eCommerce Sales Forecasting: How to Forecast Demand

Knowing how to forecast sales can be tricky, but every expert has to start somewhere. Learning the basics of an eCommerce sales forecast and demand forecast is crucial. How can you become good at something without first understanding its foundations?

This article will cover the components of an eCommerce forecast and teach you the basics requirements of a demand forecast. 

What is a Forecast?

In simple terms, an eCommerce sales forecast is a prediction of what a team, person, or company is going to sell within a specific time frame. This time frame can be anywhere from a week to a quarter or a year. 

An eCommerce forecast can be used by all types of online retailers, but it’s most often utilized by managers and directors.  A manager will use forecasting to estimate the business that their team is going to close, but a director will use it to project upcoming or future department sales. The VP of Sales can also use forecasting to project the organization’s overall sales. 

Forecasting is beneficial for a wide variety of business needs, including: 

  • Retail businesses 
  • Wholesale businesses 
  • Online businesses

To optimize their profits and predict consumer behavior, many retail and wholesale businesses make use of eCommerce sales forecasts. 

An eCommerce forecast is essential to online retailers; it helps them to evaluate past consumer behavior and revenue generated. It can also help to reveal patterns and seasonal trends. Retailers can then fill their inventory with the appropriate products.  

Once the basic evaluation is done, this information can be compared to the results of previous forecasts. The data is then used to generate a plan for which products should be reordered or kept in stock. 

Sales Forecasts vs. Demand Forecasts

It can be easy to confuse the terms or use them interchangeably, but the phrases “sales forecast” and “demand forecast” are distinctly different. So what is the main difference? The type of data that is being gathered. 

An eCommerce sales forecast is used to try to predict annual sales for specific periods of time, while a demand forecast is an attempt to project future demands for specific products or services. Despite using statistics and facts, you cannot call either forecast an exact science. 

Even though the two are different, eCommerce sales forecast and demand forecast practices go hand in hand. An accurate sales forecast relies upon an accurate demand forecast. 

We will cover both of these forecasting strategies in this article and look at how they interact with one another. Before this, however, it’s helpful to know about some of the subcategories of forecasting.

Qualitative Forecasting

To understand qualitative forecasting, you have to know what qualitative data is. Qualitative data relates to things that are observable but are not directly measurable. 

Building off of that, qualitative forecasting is a methodology that relies on experienced employees, as well as consultants, to provide insights and predictions about future trends and outcomes. 

One example of this methodology is the use of customer feedback. While a comment from a customer is not something that can be measured numerically, experts can evaluate each consumer’s response to certain products and gauge the likelihood of sales increasing (or decreasing). 

Quantitative Forecasting

So what is the definition of quantitative data?  Quantitative data is numerical data. This data is measurable and can be used to generate graphs or charts. 

This methodology is used to predict future sales trends. Quantitative forecasting calculates sales based on historical data, which is then used to project future sales.

Demand Forecasting for eCommerce

When it comes to predicting seasonal trends, demand forecasting is everything you need and more. When you want to know how to forecast demand, you’ll need to get some feedback. Demand forecasting is based on qualitative data — what is happening globally and in people’s lives. 

The holiday season is a huge time for online retail shops, and demand forecasting plays a big role in helping stores to prepare. By looking at the demand for products over certain periods of time using historical data, retailers can gain an understanding of which items are the most popular.

With this understanding, retailers can determine their stocking and inventory needs, which creates a more cost-efficient business.

Passive & Active Demand Forecasting

When you want to know how to forecast demand, you’ll want to understand passive and active methods. Passive and active demand forecasting are strategies that are used by retailers to conduct their forecasts. 

Passive forecasting is the easiest method; this method uses data from the past to help predict the future. It’s that simple! However, you have to have past data to build upon; without it, many startups will just try to use their best guess, which isn’t the sturdiest foundation to use to make decisions. 

One way around this is to research similar companies in your industry to gain an understanding of what their customers are buying. 

Active forecasting is a bit different. It accounts for market trends and other external factors. Active forecast models consider market research, campaigns, and expansion plans, too. This method looks at external factors, including the economic outlook, the growth projections for your industry, and projected cost savings. 

Active forecasting is important for technology-based businesses in particular. 

