How the Right Demand Forecasting Methods Can Propel Your E-Commerce Business Forward

How the Right Demand Forecasting Methods Can Propel Your E-Commerce Business Forward

By Nick Bartlett on December 7, 2022
Want to accurately forecast demand for your products? Here's what you need to know about the different demand forecasting models — and how to implement them.

How the Right Demand Forecasting Methods Can Propel Your E-Commerce Business Forward

The majority of retailers would love to be able to read the minds of their customers. 

Today we have corporate mind-reading of sorts; it's called demand forecasting.

Demand forecasting is a process in which retailers use historical sales data and other elements to try and predict demand for a specific time period. Elements that a demand forecast may use include:

  • Economic inputs
  • Industry factors
  • Market research results

Over the past few years, predicting demand has been particularly challenging; COVID-19 showed us just how quickly demand and supply chain schedules can shift — and the impact it can have when you then can't get anything out. 

When demand fluctuates more than historical norms, demand forecasting becomes more challenging — and more important.  

As demand fluctuates wildly due to inflation, fuel price uncertainty, and other factors, you need to include a wider range of company data and outside factors in your demand forecasting method. 

When you are trying to develop a demand forecasting strategy, many questions may pop up like:

  • What type of demand forecasting is best for your business? 
  • How can I use data and forecasts to optimize my demand chain? 
  • How can I ensure that my forecasts are accurate and helpful for my business goals?

If you and your business partners find yourselves asking these questions, it may be time to learn a little more about demand forecasting methods. Read on to discover our suggested forecasting methods for smarter business decisions.

Read about CBIP's Adaptable 4PL Logistics Services

Types of demand forecasting models

Demand forecasting is not one-size-fits-all; the variables that you should include in your forecasting model will vary depending on your business and product type. The best thing to do is run multiple forecasts using a few different types of models. 

Passive demand forecasting

When you are considering which models to use, think of what your business goals are for the next couple of years; are you aiming for growth, do you need to solve major demand problems, or are you striving for stability? 

If the latter is one of your top priorities, use a passive demand model as part of your forecasting repertoire. These models are comparatively simple; you are simply using your sales data from a month or season in a previous year to forecast what demand will be in the same season of the coming year.

Apart from its relative simplicity, the passive demand model:

  • Needs accurate historical sales data to produce accurate results
  • Does not require statistical calculations or economic inputs
  • Works well for companies looking to maintain their current level of revenue, as it assumes demand to be similar from year to year
  • Will not be as helpful if demand is fluctuating more than normal

Active demand forecasting

An active forecasting model is better for taking into account data you collect to help your company grow, like market research and specific ad campaigns.

For those who are in a start-up phase, or are just prioritizing growth for other reasons, this method will give you additional external intel that a passive model misses, namely:

  • Economic factors
  • Growth outlook for your industry
  • Consumer response to ad campaigns

Internal business forecasting

As the name implies, this forecasting method focuses on the factors occurring within your company that could potentially affect growth.

Establishing an accurate idea of what your capabilities are lets you figure out your ability to grow. Using an internal forecast, you can figure out what factors may be holding you back by looking at internal factors like:

  • Profit margins
  • Supply chain operations
  • Employees
  • Assets

External macro forecasting

When it comes to meeting company goals, external analysis is just as important as internal. In fact, research shows that businesses that use external data in forecasting are able to produce significantly better results. 

This method involves looking at trends in the economy, analyzing how those trends might affect your industry and your personal business, and factoring the results into your strategy. 

While external forecasting is a necessity for retailers hoping for growth, it's similarly important for those interested primarily in stability to make sure that no external factors are threatening to rock the boat. 

Additionally, each method should be conducted for a short-term projection and a long-term one. The short-term projection will be around 3-12 months to help you shift quickly as customer demands change, while the long-term projection allows you to formulate a long-term plan for your business, meaning for the next 1-5 years.

It’s important to note here that each model will give you slightly different results — but if results differ greatly between models, you might need to reevaluate the accuracy of your data and inputs.

Related: Why Warehouse Management Makes Your Business Better

What actually goes into a demand forecast?

There are tons of different ways to forecast demand for your e-commerce business, and each method falls into three categories:

  1. Qualitative
  2. Time series analysis
  3. Causal modeling

Take a look at each of the three categories and an example for each one.

Qualitative demand forecasting 

This method uses data like the opinion of an expert. An example of a qualitative method is market research.

Market research

Market research consists of surveys designed to give you a clearer picture of who your customer is; their needs, concerns, how much they are willing to spend, and how their demands are changing.

This type of forecasting can help your company:

  • More accurately target future marketing campaigns
  • Figure out your customer’s preferences
  • Get to know who your customer is

It takes time and money to continuously create and send out the surveys, but the data you get in return gives you invaluable info on future demand.

Time series analysis and projection

 Time series analysis uses historical data to figure out patterns. One of the simplest examples of this type is trend projection.

Trend projection

This type of model uses past sales data to predict future sales. The method is simple, but you need to account for any historical anomalies to avoid a highly inaccurate forecast.

For instance, if the prior year’s housing market was excellent but this year the market has tanked, it's likely that your bullish year selling home improvement products will not be repeated.

It’s easy to see how this method can fail to capture many important factors affecting demand, yet it's still a valuable tool. Used in tandem with more tedious methods, trend projection can help your business achieve sustainable growth.

Causal forecasting

The more sophisticated causal model type uses information about relationships between different systems. These types of forecasting models work particularly well for long-term forecasting and predicting turning points. For example, the econometric method is a type of causal forecasting.


The econometric model assesses the relationship between a dependent variable and one or more variables that affect that dependent variable. Think of a flower being the dependent variable, while the affecting or explanatory variables would be sunlight, soil quality, water, and position in the garden.

This model uses logarithmic and linear equations to calculate the relationship of each variable to the main variable. Like the flower in the garden, you pick one dependent variable, and then a slew of explanatory variables. Plugging them into your mathematical formula shows how each one affects the other. 

When one factor changes, you can use that change to recalculate and see how the dependent variable is likely to be affected.

Work with a 4PL partner who serves you the data needed for demand forecasting

With all the options for ways to forecast demand, getting started can be daunting. Adding to that, you need to assure that you are starting off with well-managed inventory and accurate data.

At CBIP, we work with a large network of logistics providers that use the latest tracking software and real-time data so that you know your data is accurate. We give you access to a wide variety of data on your company logistics, including analytics to support your demand forecasting process and help you make informed business decisions. 

Want to learn more about how CBIP can create a flexible network of partners for your business and provide you with expert logistics consulting along the way?

Get in contact with us today to receive a free assessment with our team.

About Author

Nick Bartlett

Nick Bartlett is CBIP’s director of sales and marketing. His expertise lies in marketing, supply chain management, and corporate retail experience. He honed his skills over 10+ years working across the Asia Pacific region and beyond.

Nick keeps a close eye on new markets and believes successful business operations come through value-based relationships.


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