3 strategies for developing the data-driven store

Table of Contents

  1. Summary
  2. Mapping the retail journey
  3. The data-driven store landscape
  4. Key takeaways and next steps
  5. About Sangeet Paul Choudary

1. Summary

The retail store has traditionally been a destination inviting footfalls and converting them to transactions. Today, however, consumers do not engage with stores in this type of linear fashion, as they are always connected to the store. Many see the constantly distracted consumer and the abundance of choice across channels as threats to traditional retail. However, tracking customers on their journey provides new opportunities to retailers to engage with customers and achieve their business goals.

Retailers should take one of the following three strategic paths to best respond to new consumer behavior:

  • Participate in a data ecosystem. At the most rudimentary level, retailers can continue acting as destinations and only participate in data ecosystems to drive more targeted footfalls to their destinations. In this case, retailers may not need to focus much on data acquisition themselves but may still need to personalize the experience of the store leveraging the data they obtain from participating in these data ecosystems.
  • Adopt open retail. With the open-retail model, the retailer doesn’t need to focus on data acquisition but instead can largely focus on data management. Going down the open-retail path requires the retailer to mobilize developer ecosystems and create awareness about the unique access to data that its API provides.
  • Develop the store-as-a-platform. To provide an end-to-end solution and own the entire customer journey, retailers need to focus on data acquisition and management as well as the customer experience at all points in the journey. IT infrastructure largely predates the emergence of cloud computing as a viable choice for hosting mission-critical applications. Although large organizations are now showing real signs of adopting cloud computing as part of their IT estate, most cloud-based deployments still tend either to be for new and self-contained projects or to meet the needs of traditional development and testing functions.

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