When it comes to sales, numbers are key, but they don’t always give you a comprehensive picture of your org’s performance and potential — particularly in the context of forecasting. So while quantitative forecasting can’t be ignored, you still need to consider factors beyond those hard figures if you want a truly thorough understanding of what you can expect from your sales department.
The consideration of those non-quantitative factors amounts to something known as qualitative forecasting — forecasting that accounts for the more subjective elements of sales.
By accounting for both sides of the forecasting process, you can put yourself in the best position to set accurate targets, plan for the future, and predict the success of your upcoming campaigns.
Here, we’ll take a closer look at qualitative forecasting as a concept, review some methods and techniques you can use to get the most out of the process, see some examples of what it looks like in practice, and weigh its pros and cons. Let’s jump in!
There’s no denying that numbers are a crucial part of any sales forecast — you should never try to put one together without them. But as I touched on earlier, hard figures generally can’t give you a complete enough picture to inform as accurate a forecast as possible.
That’s where qualitative forecasting comes in. It helps a company flesh out a more thorough understanding of customer and market behavior — helping that business account for more angles and potential curveballs it might run into when conducting its sales efforts over a fixed period.
Qualitative forecasting is particularly helpful when companies are exploring new sales methods or expect sales to deviate from the typical results. As companies grow, they might find themselves in uncharted territory — setting unprecedented goals and making plans they’re not well-acquainted with.
In those cases, qualitative forecasting can help businesses make sound decisions, set viable objectives, and reliably predict what they can expect to see as their sales efforts unfold.
Qualitative Forecasting Methods and Techniques
So how do you approach qualitative forecasting? There are several ways to go down this path.
1. Experience (Executive Opinion)
In many cases, some of the necessary insight and information to inform effective qualitative forecasting can come from within the company — typically from leadership.
Managers (or occasionally regular employees) might already have extensive knowledge of or experience with a certain market, product, or customer base. In those instances, they can be an excellent resource for assisting with qualitative forecasting.
Not every business has leadership that’s seasoned enough to put together reliable qualitative forecasts based on personal experience — especially if a company is younger and scaling.
That’s why companies often outsource their qualitative forecasting responsibilities to third parties. Consultants with a more developed pulse on an industry, market, or customer persona can be an excellent resource for a company struggling with qualitative forecasting.
3. Delphi Method
The Delphi Method is similar to the ones listed above in that it relies on experts, but the process is a bit more elaborate and sophisticated than most others. Instead of just asking experienced managers or consultants for their opinions off-hand or collaboratively, the method involves questioning multiple parties about a sales forecast separately to prevent groupthink.
The risk you run when leveraging the Delphi Method is a lack of consensus. If too many experts are offering varying perspectives, it can be hard to piece together a cohesive, accurate qualitative forecast.
Surveys are another way to inform thoughtful, effective qualitative forecasting. This method is one of the more tried-and-true, relatively accessible options listed here. Hearing directly from your target audience can help you tailor a forecast backed by firsthand qualitative insight.
A well-constructed survey can help give you insight into new markets, help you understand shifting tides within your industry, and better identify your customers’ collective tendencies. With several applications to create and distribute surveys at your disposal, this method is worth considering when putting together qualitative forecasts.
5. Market Research
When a business plans to enter a new market, it can use market research to boost its qualitative forecasting. This practice helps a company determine if breaching a new market is worth the effort and resources.
It also offers perspective on what potential new customers are looking for from the business. Resources like focus groups, product testing surveys, and polls can all be used when leveraging this method.
Qualitative Forecasting Examples
Virtually any significant decision any business makes can benefit from qualitative forecasting techniques.
When a company is either just starting or getting off the ground, its leadership will likely need to account for market research to find out if the company’s idea, offering, business model, messaging, pricing, and marketing are viable.
In those cases, the organizations in question don’t have existing numerical data to analyze and rely on — making accurate quantitative forecasting virtually impossible. Instead, those companies have to take different, more creative roads to produce a solid picture of what they can expect from their sales efforts and target prospects.
Qualitative forecasting is also an asset for more mature companies, looking to release a new product or service. Quantitative methods can only get you so far if you’ve never actually sold a specific offering. That’s why businesses in this position generally look beyond those strategies to get an accurate understanding of what’s to come.
Advantages of Qualitative Forecasting
For some sales leaders, the idea of using anything besides numerical analysis in sales forecasting can seem intimidating or pointless — but qualitative forecasting offers several advantages that extend beyond those of its quantitative counterpart.
It provides relevance and flexibility.
Qualitative forecasting doesn’t care about last year’s sales numbers. What it does care about is more timely, relevant information. It considers factors like new technology that your business has adopted or global trends that might have had implications on the economy at large.
Qualitative forecasting can take non-numerical events and assign weight to how they might impact a company’s performance and operations — offering that business a higher degree of flexibility in its decision-making when those kinds of variables take hold.
It gives you a more comprehensive perspective.
When paired with quantitative forecasting, qualitative forecasting can give a company a holistic look at virtually every factor at play — both objective and subjective — when considering a significant decision.
This point is particularly relevant to larger companies with plenty of historical numerical data and the resources to supplement it with internal or external expertise and market research. With the ability to deliver on both sides of the forecasting token at their disposal, these kinds of businesses can reliably put together comprehensive, accurate sales predictions.
It works particularly well for new and growing companies.
While larger enterprises likely have reliable quantitative data to pair with their qualitative insight, startups and small businesses might not be so lucky. In most cases, those kinds of companies haven’t been around long enough to accrue a significant bank of hard sales figures — making qualitative data central to their forecasts.
Drawbacks of Qualitative Forecasting
Though qualitative forecasting has tremendous upside, it still comes with its fair share of drawbacks.
It can be compromised with bias.
Regardless of whether a company turns to skilled employees, consultants, or customer insights, it always runs the risk of compromising insight with bias in qualitative forecasting. Qualitative data is inherently subjective, and subjective information is naturally prone to bias.
It’s prone to inaccuracy.
Humans make mistakes. Without hard numbers to rely on, qualitative data can produce incorrect results. This point ties into the one above — biased data is generally inaccurate by nature.
For instance, a customer might be more inclined to respond to a survey or poll a business is running to vent about a single negative experience. Or, a manager relying on past experiences to inform forecasts might bring too personal a spin to the process or see past events and trends through a warped lens.
It might be invalid.
Hired consultants or expert panels outside of the business can provide a different perspective, but their separation from the company could render their forecasts invalid. Companies turning to subjective insights are at risk of receiving forecasts that are illegitimate or irrelevant to the task at hand.
Use Qualitative Forecasting For Improved Decision-Making
Any time a business needs to make a decision or step forward, it needs a comprehensive forecast to help set goals, milestones, and expectations. Data analysis can always help guide a business, but quantitative data doesn’t always provide the whole picture.
That’s why qualitative forecasting is so important. It can provide deeper insight that takes varying viewpoints, experiences, and real-world events into account — letting a company can be as prepared as possible to move forward effectively.