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Retail Sales Forecasting - How To Make Accurate Sales Projections and Strategies

21 May 2024

Nothing is promised when running a business. One month could see an incredible wave of sales while the next could see it all come crashing down. Consumer demand can be fickle and to succeed you'll need to understand it as best you can.

Luckily, there are ways that you can predict sales and consumer behaviour. All successful retail businesses will use sales and demand forecasting methods to help them make sense of market trends and provide the best possible offering to their customers.

When used correctly, sales forecasting can be incredibly positive for a retail business. In this blog, we'll explain sales and demand forecasting in detail. This will include covering topics such as:

  • The difference between sales and demand forecasting
  • How to use forecasting in your business
  • How to ensure forecast accuracy

Let’s get right into it!

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What is sales forecasting?

In the most basic terms, a sales forecast is a tool used by businesses to predict sales. Sales forecasts help companies to predict their expected sales in a specific time frame. This time frame can be anything from a financial quarter to an entire financial year.

While measurement methods vary from industry to industry, most sales forecasts use historical sales data and current consumer trends to give their reading. Opinions on building a sales forecast vary wildly depending on who you're talking to.

Some forecasters may use their own experience in market research and intuition, while others use advanced AI systems to build forecasts. No matter how the forecast is built, every forecaster is trying to answer two main questions:

  • How much? - Every transaction in a retail store has a certain amount of money that it will bring into the business. In a sales forecast, forecasters have to use past sales data and factor in operating costs to work out exactly how much profit is made off of transactions.
  • When? - Establishing a time frame is very important for accurate forecasts. Forecasting will usually pick a time frame of a month, quarter, or financial year. By defining the time frame, forecasters can make an estimate of where the revenue will hit.

Despite their seemingly simple definitions, these two questions can be extremely difficult to answer. Some forecasters spend their entire careers perfecting a particular method that can only be applied to one specific industry or product. Forecasting is a very serious business.

For us laypeople, we can simplify the process used to answer these questions to five influencing factors:

  • Who - Forecasters should always consider who the prospective customer is. The better you know the customer, the easier it'll be to predict future customer demand.
  • What - What products are you trying to sell to your customers? What problems might you want to solve for your customers? How can your products solve these problems?
  • Where -  Where is best to maximise sales for your product? Different locations (both brick-and-mortar stores and online) have different desires. A product that sells out in-store may struggle to make significant online sales.
  • Why - Why would customers choose your product or service over something offered by your competitors? This includes competitor pricing and the quality of your offerings.
  • How - How do your customers make their purchasing decisions? Do you rely on impulse purchases and short-term profit or are you better served by building long-term professional relationships? What is your customer experience like?

These influencing factors lay bare the difficulties forecasters face while they're doing their jobs. While some of these factors are based on hard facts, some are conjecture after discussions or surveys with your customers. The art of sales forecasting is balancing the human know-how of experience with the understanding of machine learning.

The importance of sales forecasting in the retail industry

For a product to get into the hands of customers, there is a long supply chain of suppliers, designers, manufacturers, and other elements. These supply chains can sometimes be global in their scope. Sales forecasting is a large part of supply chain planning, as the chains only provide what retailers think the customers will want.

Sales forecast allows retailers to make educated guesses about customer behaviour. The forecasts inform their business decision, such as what they will sell in the next quarter and how much inventory to buy. This is what makes forecasting intensely important to the retail industry.

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Sales and demand forecasting are both very useful tools for retailers. While both have their drawbacks, both sales and demand forecasting can be used to inform business decisions, boost online sales, and drive profits.

Modern point of sale (POS) systems are a great tool that can be used to improve businesses and help them succeed. The Epos Now retail POS system is built with business owners in mind and can make a huge positive impact on how you do business.

Epos Now customers get access to a perfect payment processing service, our suite of leading integrations via our AppStore, and much, much more. We'll help you with everything from creating an online store to implementing retail inventory management tools. We’ve built our POS systems to suit your business needs, meaning you get all your tools in one place to make your sales forecasting easier.

The difference between demand forecasting and sales forecasting

Outside of the retail industry, it is a common misconception that sales forecasting and demand forecasting is the same thing. This is not the case. While the two concepts are similar in some ways, there are definable differences that are worth knowing.

The difference between sales and demand forecasting is in the name: 

Sales forecasting is how you predict sales.

Demand forecasting is how you predict demand. 

While sales forecasting only takes past sales into account, demand forecasting methods use all past data to build accurate forecasts. The data used in retail-demand forecasting include lost sales, historical data, past inventory levels, and more.

Businesses that use demand forecasting in retail can make accurate predictions about the demand for their products. Accurate demand forecasts can make it easier for businesses to meet future demand and predict future revenue. This makes retail demand forecasting more useful for businesses where inventory management is a key part of the job.

Think of it this way; a business may take a look at their sales data  to prepare an optimistic sales forecast. Based on this, they decide to order a lot of stock for the coming season. Because the business didn't prepare a demand forecast, they didn't know that customer demand for their product had dropped. This leaves them with too much inventory to sell and lost sales.

Retail demand forecasting methods

Much like sales forecasting, demand forecasting in retail can be broken down into three categories. Let's break these categories down:

  • Qualitative forecasts - These forecasts use market trends, research, and educated predictions from experts to reach their conclusions. With qualitative forecasting, customer confidence is key. Forecasters gather the relative information with methods like customer surveys and extensive market research. 
  • Time-series forecasts - In a similar way to sales forecasting, time-series forecasting uses sales data to identify trends, cycles, growth rates, and seasonality. These forecasts suffer from the same issue as sales forecasts as they use past sales as an indicator of future demand and so become increasingly inaccurate in the long term.
  • Causal modeling - Causal modeling uses a wide range of data to build simulations and predictions that ensure forecast accuracy. Depending on the product or service, these data sets could include anything from external factors such as housing prices, to internal factors such as overall ad spend. Due to the sheer amount of data used in causal modeling, forecasters will often use AI-powered demand forecasting to assist them.

Each of these categories represents different methodologies for building a demand forecast. The best analysts will often combine elements of these methodologies to create more accurate demand forecasts. 

Forecast accuracy is deeply important as it allows businesses to react to the wants of their target audience, increasing both customer satisfaction and overall profits. 

Our final thoughts

We hope you found this blog useful to understand retail sales forecasting, and how you can look at sales and demand forecasting to help inform your decisions and predictions for your business.

As part of our customer-first ethos, we keep our blog updated with helpful blogs and articles. Try one of our recent articles:

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