How I Used PostgreSQL to Diagnose an Ecommerce Revenue Decline

Ecommerce businesses rarely struggle because of one obvious problem. Revenue falls, and the first instinct is often to blame pricing, weak products, seasonality, or “the market.” But those explanations are usually too vague to be useful. The better question is: What actually changed inside the business? Did the company stop acquiring new customers? Did returning customers buy less? Did average order value fall? Did top product categories lose momentum? I built a PostgreSQL project to answer exactly those questions using transactional ecommerce data. The business problem This analysis started with a simple question: Why did ecommerce revenue decline sharply in 2018-Q3 compared to the previous quarter? That question matters because top-line revenue alone does not tell you where to look next. If a business reacts without understanding the real cause, it can waste time and money fixing the wrong thing. For example: If the issue is weaker acquisition, the next step may be channel, traffic,