Master retail sales forecasting with key techniques

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 behavior. 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 retail 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!

What is sales forecasting?

At its most basic, a sales forecast is a tool used by businesses to predict sales. Sales forecasts help businesses 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 how to best build 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 laymen, 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 maximize 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 and customer satisfaction scores are 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 difference between demand forecasting and sales forecasting

Demand forecasting predicts the overall market demand for a product or service, considering factors like trends, seasonality, and external influences. In contrast, sales forecasting focuses specifically on a business’s expected sales, using past sales data and current customer insights. While demand forecasting looks at broader market trends, sales forecasting zeroes in on what your business is likely to sell.

Key influencing factors in sales forecasting for retail businesses

When it comes to sales forecasting in retail, a few key factors can really make a difference:

Customer demographics

Knowing who your customers are (like their age, income, and preferences) helps you tailor your products and marketing to hit the right notes. This info gives you a good idea of how different groups might react to what you’re selling.

Product value propositions

This is all about showing customers why your products are worth their time and money. A solid value proposition can make your stuff stand out from the crowd, which definitely influences buying decisions and, in turn, your sales forecasts.

Optimal sales channels

Whether you’re selling in-store, online, or both, figuring out where your customers like to shop is key. This helps you focus your efforts on the channels that actually bring in the bucks.

Competitive positioning 

Keeping an eye on how your products compare to the competition is crucial too. Are you offering better prices, higher quality, or something unique? Knowing this can help you anticipate how customers might shift their preferences, which directly impacts your sales predictions.

Customer buying behavior 

Finally, don’t forget about customer buying behavior. Understanding how your customers make their purchasing decisions—like if they’re more swayed by discounts, loyalty rewards, or online reviews—can give you some serious insights. Spotting trends in their behavior lets you create sales forecasts that are right on the money, helping you manage your inventory and marketing strategies better.

Overcoming Challenges in Sales Forecasting

Sales forecasting can come with its fair share of challenges, but there are ways to tackle them head-on.

Common constraints and limitations

• Data quality: If your historical sales data is incomplete or inaccurate, your sales or demand forecast will be off. Garbage in, garbage out, right?
• Seasonality: Some products fly off the shelves during certain times of the year, while others might tank. Figuring out these ups and downs can be tricky.
• Changing consumer behavior: Customer preferences can change on a dime due to trends or economic shifts.
• External factors: Things like market trends or unexpected events (hello, global pandemics) can really throw a wrench in your sales predictions.
• Limited resources: Not every business has the budget or staff for fancy forecasting tools, which can make for a less than accurate sales forecast.

Strategies for improving forecast accuracy

Here are some winning strategies you could start today:

• Use multiple forecasting methods: Don’t limit yourself to a single forecasting approach. For instance, you might use quantitative methods, which rely on numerical data and statistical analysis, alongside qualitative methods, which take into account expert opinions and market research. This combination can give you a fuller picture of expected sales. You could analyze past sales numbers alongside insights from your sales team about upcoming promotions or trends they’re noticing in customer behavior.
• Collaborate across teams: Get input from different departments, such as sales, marketing, and customer service. Each team has a unique perspective that can enhance your forecasts. For instance, your marketing team might know about upcoming campaigns that could boost sales, while customer service might provide insights into customer complaints or preferences that could affect demand. Regular meetings or brainstorming sessions can help gather this information.
• Monitor and adjust regularly: If you notice discrepancies, take the time to understand why. For example, if a particular product sold more than expected, investigate what drove that demand—was it a successful marketing campaign, seasonal demand, or a trend? By adjusting your forecasts based on these insights, you can improve your accuracy over time.
• Factor in external influences: Stay informed about market trends and economic conditions that can impact your business. You could keep an eye on changes in consumer spending habits or supply chain issues that could affect product availability. Subscribe to industry reports, follow market news, and engage with trade associations to gather valuable information that can influence your sales predictions.

TIP: Don’t forget to check out our guide on how to protect your retail sales. It’s got tons of tips  to help you navigate the ever-changing landscape of retail forecasting and guarantee your business stays on track. 

