2017 Technology Preview: Exclusive Predictions from 15 Retail Executives
“Tailor in-store operations to improve customer experiences”
Successful retailers are constantly adapting their in-store practices to address changing consumer behaviour. Looking ahead to 2017, brick-and-mortar retailers — from large-scale department stores to smaller boutiques — will need to use shopper behaviour technologies, including traffic counting, to better understand their consumers and appropriately shape their operations.
Due to the increased level of competition today’s retailers face — across online and in-store — retail traffic and consumer behaviour technologies offer valuable insights that enable brand differentiation. Essentially, retailers can tailor in-store operations to better meet consumer expectations and provide an enhanced experience. Examples of this include:
- Leveraging retail traffic counts to more adequately staff stores during peak hours and ensure an optimal STAR (shopper-to-associate ratio),
which, in turn, increases sales and conversion rates;
- Utilising shopper behaviour insights to recognise the flow of shoppers throughout the physical store, adjusting the layout and displays to enhance in-store offerings and increase conversion as well as ATS (average transaction size); and
- Aligning associate tasks according to traffic counts in order to better meet customer demands and avoid leaving shoppers unattended, due
to associates spending labour hours stocking or folding as opposed to working directly with customers.
A critical factor to consider when determining how to tailor in-store operations in a specific store is how a retailer is determining the parameters for success or failure. That is, when retail leaders set a traffic or conversion goal for a single store, how are they arriving at that set goal? And is the goal one to which they can reasonably hold the store accountable?
2017 is the time to take data analyses to the next level. If they’re not already doing so, forward thinking retailers will look beyond single-store performance and appropriately consider each store in the context of a grander ecosystem of stores. This entails segmenting stores into “like” groups that all have similar performance expectations. These “like” groups, or peer groups, should be informed by individual store attributes that affect overall performance: for example, socioeconomic demographics of area, geography, seasonality, etc.
Proper peer grouping techniques, when combined with efforts to optimise various facets of the physical stores via traffic and shopper behaviour insights, allow retailers to create tailored best practices and sales goals for individual stores using a data-backed approach. Ultimately, this enables retailers to better delight shoppers, grow their bottom line and positively distinguish themselves from a variety of competing brands.
As the retail landscape shows no signs of slowing down, retailers that implement thoughtful technology solutions rooted in the physical store will see long-term success and prevent themselves from being another victim of competition.
“Due to the increased level of competition today’s retailers face — across online and in-store — retail traffic and consumer behaviour technologies offer valuable insights that enable brand differentiation.”
– Nick Pompa, ShopperTrak