How to Estimate Sales on Amazon

Sales forecasting on Amazon is a critical component of any successful Amazon business. Improving forecasting accuracy, even by a small percentage, can significantly impact a company’s production and financial planning, marketing strategies, inventory control, and supply chain management.

Without reliable sales forecasts, ecommerce businesses risk overstocking (leading to increased storage costs and potential waste) or understocking (resulting in lost sales and dissatisfied customers). By investing in sales forecasting, Amazon ecommerce businesses can optimize operations, reduce costs, and maximize profits.

But how do you forecast your Amazon sales for a new product you haven’t sold before? Let’s dive in.

What Is Amazon Sales Forecasting?

Amazon sales forecasting is the practice of predicting future customer sales and demand for products sold on Amazon. It involves analyzing historical sales data, market trends, and other relevant factors to estimate future sales volume. This allows sellers to optimize inventory management and make informed decisions about stock levels and pricing to meet customer needs effectively.

How to Forecast Ecommerce Sales using Amazon Data

Amazon sales forecasting relies on analyzing historical data and market trends to predict future demand. But where do you get this data? Fortunately, Amazon is a massive ecommerce platform with a wealth of publicly available data. As of 2025, Amazon holds a 37.8% shareshare of the US ecommerce market—and it’s still growing. Including third-party sellers, the total number of products available on Amazon exceeds 350 million, making it a rich source of historical sales data. So, no matter what product you’re interested in selling, you’ll likely be able to find relevant data for analysis.

Businesses typically use a combination of statistical models, machine learning algorithms, and domain expertise to refine their forecasts. The process often includes:

• Collecting Data – Gather historical sales data from key sources like Amazon, Walmart, and Google. Consider seasonal trends, competitor insights, and external market factors for a comprehensive analysis.
• Choosing a Forecasting Model – Utilize time-series analysis, regression models, or AI-driven machine learning techniques.
• Analyzing Customer Behavior – Incorporate customer demographics, purchase history, and engagement trends.
• Adjusting for Market Conditions – Factor in economic trends, supply chain disruptions, and promotional campaigns.
• Validating the Forecast – Compare past forecasts to actual sales to refine and improve accuracy over time.

A well-executed sales forecasting strategy helps ecommerce businesses anticipate demand fluctuations and make proactive business decisions. Not all market conditions can be predicted, so you’ll need to monitor and maintain your algorithm as new market variables are introduced.

What Is the Best Formula for Amazon Sales Forecasting?

For ecommerce demand forecasting, especially when selling a product on Amazon, several commonly used formulas can help predict the number of units sold. Here are some of the most relevant methods:

Machine learning methods are becoming increasingly prevalent in demand forecasting. However, historical data is crucial—you’ll need a statistically significant dataset to make accurate predictions.

Accurate forecasting requires continuous monitoring and adjustment based on actual performance and market conditions. As the market changes, you’ll need to refine your calculations.

What Is an Amazon Sales Estimation API?

If you’re not a machine learning expert or mathematician, you’ll likely want to leverage an Amazon sales estimation tool. An Amazon Sales Estimation API is a software application that allows businesses to predict future sales revenue for their online store by analyzing historical sales data, market trends, and other relevant factors.

How It Works:

• Retrieves and processes historical sales data from Amazon for a product.
• Uses machine learning and statistical models to generate accurate sales forecasts.
• Provides real-time sales projections to assist with inventory management, marketing, promotion, and pricing strategies as the market evolves.

Benefits of Using an Amazon Sales Estimation API

1. Improved Inventory Management – Accurate forecasts help businesses maintain optimal stock levels, reducing overstocking and stockouts.
2. Reduced Costs – Minimizes expenses associated with overstocking and storage.
3. Enhanced Marketing Strategies – Understanding future demand enables businesses to fine-tune marketing efforts for peak seasons and targeted campaigns.
4. Optimized Pricing Strategies – Forecasting demand allows businesses to optimize pricing for maximum profitability.
5. Data-Driven Decision Making – Advanced analytics provide valuable insights that drive smarter, more strategic business choices.
6. Increased Customer Satisfaction – Ensures products are readily available when customers need them.

Traject Data’s Amazon Sales Estimation API

For businesses looking for a powerful and reliable sales forecasting solution, Traject Data’s Amazon Sales Estimation API is designed to provide accurate and actionable insights.

Key Features:

• Sales Estimates – Provides sales projections for individual products and categories.
• Real-Time Data Access – Uses up-to-date market trends and customer behavior insights so you can continually monitor while the market evolves.
• Customizable Forecasting Parameters – Adjust forecasts based on your products, industry, and geographic location.

By leveraging Traject Data’s Amazon Sales Estimation API, ecommerce businesses can make informed decisions on inventory, pricing, and marketing strategies—ultimately driving higher profitability.See how Traject Data’s Advanced Amazon Sales Estimation API can transform your sales forecasting and explore our detailed API documentation.