HomeBlogLearn SalesforceQualitative Analysis Methods in Sales Forecasting: Why it’s the Key to Success

Qualitative Analysis Methods in Sales Forecasting: Why it’s the Key to Success

Sales forecasting qualitative methods are an essential part of sales management. They help know how much inventory you will need in the future so that your sales team can be prepared and sales targets can be met. Forecasting sales is difficult because it requires predicting the future, which we all know has not been proven possible yet! However, there are methods for forecasting sales that rely on qualitative analysis rather than quantitative analysis. This blog post discusses qualitative analysis and why it’s key to success for sales forecasting.

I have already written this article about a quantitative method of sales forecasting, so make sure you check it out before reading this post.

What is the qualitative sales forecasting method?

Qualitative sales forecasting methods rely on sales managers’ expertise and sales experience, which is why it’s a good idea to implement this method after your sales team has been established. Essentially, qualitative analysis involves going through past sales data and looking for patterns that may predict future sales performance of a product or service in the market. A common way of doing this is by using demand patterns, which can include sales statistics such as seasonality and cyclicality.

The second way of doing a qualitative sales forecast is by questioning your customers, collecting feedback, and looking for sales trends. In B2B sectors, you can even ask your customers are they planning any future purchases, which results in a more precise sales forecast.

Why is qualitative analysis important?

The best way to predict sales for a product or service in the market is by looking at past data and determining patterns that may indicate future sales performance. Qualitative forecasting methods take it one step further than quantitative sales forecasting because there’s no formula to follow; sales managers must analyze sales performance and make a judgment call on what sales will look like in the future.

As opposed to the quantitative sales forecasting method, qualitative can provide more sales forecasting insights because sales managers have the ability to go more in-depth with sales performance. For example, if a sales manager discovers that sales increase during certain holidays or seasons of the year, they can use this information as part of their sales forecast and take advantage by stocking up inventory before these occasions arise.

Are qualitative forecasting methods any better than quantitative?

Well, the short answer is NO. Is iPhone better than Android? Is Mercedes better than BMW? In all these cases the answer is the same. Both methods have their benefits and both are equally important for sales managers in making a sales forecast, which is why you should use both of them if your company allows it!

What qualitative methods are available?

There are several different qualitative forecasting methods and here are just some of the examples.

  • Expert’s Opinion Method
  • The Delphi Method
  • Sales Force Composite Method
  • Survey of Buyer’s Expectations
  • Historical Analogy Method

Expert’s Opinion Method

The most popular and the least efficient method of qualitative forecasting methods. if you use that on a high level. Let me explain. Suppose you need to produce a sales plan for the upcoming month and you use historical data to get an idea of what are sales going to look like next month. But then you go and ask an experienced guy from sales department about his thoughts about the plan for the month. Most likely you will hear a random number taken out of nowhere, but it will be close to you historical data because the guy works here forever and he knows more or less what are broad economic trends in your business.

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    Where you actually can use the expert opinion method is on a single opportunity level and this method proves to work.

    My experience on expert’s opinion forecasting technique

    I used to work in sales and I would often find myself on the phone with sales managers identifying potential sales opportunities with prospects. At this point, I would already know how much money was potentially at stake – what sort of account it was, the person selling, etcetera – but my sales forecasting process didn’t end there.

    Before I went ahead and made an offer on the prospect’s company, I took a few minutes to review the history between that account and my company.

    The salesperson is then able to see that account’s past sales performance. They will see whether or not they’ve typically done business with our competitors, how much they’ve spent in the past, and how much sales people like them tend to spend.

    The salesperson will also be able to see whether or not our competitors have had success with this account in the past. This provides an idea of what is possible for us if we choose to pursue it as well.

    A question to you, reader. Could this be accounted for as one of the qualitative forecasting methods? I’ll this it here, think about it.

    Why does an expert’s opinion forecasting technique work?

    It appears that sales forecasting using the expert opinion method works because sales managers are often looking at similar data when doing their own forecasts – such as company’s industry type, number of employees etc., which gives them enough information about future sales performance even without statistical background or training knowledge. However, there is always some inaccuracy due to different perspectives on your business and external factors influence (such as upcoming sales events).

    The Delphi Method

    The Delphi method is more complicated than the expert’s opinion technique because it involves a lot of analysis. C-level manager chose Delphi qualitative forecasting methods more often than any other type of managers.

    You will have to collect sales forecasts from various experts in the sales department, sales managers and sales representatives. You will then combine this information with past sales data to get an insight into how much you should expect from your business in the future.

    The Delphi method background

    The Delphi method was first introduced by Rand Corporation in the 1950s. It was developed as a forecasting method for sales, but it’s also very popular with market research professionals and organizational planners who want to make forecasts about future sales or sales trends.

    How does The Delphi Method work?

