What is qualitative forecasting?
Businesses large to small have one thing in common, and that’s what they stand to gain from effective sales forecasting. Accurate forecasting predictions are necessary for any business to plan its year, from covering basic costs to making investments in the right areas.
Traditionally, businesses have employed two primary types of forecasting: quantitative and qualitative. Many businesses use tactics from each category to produce increasingly accurate sales forecasts that inform business decisions — with mixed results.
To understand the benefits of qualitative forecasting and how modern sales teams are improving on this traditional model, it’s important to know what is qualitative forecasting, as well as how it differs from quantitative methods.
The difference between quantitative and qualitative forecasting
Both quantitative and qualitative forecasting methods lead to sales projections that can help a business plan its future. But there’s one key difference between the two.
Quantitative forecasting makes projections based on hard data. It takes sales data from recent history and crunches them — along with other data, such as macroeconomic data — to forecast future sales numbers.
Qualitative forecasting, on the other hand, involves predicting future trends using the informed opinions of people such as customers, sellers, company leadership, and industry experts — in short, information that’s impossible to quantify.
Benefits and challenges of qualitative forecasting
Qualitative data includes judgements and opinions from both executive-level management, who understand greater trends in the economy, and salespeople, who rely on instinct and intuition based on the relationships they have with customers.
When historical data doesn’t exist, or when data is otherwise ambiguous, sales teams can rely on qualitative forecasting to make sales predictions. Young businesses in particular need to rely on qualitative methods of sales forecasting because they lack historical data.
Likewise, qualitative forecasting enables a business to be more flexible and react to what’s happening right now. Especially when used in conjunction with quantitative forecasting, it provides a more complete picture that hard, numerical data alone doesn’t offer. Consider the limited perspective that comes with using historical data to predict future sales; the past simply cannot be used to predict exactly what will happen in the future. However, sellers who have their fingers on the pulse of what prospects are looking for can temper historical forecasting models with relevant insights. If a seller gets connected to a motivated buyer at a new company with a significant need, that deal alone could change the landscape of sales figures for the upcoming quarter.
A drawback of qualitative forecasting is that because it depends on intuition, instinct, and opinion, its predictions are biased. Salespeople may be hesitant to predict success with a customer if it means facing repercussions for not meeting that lofty sales goal later.
What are qualitative methods of forecasting sales?
There are several qualitative sales forecasting methods to make the most of the data that’s available.
Sales team forecasting
This method relies on gathering insights from a company’s salespeople, who are the closest to the customers. In theory, the sales team should have a solid idea of which customers are hot, which are not, and whether any leads are promising, as well as an in-depth understanding of customers’ needs and desires. One downside to this method is that the sales team is already slammed with making daily sales calls and recording the details in a CRM, which is a time-consuming administrative task. In fact, that can be a detriment to almost any qualitative sales forecasting method.
Market research forecasting
This method requires more upfront investment than polling an internal sales team but leads to more accurate results. By interviewing or surveying potential customers, a business can gain valuable insights for the future. Focus groups are more realistic for larger businesses with more cash flow. Methods such as email surveys and publishing questions and polls on social media channels can provide some data for smaller businesses.
The Delphi method
In this time-intensive method, a number of industry experts are brought together to discuss industry trends and reach a consensus about the future of the market.
[An] emerging type of forecast [that] leverages deep learning on both structured and unstructured (voice, text, etc.) data to derive an even more accurate forecast. Because deep learning requires a significant volume of data to outperform classic machine-learning methods, some vendors are training models on a network of their clients’ engagement data. Here, reps’ opinions augment the prediction, and most of the human focus is on beating the number by leveraging these deeper buying signals.
This type of deep learning technology is at the heart of the Collective[i] platform, which empowers sellers to punch above their weight with daily forecasts based on broader data sets. With our Intelligent InsightsTM, sellers can rely on real-time recommendations to focus their efforts on actions that will have the greatest impact on driving revenue. That means less time managing surveys and forecast data and more time listening to customers and solving real problems with human instinct.
Explore Collective[i] today and unlock the full potential of your sales team.Explore Collective[i]