Qualitative forecasting examples
Sales forecasting has to account for multiple rogue variables in its predictions. Reliable data used to forecast can be impacted by technological developments, swift market upheavals, simultaneous product launches, customer trends — in other words, the unknown. Forecasters call these unpredictable changes “randomness.”
Quantitative forecasting methods, which rely on sales data, have a hard time accounting for randomness. However, qualitative forecasting, also called opinion forecasting, is better suited for predicting random market changes.
Let’s look at some qualitative forecasting examples that showcase these opinion-based methods and results.
What is a qualitative forecast?
A qualitative forecast is one based on subjective information, such as sellers’ opinions, customer surveys, or expert insights.
While qualitative forecasting doesn’t rely on numerical analysis like quantitative forecasting does, the techniques still rely on the scientific method and develop sophisticated conclusions based on investigation and research. But in qualitative forecasting examples, the research is usually some form of collected expert opinions and subjective data.
Qualitative forecasting example #1 A marketing consultancy is considering moving from a customized services model to a more productized, tiered-pricing model. Historically, it has offered customized packages for every customer, but it has found that it makes the most money from customers whose contracts fall into one of three general categories.
To gauge customer perception of this kind of move, the sales team prepared a survey and sent it to existing customers. The survey described three packages of services and asked for input about how those packages might align with customer needs. Unsurprisingly to the sales team, 82% of existing customers responded that they would be comfortable with selecting from a menu of packages.
What are the qualitative methods of sales forecasting?
Qualitative forecasting methods rely on subjective data and expert opinion. But, collected together, these amount to more than just guesses. Qualitative methods have generated accurate forecasts for businesses to help sales teams — and that’s the real measure of worth.
Below are some qualitative forecasting examples in business and common methods employed to turn subjective data into accurate predictions.
Its name is derived from the Oracle of Delphi — the ancient Greek’s council for future predictions. This method relies on the opinion of the group over the individual. The strategy is to submit an anonymous questionnaire to a group of experts of a given market, product, or industry. The questionnaire includes some opinion-based, intuitive questions. The results are collected and shared among the group for discussion, and then the process is repeated. In doing so, the target is to achieve a consensus, which is highly valuable for predicting future sales.
Qualitative forecasting example #2 Let’s return to the marketing consultancy. The sales team and marketers on staff are a collection of industry experts and customer specialists with nearly a century of collective knowledge from different backgrounds.
When determining whether to move all existing customers to their new tiered-pricing model, or to grandfather in long-standing customers who are hesitant to make the switch, a questionnaire is issued to the group participants about their perspective on the accounts they spend the most time with to see which would be preferred. Three specific questions are asked, and the responses are published for the group to see. The questionnaire is repeated, and the consensus for those three questions grows, reinforcing agreement among the group of experts.
What is an example of a qualitative forecast?
Other informative methods for qualitative forecast rely on mass opinion over expert opinion, such as market research.
This method goes to the primary source — customers — to predict future sales. Market research may involve questionnaires or surveys that inquire about customer preferences. These can be targeted to a specific geographic area or demographic.
Market research could also involve customer testing. A group of customers can test a new product or service, and the results could be collected, analyzed, and introduced into product development.
Qualitative forecasting example #3 Six months into the marketing consultancy’s new tiered-pricing packages, the sales team asks for feedback on the new model. A quick survey is sent to customers asking them to rate their satisfaction with pricing, value, and the results of the agency’s work. Overwhelming feedback from customers suggests that the bottom tier is missing a key service offering, and the agency quickly pivots to include that service in the package moving forward.
Move beyond qualitative forecasts with Collective[i]
Each of these qualitative examples showcases the importance of understanding nuance — the data quantitative forecasting sometimes misses, especially with new products. In qualitative forecasting examples in business, we see different types of data, some collected from experts, some collected from the market.
Collective[i] uses technology enabled by artificial intelligence and machine learning to make the best of quantitative and qualitative methods of sales forecasting. It also collects historical data and data in real time from multiple market sources.
Need proof? Check out Collective[i] today to learn more about how it’s able to provide clear business directives from a hazy milieu of market data.Explore Collective[i]