September 24, 2021

8 Steps to Marketing Forecasting

Marketing forecasting can be defined as the act of predicting future market performance through analyzing past trends. This is done to give an accurate projection of future sales, growth, and patterns of consumption, to make informed decisions regarding product development, market expansion or for setting sales targets.

Market forecasting is important for any business, large or small. When making decisions about product design and production, market forecasts allow companies to make educated guesses regarding the number of products to produce. Businesses that sell services also use market forecasts to predict their future cash flows.

Market forecasting is itself an industry with many different ways to predict the future. This article will cover 8 steps you can take in order to become more accurate at producing effective market forecasts for your business.

Step 1: Pinpoint your problem(s)

A strong understanding of what problems you are facing (or trying to solve) is vital when it comes to developing a good forecast model. For example, if your company’s revenue has been dropping steadily over the last few years, your forecasting model should include items like current economic conditions, changes in the industry, and price fluctuations. If you are trying to determine how much product to produce next month, you need a different forecast model than the one used by a company looking for future revenue growth over the next few years.

Step 2: Determine all of your variables

Your data (the information you use to generate your forecasts) is only as good as its weakest link. Make sure that any data you use is accurate and up-to-date before finalizing your models. Any significant changes to the market should be accounted for when working through this step.

Step 3: Choose your forecasting model 

After pinpointing what problem(s) you are trying to solve and determining all your variables, you have to choose how to analyze the data. Although there is a large variety of forecasting models available for this step, a basic approach can be just as effective as a more advanced model. The Box-Jenkins ARIMA modeling approach uses statistical analyses with ARIMA, moving averages and trends in order to make predictions.

Step 4: Test the Data 

In this step, test your data on different time scales. This will allow you to determine if any factors were over or under-represented in the dataset used for analysis. For example, if your company’s revenue forecasts indicate that January should have higher sales numbers than December does every year but this doesn’t match up with actual customer behavior during those months, you know one of your variables has a flaw.

Step 5: Cut out wasteful data 

There are several steps to take when cutting out wasteful data from your model. The first is to make sure that all the data used in any calculations or graphs is actually related and relevant to what you’re trying to solve for. If some of the numbers seem vague or general, they should be cut. For example, if your company forecasts sales by region, but North America and South America are both listed as regions instead of separate continents, this would count as ‘wasteful data’ because it muddies up the specific sales information you need in order to make an accurate prediction.

The second step is determining how much weight each variable should carry when it comes to the final forecast. This is where correlation and regression analysis come into play. You shouldn’t use every variable in your model, as this will likely result in over-optimistic forecasts (and can also lead to unstable data models).

Step 6: Data Analysis 

The next step involves determining the best way to visualize and present your data and its resulting forecast. Analyzing past trends may help you determine what type of graph might work best – for example, if you see that sales usually increase on certain days of the year, a line graph might be more effective than a bar graph. Additionally, interactive visuals like graphs with drill-down capabilities allow users to explore different ways of looking at their data instead of seeing it all in one static chart.

Step 7: Verification 

This step involves comparing your data to actual, real-time trends and statistics. Doing so will allow you to see if the forecast is working as it should be - ideally, any numbers produced by your model will align with what actually happened during that time period.

Step 8: Track progress of forecasting strategy 

The final step for market forecasting is taking note of how well your strategy is working over time. If things are looking good after a couple months, don’t rest on your laurels – remember that business conditions can change faster than most models predict. Making adjustments to future forecasts based on changing circumstances ensures that companies can continue making effective plans for their future success. Because this process is part art and part science, no market forecast should ever be considered 100% accurate. 

Keeping tabs on how your forecasting strategy is doing. Compare it with the actual numbers which can help you correct course when necessary. So, that your entire business is ready for whatever the future may bring.

Wrapping Up

Sales forecasting helps companies plan ahead so they can sell enough goods or services to achieve their desired profits within a specific timeframe. Market forecasts are created by combining past sales data with information about variables that affect demand for the company’s products or services. Once complete, these forecasts are used internally to determine how many resources need to go into production of said goods or services in order to meet sales goals without wasting funds. 

Market forecasts help companies plan ahead so they can sell enough goods or services to achieve their desired profits within a specific timeframe. Whether a company is selling a product or service, market forecasting can be used to estimate demand for this offering and optimize resources accordingly. The main goal of forecasting is not predicting the future as much as it is figuring out what will influence consumer demand for your products. But also how these variables can best be integrated into your business strategy. This article took you through 8 steps that would help you create accurate forecasts – which in turn will allow you to make effective plans for your future success.

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Written by

Harsh Gupta

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