Logistics & Forecasting
Demand Forecasting and Supply Planning for Marketplaces
Forecasting Demand to Manage Supply
Data Connections and Enhancement
Algorithm-Based Initial Forecasts
People-Driven Forecast Overrides
Stocking Rules
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Statistical Starting Forecasts with Manual Overrides
Statistical Starting Forecasts with Manual Overrides
Our effective demand planning starts with mathematically analyzing historical data, fed into forecasting software via API, and calculating a statistical forecast. By default, we leverage sales, seasonal trends, and out-of-stock data points in our modeling. These data points are processed through an array of algorithms to define the best-fit statistical forecast.
Manual overrides by our demand planners are made over the statistical forecasts to incorporate marketplace assumptions, product lifecycles, and promotional plans. These manual adjustments are crucial to have variables like new product launches, increased ad spend, or significant changes in market share or buy box status considered.
Marketplace-Specific Variables That Impact Demand Planning
Marketplace-Specific Variables That Impact Demand Planning
On open marketplaces like Amazon and Walmart, we must pay close attention to their unique variables. Two key metrics we focus on forecasting for Amazon are buy box % and sales rank.
Buy Box %: This metric informs us of the share of selling opportunities we win as a seller. The buy box can rapidly multiply or diminish sales as sellers enter and exit listings. For example, if we are one of two sellers of a product on Amazon and the other is projected to stop selling, our sales outlook may double upon their exit.
Sales Rank: This metric indicates a listing’s position in search results. Listings on the first page convert at a much higher rate than those on subsequent pages.
By closely monitoring buy box % and sales rank, our demand planners can make informed adjustments to demand and supply plans. This ensures that forecasts remain accurate and inventory levels are appropriately managed, allowing us to respond effectively to market dynamics.
Frequently Asked Questions
Is demand forecasting important for Amazon sellers and sellers on other marketplaces?
Forecasting allows sellers to optimize inventory levels, limit stockouts or overstocks, align marketing strategies, and improve business efficiency.
What variables should be considered in Amazon forecasting?
When forecasting Amazon inventory, consider variables such as historical sales data, market & seasonal trends, promotional calendars, the competitive landscape, historical out-of-stocks, buy box share, and pricing.
How often should I reset an Amazon forecast?
Forecasts should be updated regularly, recognizing the marketplace can change quickly. However, it is important to not overact to any data point without referencing others. Monthly is usually an appropriate frequency to adjust forecasts.
What tools can I use for Amazon marketplace forecasting?
Tools include Amazon’s own forecasting reports, third-party software like Streamline, Jungle Scout, and Helium 10, and predictive analytics platforms that offer detailed forecasting capabilities.
How can I improve the accuracy of my forecasts?
Improve accuracy by using comprehensive data, regularly reviewing and adjusting forecasts, leveraging advanced forecasting tools, and considering both qualitative and quantitative factors.
Can forecasting help with inventory management?
Yes, accurate forecasting ensures you maintain optimal inventory levels, avoiding both stockouts and excess inventory, leading to efficient inventory management and cost savings.
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