    The experts are able to share their point of view anonymously by filling out questionnaires sent via email/online form that has been designed specifically for this technique. You can then send these anonymous results back to experts so they can revise them if needed before you finalize your sales forecast report.

    My experience with The Delphi Method

    In my opinion, this method works best when you need accurate sales numbers from two different groups- external stakeholders such as customers and suppliers because there is no chance to influence their sales forecasting opinions and this way you will get an unbiased sales forecast which is very close to your actual sales number.

    I can’t say that it works better than expert opinion method because every method has its own pros and cons, but I find The Delphi Method more reliable due to the fact that experts won’t be able to talk among each other about what numbers they gave during the survey or who said what so there would not be any chance for information bias.

    Does Delphi method actually work?

    I have seen multiple attempts from different companies to implement Delphi method in the business and it seems to show quite realistic numbers. The only problem with this forecasting model is the time it takes to produce a forecast.

    It takes a lot of time to produce sales forecasts based on the Delphi technique. The problem is not in data collection but in data summarization and interpretation. It often takes up to six months for sales managers to be able to finalize sales forecast projections using this method.

    Where to use the Delphi method

    Among other qualitative forecasting methods, I would recommend using the Delphi method only during your annual planning. Because it takes so much time and effort to use it on a daily basis, your manager can get tired very quickly from all the sales meetings needed. It is much better to use it only when you need a reliable sales forecast for your business because it will give you an unbiased sales projection that should be very close to the actual sales number at the end of the year/quarter. I would recommend using the Delphi method in combination with other forecasting techniques such as expert opinion or trend analysis which takes less time and effort but still gives a good insight into future sales numbers.

    Sales Force Composite Method

    The sales force composite method of sales forecasting is a technique that’s based on the sales data of sales representatives. This sales forecast technique is often used by sales managers to evaluate the sales performance of sales representatives.

    The sales force composite method consists of four components:

    1. Sales data from sales reps,
    2. Sales data for different periods in time,
    3. Total sales figures for all reps, and
    4. The size of the company’s sales force.

    Sales managers usually use this forecasting tool in combination with other forecasting methods such as trend analysis or prediction.

    How to sales force composite method work?

    The sales force composite method is similar to the Delphi method, but it uses sales rep data versus executive-level employee responses. Usually, you have a CRM system where you track opportunities and each of the sales reps enters the expected opportunity value. From this sales data, you then calculate a sales forecast that can be used to evaluate reps’ sales performance.

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      This forecasting tool is best for evaluating individual rep performance because you can compare them against each other by looking at opportunities closed and average opportunity values per quarter which gives good insight into how well your reps are performing on the market/with current customers. The downside? It doesn’t give an accurate overall picture of future sales numbers so it should only be used together with another forecasting technique.

      My experience with sales force composite method

      This future sales prediction method is the only one which comes with every CRM system on the market. I would say it’s one of default qualitative forecasting methods. If you register trial account with Salesforce and open up any random opportunity record you will notice there are two fields – deal amount and closing date. These fields will be used for this forecasting method.

      If you have a good sales manager in place who will actually track what sales reps are writing there out of all qualitative forecasting techniques this one is the most accurate.

      Where to use sales force composite method?

      Sales force composite quantative sales forecast is best used in sales force prospecting, sales forecasting, sales pipeline management. The sales force composite sales forecast is also effective in sales assignments and sales management. This is the most common way of forecasting sales, so feel free to use it.

      What sales force composite method is not good for?

      This sales forecast technique is definitely not best suited to sales cycles longer than twelve months. If you have a long sales cycle, there’s no guarantee that your projections will be accurate simply because of the nature of large deals which can change from month to month and year to year.

      Can I use sales force composite with another qualitative forecasting methods?

      Absolutely! It would actually make a lot sense since both sales forecasts methods are qualitative in their nature so they should compliment each other very well. Composite Sales Forecasting Method works great when combined with linear regression or exponentially smoothed average techniques as it will provide more clarity on what factors really influence customer buying behavior over time period.

      Survey of Buyer’s Expectations

      This qualitative forecasting techniques are actually similar to quantitative methods, because uses aggregated data. The only difference is that quantitative forecasting methods use sales metrics to forecast sales whereas, this sales forecasting method uses survey results.

      In other words, survey uses same statistical methods, but analyze subjective responses from buyers. In other words – they are not about statistics, but about asking people what they think.

      How does Survey of Buyer’s Expectations work?

      It is very simple – you just need to ask your customers what they expect in terms of future sales and trends so that it would be easier for them to make decisions on product investments. For example, if you are selling computer components than probably most important factor which will define how much PC one consumer can build in the next six months is CPU price (absurd example, but Illustrates the idea). If there might be some new generation CPUs released then people may not buy last year’s model but wait until prices drop even further after release date before buying one.