The role of technology in sales forecasting

Technology helps you make more accurate predictions, run your operations smoothly and boost future revenue. Here’s how you can use technology to boost your sales forecasting.

Leveraging technology

Retail point of sale (POS) systems are key players here. Today’s POS systems do much more than just ring up sales. They gather important data in real time. This historical data is gold when it comes to spotting trends, understanding customer preferences, and predicting future sales. For example, if your POS shows that a certain product sells a lot during a particular season, you can adjust your inventory and marketing strategies to capitalize on that. Many POS systems also come with reporting tools that let you easily generate sales reports and forecasts, saving you time and improving efficiency.

Plus, many of these systems now have advanced analytics features that provide insights into how customers are buying. If you notice that people often buy one product along with another, you can stock up on both to meet that demand. This not only keeps customers happy but also helps you avoid lost sales because of being out of stock.

Integrating payments and inventory management

A good system keeps real-time tabs on your inventory levels based on sales data from your POS. This means you can see exactly how much stock you have and how quickly it’s selling. With this info, you can make smart choices about when to reorder products and how much to buy, preventing excess inventory or running out of popular items.

For instance, if your inventory management system tells you that a hot-selling item is running low, you can quickly order more before it’s gone. This proactive approach not only keeps your customers satisfied but also helps maintain a steady flow of revenue. Plus, having a clear view of your inventory allows you to look back at trends over time, making your future sales forecasts even more accurate.

On top of that, linking payment processing with your POS can make the checkout process smoother. A faster checkout experience can lead to more sales, and the data collected during transactions can give you even more insights for forecasting. Knowing which payment methods customers prefer can also help you fine-tune your offerings to meet their needs.

Measuring Sales Forecast Performance

To really know how well your sales forecasts are doing, you need to measure their performance. Here's how:

KPIs

Key performance indicators are metrics that give you insights into how accurately you’re predicting sales. Some important KPIs for sales forecasting include:

• Forecast accuracy: This measures how closely your forecasts match actual sales. A higher accuracy percentage means you’re making better predictions. You can calculate this by comparing your forecasted sales to the actual sales and figuring out the percentage of accuracy.
• Mean Absolute Percentage Error (MAPE): This is a popular method to quantify forecast accuracy. It shows the average percentage error between your forecasts and actual sales. A lower MAPE indicates that your forecasts are more precise.
• Sales growth rate: This KPI tracks the increase in sales over a specific period. It helps you see if your forecasts align with actual sales growth and whether your strategies are working.
• Stockouts and overstocks: Keeping an eye on how often you run out of popular items (stockouts) or have too much inventory (overstocks) can indicate how well your forecasting is functioning. Ideally, you want to minimize both to maximize sales and customer satisfaction.

Evaluating forecast and accuracy

To evaluate how accurate your forecasts are, you should regularly review and compare them with actual sales data. Start by setting a specific time frame—like monthly or quarterly—to assess your forecasts. Look for patterns or discrepancies between what you predicted and what actually happened.

If you find that your forecasts are consistently off, dig into the reasons why. Were there unexpected market changes? Did customer preferences shift? Analyzing these discrepancies can help you identify areas for improvement in your forecasting methods.

Additionally, consider using historical sales data to refine your forecasts. By examining past sales performance, you can better understand seasonal trends, customer buying behavior, and other factors that may influence sales. This information will make your forecasts more accurate over time.

Remember, measuring sales forecast performance is an ongoing process. By keeping track of your KPIs and continuously evaluating your accuracy, you’ll be able to fine-tune your forecasting strategies and make smarter decisions that drive sales and enhance your retail business’s success.

Final thoughts on retail sales forecasting

So there you have it, our complete guide on retail sales forecasting, packed with everything you need to know to boost your forecasting game. Sales forecasting might seem like a complex puzzle, but when you break it down into manageable pieces, it becomes a powerful tool for your retail business.

In the end, retail sales forecasting isn’t just about numbers. No, it’s about understanding your customers, anticipating their needs, and staying adaptable in a fast-paced market. By applying the strategies we’ve discussed, you can enhance your sales forecasts, improve customer satisfaction, and ultimately drive your retail success.