How To Grow Your E-commerce Business With Demand Forecasting

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What is E-commerce Demand Forecasting?

E-commerce demand forecasting analyzes past retail data to predict future product demands and customers’ interest in buying certain items or services. It helps businesses make informed decisions that can estimate sales and revenue for the future. 

Demand forecasting for e-commerce is done with varying levels of specificity. For instance, retailers can choose a specific day of the week and predict product demands. Alternatively, retailers can also choose to predict how many people in their country of operation will buy their product next year. 

Types of Demand Forecasting

Overall, six types of demand forecasting methods exist, which are as follows: 

1. Macro-level: This type of demand forecasting in e-commerce analyzes broader industry and economic trends influencing the demand for a particular product. If you are an enterprise launching new products or are entering the market for the first time as a business, macro-level demand forecasting is the right option for you. 

2. Micro-level: Contrary to macro-level demand forecasting, in micro-level demand forecasting, brands must analyze their data and records to fix supply chain errors, comprehend risks in a particular category, and better monetize what is already working for the enterprise. 

Some forms of data that are helpful in micro-level forecasting are:

  • Cost of production
  • Cash flow
  • Past sales performance
  • The profit margin on various products and services

3. Short-term: Short-term demand forecasting is ideal for predicting and responding quickly to volatile market demands to change inventory, manpower, and production capacity. Usually, in short-term demand forecasting, data from 3-12 months are analyzed. 

4. Long-term: As the name suggests, long-term demand forecasting is used to predict future demands with the help of current market trends, regulations, demands, and so on. Long-term forecasting helps enterprises prepare better business strategies for the future and increase profits. 

What Can Impact Your E-commerce Demand Forecasting?

E-commerce demand planning and forecasting are affected by several factors, which are as follows: 

  • Seasonal trends: One of the main factors impacting demand forecasting in e-commerce is seasonal trends. Many companies put extra effort into cracking seasonal trends and demands to perform better throughout the year. A key example of a seasonal trend is Black Friday or Cyber Monday. 

For instance, in 2022, Australian enterprises made 4.97 billion USD during Black Friday sales. Furthermore, the average cart price per transaction was $167.99, a considerable increase from the average cart price in 2021 ($163.28). This shows how seasonal trends can impact demand forecasting; therefore, companies must stay prepared. 

  • Market size and location: Market size and location considerably influence demand forecasting. For instance, an international chips brand XYZ sells flavors like ‘ranch’ in Australia but curry-flavored spicy chips in Asian countries. This is because, depending on market location, customers’ preferences and tastes change. Hence, a particular product’s market size and location should be kept in mind while e-commerce product demand forecasting. 
  • Product categories: The type of product you sell will help you forecast future demands. For instance, if you are involved in selling high-priced electronic items, your sales velocity might be low. Therefore, you should analyze data for 24-48 months for accurate demand forecast results. 
  • Competitors: Needless to say, market competition influences enterprises in several different ways. An effective method to combat competitors is creating a unique selling point or USP for your company, paired with reliable goods and services. 

How Does Demand Forecasting Work?

Demand forecasting for e-commerce allows companies to understand sales trends and boost their inventory. It works in two ways – 

Qualitative forecasting

  • It looks into a broader economic environment to generate forecasts. 
  • You must consider factors like market research, industry experts’ opinions, and national or global economic circumstances. 

Quantitative data analytics

  • It considers previous hard data to develop a trend projection. It involves looking into previous sales data and finding patterns. 

Benefits of Demand Forecasting for E-commerce Businesses

The following are the biggest benefits of demand forecasting:

  • Risk reduction: An accurate demand forecasting in e-commerce helps businesses to reduce financial risks. It helps companies eliminate the risk of stock-outs and dead stocks. 
  • Improved inventory visibility: Since demand forecasting makes predictions based on past product movement, sales data, and current inventory levels, you will have a complete overview of your entire inventory. Consequently, you will always be able to have the right inventory level to satisfy varying customer demands. 
  • Increased customer satisfaction: Since e-commerce product demand forecasting helps optimize all aspects of inventory management, by extension, it also helps increase customer satisfaction. This is because customers highly value quick fulfillment experiences. Hence, with the right inventory levels, a business will never go out-of-stock and, thus, make quicker deliveries. 
  • Better demand planning: Demand forecasting in e-commerce helps enterprises pinpoint the exact periods when they have higher customer demands; it equips such companies to maintain steady stock levels during such periods. Subsequently, companies become well-equipped to deal with high-volume seasonal demands no matter how big they grow. 
  • Refined pricing strategy: Demand forecasting also helps companies refine their pricing strategy and make the most profits. You may increase the product’s price to capitalize on the high demand and low supply situation. 

