Store network

Boost store network productivity with smart analytics

In this post-Covid business environment, where online sales now account for 25% or more of retail sales, the majority of Australian retailers are reviewing their physical store network.

In reality, many retailers could be better served by maintaining a smaller, more efficient store network. To achieve this result, retailers pursue optimization efforts that generally fall into two parts.

The first stream of activity is the most obvious: to rationalize the network of stores. This involves closing underperforming or unprofitable stores and negotiating with landlords sustainable rents for the remaining stores.

The second stream of activity relates to productivity – optimizing store performance to ensure that they maximize sales with the lowest cost of service. When looking to improve productivity, retailers will increasingly rely on data to drive change across a range of functions. There are proven approaches to using data that can be adopted by all retailers. The most advanced retailers use tightly defined data and information that drive specific behaviors and results. There are a number of areas that retailers are focusing on.

Managing the performance of sales teams

A successful sales team will deliver up to 50% better in-store sales results. Store managers should have access to data KPIs first comparing their store to other similar stores and then by the salesperson to identify team strengths and weaknesses. KPIs should extend beyond sales and transaction values ​​to target specific behaviors that produce long-term results. This can include KPIs that measure engagement with VIP customers, capture of critical data for marketing purposes, participation in loyalty programs, and basket composition. Tracking KPIs on a consistent basis will inform both staff training and development opportunities as well as roster composition.

Staff efficiency

Store wages are one of the main costs of a retail operation, but unlike rent, they are variable and can be managed over time to reflect demand. To maximize in-store payroll spend productivity, successful retailers combine sales data with store traffic data and payroll information to optimize listings. For many retailers, this data already exists in the business, but store managers need to be able to look at it in an integrated and easy-to-digest way in order to implement effective changes to their listings.

Operational Execution

Data can play a role in driving operational behaviors which, in turn, will optimize sales opportunities. These often involve the use of exception-based alerts to trigger in-store action regarding a specific issue. The following are examples of such operational execution alerts:

  • Goods in transit not yet received.
  • Pending customer orders to be fulfilled.
  • Stock adjustment alerts.
  • Negative and fake stock.
  • Loss prevention.

Client orientation

Many retailers will focus on both retaining core customers and nurturing relationships with their key customers (think VIP). For many discretionary retailers, these key customers can represent a significant portion of revenue, so customer-centric retailers are now beginning to use data about these customers to drive change. Retailers provide store teams with not only the list of key customers, but also how they spend — and in some cases interact — with loyalty programs.

They drive productivity by ensuring that sales teams allocate enough time to key customers who move the sales needle. More importantly, they use this data to reconnect with lapsed customers using techniques like soon-to-expire loyalty points. Tracking metrics around key customer acquisition and retention is also becoming a critical strategy for many retailers.

How to enable this for store teams

Quality not quantity is key when it comes to using data to optimize the store network. Store managers don’t have the time or inclination to sift through tons of data to find the golden nuggets that will make a difference for them. It should be served in a concise, easy-to-digest method – think dashboards and exception-based insights. The real challenge for leaders looking to optimize their productivity is to properly prioritize store teams and ensure that the data provided is adequate to drive real change.

If you want to know more about optimization your store’s productivity, please visit The retail score and register for a webinar.