      My experience with buyer surevey

      I don’t have much, to be honest. I don’t use this method, because most of my life I work in B2B and the only case where this actually works is when you pick up the phone ask your existing customer about his plans for the next year’s budget. That’s it.

      The problem with asking buyers is always in quantitative data. In other words, their provide you with their opinion which is not justified with real intention to buy. It is just a simple guess what might happen in the area of business they are working on.

      I have seen many cases of historical data being used for forecasting which was only based on the experience. For example, I had situation when historical sales data provided by vendor (the company where we buy our machines) showed that they sold around 100 units per month but actual order numbers were completely different – something like 40-50 units per month. As a result, do not expect this market research to provide you with high quality data.

      Historical Analogy Method

      This is another forecasting method which I have seen being used since the beginning of my career. It was mostly historical data from similar products, companies or industry where you are working on now. But there are two main problems with this approach: firstly it requires much more historical input than any other type of forecast and secondly – it always produces accurate results only in case if product/company/industry stays unchanged during that time frame (i.e. same company structure, functions, etc).

      How would people use this?

      I think one example will be enough to show how historical analogy could work for your business as well – let’s say you run a local bakery shop but want to start selling pies online via Shopify because you have a new idea how to make it more productive. In this case historical analogy would require you going back in time and taking historical data from similar product (baked pies) sold through different channels for at least one year if not two years, because the longer it is – the better your chance of having accurate forecasting results.

      In my opinion, there are only three things that can provide you with high quality historical analogue forecasts:

      • You work on same product/company/industry AND all these factors remain unchanged during certain period of time;
      • Company structure changed but customers don’t really care about changes which means they still use historical information when buying products or services;
      • Historical sales numbers were so incredibly bad or good (i.e. historical data is very inaccurate) that forecasting accuracy will not be affected even if you decide to use less historical information for your forecast.

      So, the question still remains – why should we bother with historical analogue method in sales forecasting? Because it does provide accurate results and can identify future products/services which need investment in order to become more productive or introduce new features in their product portfolio after certain time frame has passed by..

      Conclusion: Qualitative Analysis is Key

      Qualitative analysis provides us with high quality forecasts when combined with historical analogy method of forecasting because it includes all factors than influence decision making process of customers when they buy something from your company such as competitor activity on market, economic situation and other aspects that might affect historical analogue forecasting results. It is also worth mentioning that we can use qualitative analysis to identify future trends which might influence our business and thus, enhance our forecasts even more..

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        How you combine historical data with qualitative research?

        I like combining both historical information (like historical analogue) collected through different sources such as customers, vendors or experts in certain industry/market segment plus using my own experience when I talk with people working on the same market because this gives me huge advantage over companies who don’t do it at all. Although many of them are still doing great but there is always room for improvement if they decide to invest some time into understanding why their product did not sell well enough even though historical data suggested otherwise during previous periods of time.

        That being said historical data is still useful because it shows who are the most successful players on particular market/industry which can help you to understand what type of product or service is in demand at the moment and thus, forecasting sales volume for current period becomes much easier than before when historical analogy was your only choice.

        Company has to be stable

        Qualitative analysis will provide accurate results as long as company structure does not change too often which might lead to wrong conclusions about customer needs. For example if there were changes made during certain time frame but these changes did not affect customers directly (i.e. they don’t ask for new features) – historical analogue method would work just fine with qualitative research added into mix…What do I mean by this?

        Take a look at the following example: historical sales data shows that company has been selling certain type of product for five years with one-year break in between because they decided to focus on core business and introduce new products later.

        Combining data is key

        If you combine historical information (in this case historical analogue) collected through customers, vendors or industry experts plus qualitative research – forecasting results will be accurate as long as current period does not exceed five years.

        Qualitative analysis is key if we want to create high quality forecasts which can help companies make better decisions about their future plans like introducing new features into existing product portfolio after certain time frame has passed by, stop investing money into products/services that are out of demand but were still successful up until now etc.. Historical analogue method can be considered as a first step towards qualitative research which should lead into accurate forecasting results.

        Hope this article was useful and helped you better understand qualitative forecasting techniques and methods.

        Have a great day/night whatever it is now when you are reading this.


        System Thinker, Technology Evangelist, and Humanist, Jeff, brings a unique blend of experience, insight, and humanity to every piece. With eight years in the trenches as a sales representative and later transitioning into a consultant role, Jeff has mastered the art of distilling complex concepts into digestible, compelling narratives. Journeying across the globe, he continues to curate an eclectic tapestry of knowledge, piecing together insights from diverse cultures, industries, and fields. His writings are a testament to his continuous pursuit of learning and understanding—bridging the gap between technology, systems thinking, and our shared human experience.

        No hocus pocus, just strategic focus.

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