Better understand your customer with Retail Analytics
The seemingly boundless possibilities of the digitalization are changing the retail sector fundamentally. New business models and sales structures are necessary requirements to reach customers in a digital world and to keep in pace with the changing, customer-centric competition. Today’s customers are connected, they are demanding, empowered and equipped with unlimited information. The ability to understand and meet customer expectations is a primary driver of growth. And more than ever it is of permanent importance to engage with the customer and build a relationship.
How can CE retailers meet these challenges? One of the core parts of their strategy should be leveraging customer data. And this is where KPMG’s retail analytics solutions come into play: they provide data-based answers to acute questions of the CE sector: Who are my customers? How can I cluster them? What will be the ideal customer journeys and touchpoints for my personas? How can I create a workflow for orchestrated customer experience? The POS is a hugely important touchpoint in the overall client journey and needs to be much better understood.
Another focus point is to manage physical retail space in the era of shrinking productivity per space unit. Therefore retailers need transparency of catchment area and traffic analytics, prognostic macro- and sociodemographic data as well as the good old e-journal. Shop owners can only tap into the so far unaddressed shop potential if they understand two fundamental things: firstly, the real catchment area potential of every single POS in comparison to its today’s estimated potential and secondly, today’s archetype mix in contrast to the potential archetype mix resulting from catchment area analytics. By analyzing these questions, the retailer is able to optimize product offers as well as to know which location is profitable and what is the actual value of his POS. These analysis increase confidence on how to compete with competitors as well as how to design the sales space according to fact-based customer potentials.
As of now, Geo Analytics is successfully in operation. For example in South Tyrol, on behalf of the local trade association, KPMG analyzes the economies of agglomeration in order to support regional decision-making and improve planning accuracy for stationary retail developments.