Basic Steps in an E-commerce Demand Forecasting Process

E-commerce demand forecasting is a challenging job requiring continuous monitoring and adaptation but also a long-term approach. The five basic steps encompassing demand forecasting in e-commerce are as follows:

1. Define your objectives: The demand forecasting you carry out will depend on the goals you want to fulfill. Hence, depending on your product, inventory, logistics, marketing, and so on, you need to pick the right forecasting method. 

2. Collect data: Once your objectives are set, collect data. Some of the data worth collecting for analysis are:

  • Average sales per month: This helps you understand the number of units you are selling every month. Hence, you can adjust your inventory accordingly. 
  • Revenue per day: By understanding your daily revenue, you can monitor your daily trends and make future business strategies based on that. 
  • Average Order Value (AOV): AOV can be derived by dividing total revenue by the total number of orders. Higher AOV indicates more sales, which suggests higher demand for particular products. 
  • Net sales: It refers to the money your company makes after deducting reimbursements, discounts, and other associated costs. This metric is a reliable indicator of a company’s financial health and helps business owners plan their future budgets accordingly. 
  • Return rate: Enterprises need to monitor their return rates. A high return rate indicates problematic goods or services that must be corrected immediately to avoid losing customers. 

3. Analyze data: Analysis of the collected data is a key step in demand forecasting. This can be done manually or using e-commerce demand forecasting software. Either way, the analysis should be as accurate as possible to minimize future risks. Find patterns in the data, and understand and evaluate overall sales and demand. 

4. Forecast demand: You can finally move to forecast demands once all the previous steps are carried out. If your product had very low sales, find the root cause and forecast the products required for the next quarter.

5. Make adjustments: Adjust your inventory, budget, production capacity, and so on based on your forecast. For instance, if you have forecasted low sales for a particular product during March, you can lower the production and inventory of that product when the time comes. This will help save money, space, and other resources. 

Developing a Demand Forecasting Strategy

To develop an optimum e-commerce demand forecasting strategy, consider the following: 

  • Prioritizing the right data sources and tools: Accurate data is the most crucial aspect of demand forecasting in e-commerce. It helps you make future predictions. As mentioned, some reliable data forms worth noting are daily revenue, average monthly sales, return rates, and so on. 
  • Gaining insight into customer behaviors and preferences: Consider customer’s shopping habits to get real market demands. One of the ways to track a particular customer’s behavior is by monitoring what they buy and then suggesting similar products. 
  • Utilizing advanced inventory management practices: Forecasting product demand in e-commerce must be made in tandem with constant inventory and stock levels monitoring. It helps you understand which goods have high and low demand. 

Therefore, with advanced inventory management practices, such as inventory management tools and software, business owners can constantly monitor inventory levels at every stage of the order processing and fulfillment procedure.                                             

  • Balancing inventory levels for maximum efficiency: Inventory balancing refers to moving excess stock from one location to another, which is in high demand, but low in number. 

If demand forecasting is done correctly, it can show which market locations have a higher demand for which products. Consequently, it is up to businesses to balance their inventory levels based on these results to maximize quicker order fulfillment and customer satisfaction. 

  • Understanding and optimizing your sales channels to increase growth: Sales channels refer to how a business sells finished products affecting company sales. Broadly speaking, there are four sales channels; Wholesale, Business-to-Business, Business-to-Customer, and Retail. Furthermore, sales channels can also be divided into online and physical spaces. 
  • Maximizing opportunities in e-commerce platforms: E-commerce platforms are websites used to catalog products, register customer orders, and help maintain business-consumer relationships. Both small and big businesses can utilize good e-commerce platforms to reach a wide audience base. Furthermore, several e-commerce platforms provide real-time data on sales, product demand, returns, and user experience, all of which can help forecast e-commerce demand forecasting. 
  • Implementing the right technology solutions: Another strategy worth adopting is installing an e-commerce demand forecasting software. Such software will automatically analyze your past data and come up with the most accurate future demand projections in a short time. Furthermore, such tools will help you continuously monitor and track your numbers. 
  • Evaluating historical performance regularly and ensuring informed decisions: Lastly, demand forecasting in e-commerce is a dynamic process. While it is important to regularly monitor your data, it is also imperative to evaluate your past performance to understand both your right and wrong business moves. To add to that, be sure to make informed decisions taking all the data and statistics into account. Remember to not be biased, and you will surely be able to get a precise demand forecast result.

