ECommerce forecasting: A guide to profitable sales growth

Managing supply and demand in eCommerce is a balancing act. If the scales tip too far either way, you risk harming your profits and stunting business growth. ECommerce forecasting stabilizes the balance and gives you the insights you need to avoid overstocking, swerve understocking, and make profitable business decisions.

In this guide, we will dive into some eCommerce forecasting strategies that you can use to increase sales and profit. But first, what is demand forecasting in eCommerce, and why should you be doing it?

What is eCommerce forecasting?

ECommerce forecasting involves analyzing a range of historical and real-time data, such as past sales, market trends, seasonality, and consumer behavior, to predict future product demands. It guarantees that inventory levels are optimized for specific periods and that pricing, production planning, and marketing strategies are aligned with customer demands.

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Understanding the types of demand forecasting

There are 4 main types of eCommerce demand forecasting that you need to know: Macro-level, micro-level, short-term, and long-term. 

Macro-level demand forecasting

Macro-level forecasting considers the external trends, events, and forces that disrupt eCommerce at scale. For example, a nationwide demand for more sustainable products might lead to a decrease in single-use plastic product sales. So, this change in customer behavior would force many retailers to adapt and start selling bamboo or recycled paper alternatives. 

Other external factors impacting macro-level demand include economic downturns and competition. Monitoring them can help you predict potential supply chain issues, mitigate the financial impact of challenges, and even spot opportunities for product expansion. 

Micro-level demand forecasting

Micro-level forecasting focuses on the more specific external factors that affect demand. It zeroes in on specific industries, customer segments, or geographics to predict, overcome, and capitalize on challenges.

Let’s say a certain location is predicted to experience an abnormally lengthy spell of hot weather. ECommerce appliance stores might increase their inventory of fans and air conditioners to meet projected demand. Clothes stores might amplify their orders on sandals, shorts, and summer dresses. 

Long-term demand forecasting

Long-term demand forecasting involves making projections between 1 to 4 years in advance. It relies on extensive historical sales data, external data, market research, case studies, and more. 

As well as helping you identify and prepare for seasonal and annual patterns, long-term projections are vital if you’re pursuing investments, partnerships, or global eCommerce expansion. It gives you the insights to map your growth trajectory and assess long-term risks.

Short-term demand forecasting

Demand forecasting can be done for short-term projections, typically between 3 to 12 months. As well as planning for one-off events (such as Black Friday sales), short-term forecasting helps you make the day-to-day marketing, sales, and supply chain decisions that keep business ticking along.

Benefits of accurate eCommerce forecasting

From amplified sales growth to enhanced customer satisfaction, here’s why eCommerce forecasting is so vital.

Amplified sales growth

When you know what your customers want, you can optimize your inventory and make strategic pricing and promotional decisions. Demand forecasting enables you to capitalize on sales opportunities, meeting customer demands while maximizing profit margins.

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Streamlined inventory management

Demand forecasting uses historical and real-time data to optimize inventory levels. With data-backed evidence of previous sales, product movement, and current stock, you can make informed inventory management decisions and reduce the risk of stockouts and overstock. Most importantly, it offers insights into what to buy, how much to buy, and when to buy it to meet demands. 

Elevated customer satisfaction

When you know exactly what your customers want and when they want it, you can promptly meet their demands and boost customer satisfaction and loyalty. 

This is where forecasting will rely heavily on your own previous data. By using customer surveys and customer order tracking software, you’ll have access to customer data and feedback as well as a detailed view of your order fulfillment process. These kinds of insights will help you make better decisions and give you the ability to predict customers' wants and needs. 

Improved decision-making efficiency

Making decisions is far less risky. With a forecast to hand, you can make quick, informed decisions about everything from your pricing strategy to inventory management. For example, if you were running low on a product, you can use your forecast to determine the profitability of ordering more stock. You might even decide to raise the price of low-supply, high-demand items to gain more profit. 

ECommerce forecasting challenges

Despite its many benefits, accurate eCommerce forecasting does have its challenges. Here’s what you should prepare for. 

Striking a balance with historical data

Modern businesses sit on mountains of data. If companies lack selectivity, they can be left sifting through masses of irrelevant, outdated data, ruining the precision of insights. For this reason, you should focus on collecting relevant, consistent, and up-to-date data. 

Plus, leaning too heavily on historical data can leave you blind to upcoming trends and innovations. Strike a balance between historical data and real-time insights to remain competitive and innovative.

Finally, remember to use and combine various data sources, from enterprise resource planning (ERP) software, Google Analytics, to time and expense management software for small businesses. This will help you balance your historical data by providing a more holistic view of your business and a better understanding of your forecast. 

