To understand why shoppers bought more items from the outside edges of the store rather than the inner aisles, diagnostic analytics would be the most appropriate type of data analytics.
Diagnostic analytics focuses on understanding the reasons behind past outcomes. In this case, it would help analyze shopping behavior, store layout, product placement, and other factors influencing why customers prefer the edges of the store.
Outcome analytics typically measures the results of certain actions without necessarily exploring the reasons behind those results. Predictive analytics forecasts future trends based on historical data, while prescriptive analytics suggests actions to achieve desired outcomes, neither of which would delve into understanding the underlying reasons for current shopper behavior as effectively as diagnostic analytics.