How a Data Strategy Can Unveil More Insights

The future of retail is data-driven.
The most successful retailers invest considerably in measurement and analysis tools across all stores and online levels to understand how they can continuously improve.

The most common metrics include:

  • Traffic, and where the customers came from.
  • Percentage of new vs. returning customers.
  • The number of searches, products searched, the number of purchased vs. abandoned.
  • Which store areas/site pages were visited, time spent, which were visited prior to a purchase, which led to abandonment.
  • Number of purchases made, average basket quantity and value.
  • Geo-Demographic, psychographic and behavioural traits of visitors and customers.

Whilst these areas are easy to track online with tools such as Google Analytics, they are more challenging to track in a store environment. Traffic counters, RFID tags, beacons, apps, CCTV and POS, CRM and loyalty data should be aggregated to glean critical insights. These insights must be analysed using an omni channel approach. A customer's’ journey is made of multiple touch points, and having a clearer view of behavioural patterns can lead to differentiated and more streamlined activity.

Mastering a Data Strategy

Successful retailers have a clear definition of data types in their business across:

  1. Product
  2. Customers
  3. Sales
  4. Finance
  5. Inventory
  6. Purchasing
  7. Supply Chain
  8. Store
  9. Online

For each of the nine areas above, they have clearly defined hierarchies with multiple levels of categorisation and tags, to be able to either analyse high-level trends or drill down into granular detail. The true power of a master data strategy comes from being able to drill-down on multiple types of operational data (e.g. Products + Customers + Inventory), to answer probing business questions. For example, it would be insightful to not only know what the best performing brands are in the womenswear category but also which items are within those best-performing brands? What are the common attributes and purchasing patterns of customers who have purchased these items? What channels and media touch-points made up their journey? What locations have the highest sales rates of these product types, categories, and attributes? Understanding operational and sales data can allow you to optimally plan assortments and inventory allocation for each store, lowering freight costs and increasing sales.

Score your business in each of the critical areas of practice to identify strengths, weaknesses and potential blind spots.

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