category-performance-diagnosis

Root cause analysis for declining retail category sales decomposes performance changes into specific drivers like traffic, conversion rates, basket size, and pricing pressures to pinpoint exact decline factors. This structured methodology identifies whether drops stem from fewer visitors or reduced basket size.

E-commerce category performance diagnosis requires category sales data and product hierarchy as mandatory inputs. For comprehensive decomposition and deeper growth driver analysis, you should optionally provide traffic, basket, pricing, distribution, and broader market data.

Identifying growth drivers in retail analytics uses a structured, root-cause-driven methodology to analyze category health and decompose performance metrics. This approach isolates specific levers like traffic and conversion to reveal actionable improvement insights.

You can analyze category health using only category sales data and product hierarchy. However, omitting optional distribution and market data limits the comprehensive decomposition of external factors affecting your performance diagnosis and growth driver isolation.

Stagnant retail category sales despite steady traffic indicate underlying issues in conversion rates, basket size, or pricing pressures. A category performance diagnosis breaks down these specific growth drivers to uncover the root cause of the stagnation.