Most analytics stops at describing what happened. How many visits did we get? Where did they come from? Which centres grew, which fell? Useful, but incomplete. It tells you what did happen , not what should have happened . If you don’t know what a centre should  be doing given its catchment, competition and format, you can’t answer basic questions: Is this asset genuinely strong, or just average for its position? Is that suburb “difficult”, or are we just under-performing it?

Why We Choose Accuracy Over Speed Our team has over a decade's experience analysing mobile signal data, and we've learnt the hard way about the many pitfalls of this dataset and its wild spatial and temporal sample fluctuations. We are often asked about mobile-signal analytics platforms that deliver glossy insights at rapid speed and low cost. You may have seen one. Draw a polygon, hit “run”, and a few seconds later you get a neat set of charts. Under the hood, the process i

Stop Paying Monopoly Prices for Blunt Retail Analytics Retail property analytics hasn’t kept up with the market it’s meant to serve. If you’re a landlord, investor, retailer or leasing agent, you probably know the current options: Premium banking-data products with genuinely strong signal, but heavy price tags and usage restrictions. “Trade area” analysis where someone draws a neat shape on a map and calls it insight. Cheap data feeds and self-serve products that look impress