also accounts for external sales factors like market changes. This helps you see how your prospects are likely to react to current events.
Not a PhoneBurner user yet? Start your free trial here to find out how much easier our platform can make your forecasting efforts—then keep reading to learn about the three main forecasting categories and when to use each one.
Qualitative Techniques
Qualitative forecasting is ideal for situations where data is limited or new products are being introduced. This technique relies on expert judgment, market research, and feedback rather than historical sales data.
When to Use
You might use qualitative methods for your phone sales team if you want to:
Gauge market sentiment
Assess sales potential for new services
Anticipate changes in customer behavior
What You’ll Need
A way to conduct market research
Access to expert opinions
The confidence to make judgment calls based on largely subjective data
Key Steps
Gather input from prospects, current customers, and experts within the company or industry.
Use surveys or group discussions to reach a consensus on future sales outcomes.
Convert qualitative insights into quantitative estimates to provide guidance for planning.
Examples
Your phone sales team might use qualitative forecasting when you're introducing a new service or entering a new market. For example, if you're planning to roll out a new subscription package, you might:
Gather input from your experienced team members and consult external experts or customer feedback.
You can also use surveys or customer focus groups to understand how likely people are to adopt the new offering.
With PhoneBurner’s monitoring tools, you can listen in on sales calls to hear how prospects respond to the new product in real time.
As you collect feedback, track early sales trends using PhoneBurner’s analytics dashboard to make data-driven adjustments.
By combining these qualitative insights, you’ll be able to estimate how quickly the product will gain traction, helping you set realistic sales targets.
Time-Series Analysis
Time-series analysis involves looking at historical sales data to identify trends, patterns, and seasonality that can inform future sales projections. The goal is to predict future performance based on past results, making it ideal for more stable sales environments.
When to Use
You might use this technique for your phone sales team if you want to:
Identify repeating patterns in sales data
Determine the growth rate of these trends
What You’ll Need
Access to consistent sales data over a period of time.
Past sales that reliably indicate future results.
Reporting tools that collect and present key metrics so you can easily spot patterns and trends
Key Steps
Collect historical sales data, focusing on trends and cycles (such as monthly or quarterly sales).
Use moving averages or exponential smoothing to identify seasonal patterns or long-term trends.
Project future sales by analyzing these trends over the next forecast period.
Examples
If your team has been selling the same product for several years, you likely already have historical data on sales patterns. For instance:
Maybe you’ve noticed that conversions drop during the summer and surge again in the fall.
Using PhoneBurner’s reporting tools, you can pull detailed data from previous years to identify these seasonal trends.
From there, you can use a time-series analysis to project when and how those fluctuations will happen again.
By anticipating these sales dips and spikes, you can adjust your team’s outreach strategy or staffing levels to optimize resources. PhoneBurner’s reports allow you to visualize these trends easily, helping your team stay proactive and prepared for seasonal changes.
Causal Models
Causal forecasting models identify relationships between various factors (such as economic conditions, marketing campaigns, or competitor activities) and sales performance.
For phone sales teams, this method can provide a more dynamic view by taking external influences into account, allowing more accurate forecasting when combined with other techniques.
When to Use
Causal models are typically best for sales teams that want to:
Establish a mathematical formula for predicting sales
Accurately anticipate turning points in sales trends
Prepare reliable long-range forecasts
What You’ll Need
Accurate historical data and a clear understanding of how external factors (market forces, socioeconomic changes, etc.) influence sales trends
The time to continuously revise your model as new data becomes available
A significant budget to dedicate to sales forecasting—as developing a causal model is typically more expensive than other methods
Key Steps
Identify external factors that may impact sales (e.g., market trends, economic shifts, or new regulations).
Collect data on these factors and their potential influence on sales.
Build a model to estimate the effect of each factor on future sales performance.
Note: the causal model you build will likely include the results of a time-series analysis, but should also account for the impact of outside factors on those trends—to the best of your knowledge. This will require you to make some assumptions at first, but these will either be validated or updated as new information becomes available over time.
Examples
Your phone sales team may experience sales fluctuations due to external factors like a competitor’s pricing strategy or broader economic changes. With a causal model, you can analyze how these external events are impacting your sales performance. For example, if a competitor launches an aggressive promotion, you might:
Begin by tracking the immediate impact on your sales. With PhoneBurner’s detailed reports on call answer rates, conversions, and follow-ups, you can identify any downward trends that coincide with the competitor’s campaign. This provides the foundation of your causal model—linking external competitor activity to your internal sales metrics.
Next, you’ll need to integrate additional external data, such as overall market trends, economic indicators (like consumer confidence or unemployment rates), or specific customer behaviors you’ve identified through PhoneBurner’s custom disposition buttons. For instance, if your disposition buttons show an increasing number of prospects indicating budget concerns, this may suggest that broader economic shifts are at play.
Once you have these data points, start constructing the model by mapping out the relationships between these external factors and your internal sales performance. You can use regression analysis or other statistical methods to determine how strongly each external factor influences your sales. For example:some text
Competitor promotions might lead to a 15% decrease in conversions during the promotional period.
Economic downturns might correlate with longer sales cycles or more frequent objections related to budget.
As you collect more data over time, continue to refine your model by adding new variables or adjusting the weight of existing factors. This iterative process makes your causal model increasingly accurate, allowing you to anticipate how future competitor moves or economic shifts will impact your sales pipeline.
The Right Forecasting Method Makes Your Sales Team Efficient
Accurate sales forecasting is key to effective sales management. It helps you optimize resource allocation for your team, set achievable targets, and remain agile in a dynamic market.
Whether you’re using qualitative techniques, time-series analysis, or causal models, PhoneBurner's powerful reporting and analytics tools can help you refine your forecasting for greater precision. Ready to elevate your sales forecasting efforts? Try PhoneBurner for free today and see how our platform can help you achieve more accurate predictions and better results.
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