Store Performance with DILAX

City centers are booming. Everything is set for growth. And for change. Let’s look at the district of Mitte in Berlin. Still barely developed, the sparse retail trade at the beginning of the millennium concentrated by and large on just two streets: Berlin Mitte was the hub for small, trendy boutique stores. Today, almost 20 years later, the face of Mitte has completely changed. The district has been widely developed, and the exquisite small boutiques live in co-existence with big-name fashion chains and flagship stores.

A blessing for one, a curse for another

Retailers, brands, chain stores... many came, and just as many left. The trendy neighborhood of Mitte, one of the world’s most popular shopping hotspots, attracts large numbers of visitors. But numerous examples show that they alone do not fill the cash registers.

Why is revenue missing?

Every penny counts.

High rents, overhangs, personnel – costs rise, often with constant to falling revenues. Very few companies can still afford to have stores just for branding reasons – each individual store must perform, sales must be in tune with other chain stores in these times of tough competition.
There may be several reasons why revenues are missing. It’s worth researching the causes, because sometimes it’s enough to just adjust a few screws to get the store up and running again.

Local Data

For Retail Operations Managers

Statements about customer frequency help, but are not enough to bring about change on their own. With the help of valid data, I, the Head of Retail Operations, can relate the figures and compare this branch with others. One store is not exactly like another. The direct comparison in the Pareto benchmark helps me to understand where there is a problem, whether I can change something and what to do to improve performance.

Can I adopt routines from the best performing store?

  • Staff planning
  • Product placement
  • Flows from the changing room to the cash register

Growing organically

Once the problem has been identified, I am then able to find solutions for how to apply the strategy of my top performers to the lower performing stores or introduce further innovations that change performance for the better.

Changing processes iteratively

For more productive areas

Increasing rack density, i.e. more stock in store, does not always lead to an increase in sales in all departments. Good data analyses on customer in-store behavior reveal new design options: e.g. fewer displays and wider islands to facilitate easy access to the products and an all-round more pleasant shopping experience.

Positive effects are achieved on the basis of frequency-based staff planning with trained sales staff for direct sales work with customers (from fit to till) in terms of dwell time, return rate, conversion rate and average sales transaction.

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