An accurate measurement of price level differences across regions within a country is essential for assessing inequality in the distribution of real incomes and consumption expenditures. However, systematic attempts to compile sub-national Purchasing Power Parities (PPPs) on a regular basis have been hampered by the labour-intensive analyses required in processing traditional price data. The increasing availability of big data may change the current approach for estimating sub-national PPPs, although only for household consumption expenditures. This paper estimates spatial price indexes using a scanner dataset set up for experimental CPI computations in 2017 and includes information on prices, quantities and quality characteristics of products at barcode level. Our dataset refers to grocery products sold in a random sample of approximately 1,800 outlets across Italy belonging to the most important retail chains (95% of modern retail trade distribution), covering 55.4% of total retail trade distribution for this product category. We use various weighted index formulas for calculating consumption sub-national PPPs at detailed territorial level and at the lowest aggregate level at which no quantity or expenditure weights are usually available. Finally we report preliminary estimates of between-regional spatial price indexes for specific product groups and for Food and Non-Food consumption aggregates.