Retail sales forecasting is one of the smartest ways to predict future revenue based on quantitative and qualitative data. When opening a new business, many questions might trouble you. How many employees do I need to hire to hit my revenue goals? How will my business look three years from now in terms of revenue?

Data is always a great option since retailers don’t have a crystal ball to foresee the future. To avoid costly mistakes and minimize risks, you need to invest in sales forecasting in retail management. This will help you make smart decisions on your inventory, marketing, offers, and more. 

In this guide, we’ll break down the different strategies and tactics you can use to predict your moves in your next retail sales forecasting. Let’s get to it!

What is retail sales forecasting, and why is it important?

Sales forecasting in retail management predicts anticipated sales, revenue, supply and demand, lead generation, or new customers based on historical data and benchmarks. Although there’s no one-size-fits-all when it comes to retail sales forecasting, it certainly helps businesses set their future goals.

Retail sales forecasting has multiple benefits. Here are the most important ones:

  • Manage stock – it’s easy to run out of stock and disappoint your customers or overstock and waste your money on products that don’t sell. With sales forecasting, you can predict which products need to be restocked along with their profitability.
  • Launch new products – introducing new products can be a huge risk without accurately predicting your inventory, manufacturers, costs, suppliers, storage, and marketing. Sales forecasting minimizes that risk by revealing specific demographics of your audience that help you foresee their needs and whether a product will interest them or not.
  • Employ adequate staff – similar to product stock, having the proper number of employees to serve your customers is a win-win for everyone. With retail sales forecasting models, you can evaluate historical data based on customers’ peak hours or important days of the week and manage your staff efficiently.
  • Run better marketing campaigns – having accurate data on your target audience and knowing when to invest in marketing is key to business growth. For example, by knowing peak sales periods beforehand, you can run limited-time offers or double down on your loyalty program.

What are the different retail sales forecasting models?

There are different types of retail sales forecasting models and methods that you can access. Here are the most important ones:

1. Trend projection model

The trend projection model works best for businesses with historical data (ideally two years or more). This is because it essentially uses past sales data to reference future revenue. This means that with this method, we assume that the factors that led to past sales will continue to play an important role for future ones.

For this model to work, you need to consider any anomalies compared to past data that might lead to different outcomes. For example, if customer needs or competition have changed, it’s most likely that the trend projection model won’t lead to satisfactory results.

2. Barometric method

The barometric retail sales forecasting model uses three core indicators to deliver accurate data:

  • The leading indicator – it takes into account how performance indicates future events. For example, an increase of customers in your loyalty program projects more recurring future purchases.
  • The lagging indicator – it calculates the importance of past events for future revenue. For example, frequent product returns show a lack of success of the products you sold in the past, ultimately affecting future revenue.
  • Coincidental indicators – they take place in real-time. For example, staff turnover is a coincidental indicator that affects your store’s capacity for the near future.

3. Econometric method

The econometric method focuses on statistics and complex mathematical equations to combine sales data with other influential factors. This retail sales forecasting model is a bit more complicated than the rest, as it tries to predict future revenue by combining demand with coincidental factors.

For example, it will try to predict the demand for coffee based on a city’s population. It will also take into account economic conditions and external factors to give more accurate predictions. 

4. Market research & customer surveys

The market research retail sales forecasting model is based on customer surveys. So instead of guessing, you can always directly ask customers about their needs and preferences to form better products for them. 

This is valuable information for businesses in search of the right business location, as well as exploring new products and improving their existing ones.

5. Salesforce composite model

The salesforce composite retail sales forecasting model is all about making the most out of employees’ feedback. Your employees are the soldiers in the first line that know your customers better than anyone. They know their complaints, needs, frequently asked questions, and behaviors and are able to share tons of insights on how to handle them efficiently.

You can generate a forecast that accurately predicts users’ behaviors, supply and demand, future revenue, and overall customer experience based solely on employees’ feedback.

6. Delphi model 

Finally, the Delphi method utilizes a panel of experts who share their opinions anonymously based on your questionnaires. The replies sourced can help generate a retail sales forecast that tracks users’ expectations and consumer behaviors.

The mindset behind this method is relatively straightforward. What is it that you’re trying to understand about your business? What’s the problem you’re hoping to solve? You can answer these questions with the Delphi model.

Expanding your business with retail sales forecasting models

Analyzing data for your business is key for making the right decisions that minimize risks and grant future outcomes. At Dotlas, you can get access to thousands of data for individual locations you’re targeting and understand their characteristics. This will help you determine future sales areas, customer demographics, income levels, and delivery applications within a few clicks. Book a demo today and embark on your business journey with accurate data.

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