Calculating MAD & MAPE

Any researcher knows that human error must be accounted for. This is particularly true with demand forecasting. To do this, both MAD and MAPE are implemented during the demand forecast processes. 

MAD, or mean absolute deviation, is the average of the absolute value. This means that you’ll be viewing the difference between actual values and average values. This is used to calculate the demand of variability. 

MAPE, or the mean absolute percentage error, is a direct measure of a forecast’s accuracy. This accuracy is measured as a percentage. It is calculated by dividing the average absolute percent error for each time period — minus actual values — by actual values. 

Both mean absolute deviation and mean absolute percentage error are easy and efficient ways to record and calculate sales trends. Accuracy is important, and these tools are the best ways to ensure that your calculations remain as accurate as possible. 

To implement these calculations into your forecast, however, you’ll first need to keep track of your sales data.

Sales Forecasting for eCommerce

Sales forecasting is — and always should be — primarily quantitative. This means that you’ll need to use hard data in your sales forecast. 

If you do not have enough numerical data to analyze, however, you will need to do more qualitative research and make an estimate on the numbers.

There are a few steps to take, which include:

  • Establishing a baseline
  • Collecting and organizing data 
  • Calculating the historical growth rate

By following these steps, you will be able to use this data in your sales forecasting and increase profits. 

1. Establish a Baseline

The first step is to establish a baseline. Baseline surveys are a measure of key indicators before a project — your sales forecast — begins. 

Baseline surveys allow you to:

  • Establish realistic and measurable goals
  • Gather baseline data 
  • Provide a clear starting point to be able to identify benchmarks 

Baseline surveys help you to establish realistic goals for your business through baseline data and the creation of benchmarks. Once you identify the type of data you need to gather about your consumer base, you can then outline clear and realistic goals for your business. With a clear starting point, you can develop a list of indicators that represent progress or growth. 

It is important to understand break-even points and profit margins in this step, too. Without this knowledge, you won’t be able to properly gauge or measure your growth from the benchmark. 

2. Collect and Organize Data

To calculate the actual forecast, you first need a history of data. 

This step is easy enough for businesses that have been around for a while, but if you’re a startup or have recently opened for business, you may not have any idea where to start. In this case, it is best to make an educated guess on sales based on companies that are similar to yours. 

Additionally, you’ll have to get the spreadsheets out to keep your data organized. An alternative would be to invest in data management software, such as a point of sale system. 

Point of sale systems are digital networks that consist of a main computer that is linked to several checkout terminals (registers). This type of system is often supported by features like a barcode scanner and card payment terminals. 

The data points that are most helpful when you begin to collect data for forecasting sales include: 

  • Product sales per day 
  • Average sales per customer
  • Number of items sold each day
  • Number of customers who purchased items each day

Collecting and tracking your data is essential; it will help you start to build the history that you need. 

3. Calculate Historical Growth Rate

To calculate your historical growth rate, you’ll need to use the straight-line method. This method is simple to follow and is used to calculate the cost of a capital asset — your products. The method reflects the consumption patterns of your product sales.

To calculate the historical growth rate using the straight-line method, you simply divide the cost of a product, minus the salvage value, by its useful life.  

Solutions for eCommerce Forecasting

There are many challenges to eCommerce forecasting, such as the need to rely on past data and the fact that the market rapidly changes. In addition, if your business sells on multiple platforms, this can complicate your eCommerce forecasting. 

Consider a 3PL for eCommerce Order Management

This is where a 3PL steps in to save the day. These companies are an all-in-one solution for eCommerce needs. 

Here’s what a 3PL company can do for you:

  • Order management 
  • Order fulfillment 
  • Warehousing and storage 
  • Inventory management 

Some companies can do on-demand orders and handle the entire order process for you from start to finish. How helpful is that? Print Bind Ship does all of the above and more. 

We use integrated technology solutions that allow you to monitor your inventory night or day while maintaining highly accurate stock levels. We make orders and inventory tracking easy. 

With our services, you’ll have accurate data in no time. 

If you’re ready to say goodbye to forecasting and need a professional warehousing and fulfillment company to take the guesswork out of the sales process, get in contact with an expert for a free consultation here!