It’s been reported that by 2027, the e-commerce market could be worth over $7.9 trillion. It’s safe to say that e-commerce is a thriving big business.
However, it’s not always the most predictable industry where e-commerce demand forecasting comes into play. It helps you understand what products your customers want before they even know it themselves and, therefore, helps you boost your sales. That’s the power of accurate demand forecasting.
Let’s break down demand forecasting, why it’s a game-changer for your business, and how to use it to stay ahead of the competition. Read on to find out more.
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E-commerce demand forecasting is all about predicting future demand for products sold by online retailers.
So, how is this done? Well, several factors are in play when it comes to forecasting consumer demand. A good way to start is to analyze past sales data and look into market trends.
You can then anticipate which products will be popular and how much inventory you need to keep in stock. You can also plan marketing strategies. Accurate e-commerce demand forecasting ensures you’re ready to meet customer needs without overstocking or understocking.
Let’s look at some of the key benefits of e-commerce demand forecasting.
With accurate demand forecasting, you can maintain balanced inventory levels. You can avoid overstocking some items, reducing storage costs and minimizing the risk of unsold products.
(In fact, you can even forecast which items to discontinue altogether.) Optimizing stock this way can help you avoid missing sales opportunities, which could disappoint your customers.
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Another forecasting benefit is that it can help you make cost-effective business decisions. By purchasing inventory in line with expected demand, you can reduce expenses related to excess inventory.
This also reduces the number of items in the clearance section!
Customer satisfaction is one of the main things your business needs to get right. When customers find what they want when they want it, their satisfaction skyrockets.
Forecasting ensures that your products are available during peak times, leading to fewer lost sales and happy customers much more likely to return.
You can make informed decisions about pricing, promotions, and marketing strategies with accurate forecasts. You can design your business strategies with predicted demand in mind, optimize your overall performance, and ensure better results based on market trends.
E-commerce demand forecasting allows you to communicate and plan with your suppliers more effectively. You can provide them with more accurate demand predictions so they, in turn, can prepare the products for shipment before you need them.
With this system in place, you can ensure timely deliveries and avoid any last-minute rushes.
While e-commerce demand forecasting does have many benefits, you need to consider the following challenges.
Good quality data can make or break good sales forecasting. If you have inaccurate or incomplete data, it can lead to poor predictions and misguided decisions. So, always ensure your data is clean, accurate, and up-to-date for effective forecasting using a solid data pipeline.
One of the elements beyond your control is the market.
The e-commerce landscape is dynamic, with trends constantly evolving and consumer preferences regularly changing. Forecasting methods must adapt to these changes, which can be challenging, especially in fast-paced or newer markets.
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Implementing advanced forecasting tools and integrating them with your existing systems can be complex and costly. So, you must choose the right technology to fit your business needs.
This can enable a smooth integration process, which is essential for effective forecasting.
There are 5 key methods that businesses use to forecast demand.
This is where you analyze past sales data to predict future demand, and is common practice for many businesses.
Analyzing real past customer data can be invaluable in helping you predict how future sales may go, as it relies entirely on your sales history.
After reviewing historical sales records, you can then use calculations such as moving averages or exponential smoothing to identify trends and seasonality to forecast future demand.
Trend analysis is where you take a broader approach to data to look beyond past business trends and into the broader market. You need to study market trends and determine key external factors to understand long-term movements that may affect demand.
For instance, if eco-friendly trends increase as more people want to do their bit to help the planet, you’ll likely see sales in these areas of your product range.
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You can understand specific niche or segment performance by examining your practices with a fine-toothed comb. This can help you fix any supply chain issues you’re experiencing and further capitalize on your best-selling products.
You will need to consider past sales and cost of production and perhaps look to adjust the profit margins on your products.
You may want to use algorithms and artificial intelligence to analyze large datasets and predict future demand.
With this method, you can look at both short- and long-term demand trends and highlight any issues or changes you might need to make to ensure you can meet those demands. It will help your business if you can quickly adapt to any external factors.
A machine-learning model might analyze sales data, customer behavior, and external factors over a period of time to refine demand predictions.
Lastly, you may rely on your own expertise and judgment when it comes to sales trends.
By leveraging the knowledge and experience of industry experts and people within your team, you can strengthen your ability to forecast demand for your products.