For example, while Google Analytics may indicate new markets and audiences that you should be targeting, your time and expense software might also show that your marketing department is overworked and doesn’t currently have the capacity to focus on new campaigns. By combining your data, you can make more informed decisions and accurate forecasts. 

Recognizing the impact of external factors

Although you have no control over the economic climate, changing customer preferences, and technological advances, they have a critical effect on demand. Failing to foresee and accommodate external factors can skew forecasts and cripple business growth.

Take the drastic effect that the pandemic had on customer demand. Some businesses adapted and thrived by recognizing the long-term impact: cloud communications is a prime example. Peloton’s at-home fitness bike subscriptions spiked during the pandemic, but once gyms reopened, they struggled to maintain their success. 

But, there are some significant external factors that you do have minor control over, for example, when it comes to planning your inventory and stock. 

You can use your inventory planning software to forecast which products are more likely to be in demand at certain periods, such as summer and winter products, as well as to track different trends. 

For example, an online shoe store might discover that the increasingly hot summers have meant that wedding seasons have started to shift and so have shoe trends. By recognizing the impact of these factors and utilizing their forecasting tools, they can start adjusting their stock to include wedding sandals at the new more popular times of year to get married. 

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Strategies for effective eCommerce forecasting

So, how do you forecast successfully? Here are the main strategies that you should try.

Maximizing data precision

Data is your most important asset in eCommerce forecasting. But if your data is inaccurate or outdated, it will mislead your forecasts and harm decision-making. Follow the best practice of maximizing data precision by standardizing and validating the data you collect. 

Utilize accurate data sources

Make it a priority to utilize reliable internal and external data sources like: 

• Customer relationship management (CRM) systems.
• Web analytics platforms.
• Social media analytics.
• Accounting system analytics.
• Case studies from reputable sources.
• Customer feedback data.

Once you’ve established and collected data from reliable sources, you must standardize and validate it. Unify data from disparate sources and validate it to reduce the risk of inaccuracies and inconsistencies.

Implement advanced analytical models

Once you’ve got hold of your big data, how do you use it to extract insights?

The main analytical model you’ll need is a predictive analytical model. Predictive analytical models typically leverage AI and machine learning to estimate future performance by evaluating current and historical data, patterns, and trends. The 3 most utilized predictive analytics models are:

1. Classification: A supervised machine learning model that analyzes labeled historical data to identify similarities and relationships in datasets.
   
   
2. Clustering: An unsupervised learning model categorizing unlabeled data based on similar attributes and characteristics.
   
   
3. Regression: A form of predictive analysis that estimates the causal relationship between variables. This helps to determine patterns and how changing one or more variables will affect another. 

Continuously monitor and adjust

The older your eCommerce forecasts are, the more susceptible they become to inaccuracy. Changes in the economy, market trends, customer behavior, and more can rapidly influence demand, rendering your forecast obsolete. 

You can keep your growth strategies up-to-date and effective by continuously monitoring and adjusting your forecasts in response to new data. 

Strategic marketing alignment

Align marketing and sales with your demand forecasting using the following strategies. 

Integrate sales and marketing data

Demand forecasting needs marketing data just as much as sales data. To accurately gauge demand drivers, you need more than just a description of what your customers bought and when. You need to delve deeper into your customer segments' needs, preferences, pain points, and buying patterns. 

In doing so, you can answer the fundamental question: What motivates your customers to buy? This guides your demand forecast along with a bunch of other strategies. In fact, aligned sales and marketing teams are 107% more likely to meet their business goals. 

Image created by writer, data sourced from Hubspot 

Analyze customer behavior

Analyzing customer behavior tells you more than just what products your customers buy. It uncovers the factors that influence why, when, and how often customers buy the products they do. This is invaluable data to have because it can expose behavioral patterns that shape current and future market demands.

Adapt with flexibility to marketing shifts

The marketing materials that customers resonate with are in constant flux. Social platforms and content types surge and plummet in popularity. This is all alongside the marketing shifts we mentioned earlier, such as economic conditions and new competitors.

Adapt with fluidity to marketing shifts, leaving room in your forecast for flexibility. Keep updated with the latest AI-powered ecommerce tools to continuously meet customer expectations. 

Final thoughts

Meeting customer demands is at the core of eCommerce forecasting. When you can predict what your customers want and when they want it, you can optimize your inventory to meet their expectations. In doing so, you amplify your sales, profit, and growth, reduce costs, and improve production, marketing, and sales strategies.