The Biggest E-commerce Inventory Forecasting Challenges

The top 3 most notable challenges related to e-commerce demand forecasting are discussed here:

  1. Picking the wrong forecasting methodology: With several demand forecasting methods, it can become confusing for businesses to understand which method can be applied to their enterprise. However, choosing the correct forecasting methodology is necessary to benefit from demand forecasting. For instance, if a brand wants to enter a new segment in the market, it should opt for qualitative and macro-level demand forecasting. If they pick any other forecasting methodology, the results may not be reliable or even accurate. 
  1. Using incomplete or incorrect data: E-commerce demand forecasting heavily relies on records and numbers to make calculations and projections. Therefore, if you cannot collect complete past supply chain, sales, or demand data, your data is inaccurate, leading to an inaccurate demand forecast. 
  1. Not considering supply chain delays: Whether you like it or not, supply chain delays cannot always be avoided. Hence, it is best to consider such delays while making demand forecast projections. Without considering supply chain delays, you may be unable to calculate the right amount of safety stock you should keep. This will increase your chances of selling out and being unable to satisfy customers. 

How Top E-Commerce Brands Take Control of Their Forecasting

Top e-commerce brands pay considerable attention to their e-commerce demand planning and forecasting to get the best results and enjoy all the benefits of demand forecasting. Some of the methods used by top brands to control their forecasting are:

Storing all relevant inventory data: By now you have surely understood the importance of data in e-commerce demand forecasting. Therefore, companies who want to take control of their forecasting store all relevant inventory data to make the most accurate projections. For instance, companies use specific software or manual methods to keep constant track of SKUs (Stock Keeping Units) and product movement, and hence, are immediately made aware when demand volume fluctuates. Consequently, the demand forecast results are updated as well. 

Supports operational inventory planning: Companies often opt for demand forecasting for e-commerce to determine optimal inventory levels. This helps them to meet customer demands and minimize the costs of carrying inventory. 

Proper production planning: Apart from data and inventory, production planning also helps manage demand forecasting for e-commerce. The top companies are choosing to make production plans 12 months ahead to take control of their demand forecasting results. In this way, brands are ready with adequate stock, but they also get enough time to negotiate better deals with manufacturers. 

Conclusion

 Demand forecasting in e-commerce helps companies make informed decisions about every aspect of the business, from manufacturing to supply chain management and order fulfillment. Hence, it is an integral part of e-commerce businesses that cannot be ignored. 

In this blog, we looked into the various benefits of demand forecasting and learned how it could be done based on a business’s goals and objectives. With the right approach, e-commerce demand forecasting can help companies achieve immense growth quickly.

FAQs

How to use demand forecasting to grow your e-commerce business?

E-commerce businesses use demand forecasting to make accurate predictions about future customer demands. Hence, they get the opportunity to be prepared with the right amount of stock beforehand and always have stock. This increases customer satisfaction and thus, helps businesses grow.

What is e-commerce demand forecasting?

E-commerce demand forecasting uses past sales and inventory data to predict future consumer demands and market trends.

Why is e-commerce demand forecasting important?

E-commerce demand forecasting helps businesses maintain optimum stock levels, reduce overstocking-related expenditures, and improve customer satisfaction. Hence, it is an integral part of businesses.

What types of demand forecasting are there?

Some e-commerce demand forecasting types are micro-level, macro-level, quantitative, and qualitative.

How to get started with demand forecasting?

To get started with demand forecasting, a company must first understand its objectives and then proceed to collect and analyze the relevant data such as average monthly sales, revenue per day, and so on.

Why do all e-commerce businesses need forecasting?

Small and big businesses need demand forecasting to accurately predict customer demands and keep the optimal amount of stock and serve customers.

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