This technique combines qualitative insights from experts with quantitative data to create a robust forecast. A method like this is useful when data is limited or when predicting new market trends.
Here are some best practices if you want to improve your sales with e-commerce demand forecasting.
You shouldn’t limit yourself to just one technique when there are so many useful methods available. Some may work better than others for your specific business, so it’s worth testing the waters to see which one yields the best results.
You can gather valuable insight into future demand by combining different forecasting methods, such as historical data analysis and industry expertise. This multi-method approach avoids the limitations of any single method and can deliver more accurate forecasts.
In reality, demand forecasting is a continuous process.
Especially when you include ever-changing consumer preferences fueled by social media trends, it’s good practice to regularly review and update your forecasts based on new data and market conditions.
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Ensure you integrate your forecasting tools with other business systems, such as a B2B customer data platform, inventory management tools, and your CRM platform. This integration will enable seamless data flow and ensure you can use forecasting to make business decisions.
Invest in training your team so they can truly understand and effectively use forecasting tools and methods. And if you involve various departments across sales, marketing, and suppliers, you can glean further valuable insights and improve your overall forecasting.
Sometimes, businesses make mistakes when forecasting demand; unfortunately, it’s not foolproof.
So when forecasts don’t match actual demand, look closely at any discrepancies to understand what went wrong and refine your methods to reduce the chance of anything similar happening again.
E-commerce demand forecasting isn’t just about predicting what’s going to sell—it’s about using those predictions to drive smarter decisions that boost your sales. Here’s how you can use demand forecasting to transform your sales strategy.
Forecasting data is about more than just managing inventory. It can also help personalize your customer’s shopping experience, create a more engaging experience, and reduce cart abandonment. By analyzing past sales trends and customer behavior, you can recommend products likely to appeal to individual customers.
For example, if you know a certain product is trending online, you can suggest related items or release limited edition bundle offers. This can lead to higher average order values and increased sales.
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Using demand forecasting, your marketing team can create new and innovative strategies, including creating content that drives sales. By understanding when certain products are likely to be in demand, they can perfectly time their marketing campaigns to coincide with the increase in demand.
For example, if the weather is warming up, your forecast may pick up demand for summer clothing. Subsequently, you can maximize your marketing efforts just before the season starts.
As we’ve discussed, stocking issues can lead to surplus inventory or no stock, damaging customer satisfaction. Accurate forecasting minimizes these issues by ensuring you have the right amount of stock for the time of year.
This reduces the chances of customers being disappointed by out-of-stock items and decreases the likelihood of returns due to overstocked, unwanted products.
When you introduce new products, it’s an exciting time for your business. You’ve spent months (maybe years) developing a new product you’re sure your customers will love. But when it’s time to hit the market, navigating the rollout process is another matter. If you’re not prepared, your product may fall flat.
E-commerce demand forecasting can provide you with insight that will tell you how well new items might perform based on the past performance of similar products. This data means you can gauge the initial stock levels you need and plan your launch strategy.
You can improve your supply chain efficiency when you predict demand because you work more closely with suppliers to ensure timely deliveries.
This proactive approach will help you prevent bottlenecks and delays and ensure that your products are available when your customers want them. It also allows for better negotiation with suppliers, which should save you money!
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Wondering how to calculate your sales forecast? You can use a few different methods.
You can use a few methods to forecast e-commerce demand: analyzing historical sales data, studying market trends, using technology like machine learning, and consulting industry experts.
There are several types of e-commerce demand forecasting, including quantitative methods (historical data analysis) and qualitative methods (expert judgment, market research). The one you should choose depends on your specific business needs.
The future of e-commerce demand forecasting will involve advanced technologies such as artificial intelligence. Using AI tools may help to enhance forecasting accuracy, adapt to market changes more swiftly, and provide deeper insights for better decision-making.
It’s clear that demand forecasting isn’t just a fancy term for predicting the future; it’s a vital tool that can seriously boost your e-commerce sales. By understanding and applying the right forecasting methods and best practices, you can set up your business for success.
You can manage inventory more effectively, improve customer satisfaction, and stay one step ahead of the competition. Put our insights into action and transform your e-commerce strategy.
Brooks Patterson is RudderStack’s Product Marketing Manager. RudderStack elegantly handles every piece of data from every source and syncs it with every tool in your stack. They are building the most advanced, bi-directional pipelines for your data stack.