One of the biggest problems that eCommerce companies face is inventory management. Having too little or too much inventory for a product lowers profitability. Lack of inventory can also mean a lost customer.
There are many solutions for inventory management today. Most of these focus on forecasting sales for existing products or newer versions of existing products. There are fewer and less proven methods for forecasting sales of completely new products. And understandably so - without any historical sales data for comparable products, it is more intuition than science.
That said, there are ways to get some idea of how a new product will sell. Instead of directly looking for comparable products, information about product life cycles can be used.
Newly launched products are likely to have a life cycle similar to at least some products launched in the past couple of years. With this in mind, we can input product life cycle information to a learning algorithm to create "clusters" of products with similar sales patterns. Once we have the clusters defined, we identify commonalities within each cluster. Then, when a new product is launched, we only need to identify the cluster in which it falls to get a sales forecast.
Here are the steps you will want to follow -
Note: There is always a margin of error in forecasts, so this should always be supplemented with other qualitative information about the new product.
Need help setting up the above steps? Reach out here.