How to Compare Store Performance of a Retail Portfolio in Pandemic Times

Retail executives often struggle to objectively evaluate the store performance of their portfolio due to changing market dynamics and consumer behaviours pre- and post-Covid. The good old Footfall Utilization Index (FUI) might be of help.

Retail business has always been tough. But today’s challenges for brick & mortar retailers reach unprecedented heights: partial or full shutdowns, consumers forced to shop online, stringent hygiene measures in stores, the emotional burden on sales staff dealing with consumers who don’t follow them, limited in-store traffic based on space allowance per consumer, raised consumer expectations regarding multichannel service… the list seems endless.

However, many retailers also report positive store performance developments: conversion rates of 50% and more for stores that previously struggled to reach 10%, higher average tickets as consumers buy more (increasing units per transaction) and more expensive items (increasing average price per item).

Change (Photo: Gerd Altmann auf Pixabay)

Change (Graphic: Gerd Altmann)

Changing consumer behaviours seem to be the only constant. Whenever stores reopen after a shutdown, that’s what retailers experience: Consumers who want or need to buy something visit their favourite stores and end up buying. They carefully plan upfront which stores they want to visit and what they want to buy. This explains the high conversion rates and average tickets. But will it last? When will baskets and conversion rates start to normalise?

When looking into actual store performance, the only negative KPI (key performance indicator) compared to pre-Covid-times is footfall, both street and in-store traffic. Additionally, there are significant differences depending on location. Smaller cities are less affected than big cities and local shopping centres attract more consumers (compared to pre-Covid-times) than larger malls. This all complicates the evaluation of store performance in a retail portfolio even further.

System error (Photo: PagDEV auf Pixabay

System error (Photo: PagDEV)

The Footfall Utilization Index (FUI)

I have already written about this KPI a couple of times. It may be the most objective retail KPI conceivable, because it allows you to compare large and small stores, stores with one or two floors, stores with optimal layouts and those with narrow and angled layouts, stores in top retail locations with stores in a local shopping centre, stores with a construction site in front of the entrance with others, and so on.

The FUI shows you how well each store team made use of the existing traffic development. It’s so objective because it compares each store with itself, measuring whether its turnover development was better or worse than its traffic development in any given period of time. And this is how to calculate it:


Footfall Utilization Index (Graphic: Heike Blank)

If the FUI scores above 1.0, retail staff managed to make more out of the actual footfall. If it scores below 1.0, staff couldn’t convert higher footfall into at least the same turnover growth, or to keep turnover drops on the same level as footfall drops.

Pre-Covid times would see a mix of FUIs above and below 1.0 like in below graphic:

Graphs showing turnover, traffic and FUI development of 10 post Covidstores

Pre-Covid Store Performance (Graphic: Heike Blank)

Store 2 and 6 show the best overall turnover development. But while store 2 achieves this with slightly lower traffic than last year,  store 6 benefits from slightly higher footfall. Therefore the FUI of store 2 is higher than that of store 6.

Store 5 and 10 are  outperforming the portfolio in terms of footfall utilization. Store 10 manages to achieve almost same turnover (99%) although footfall dropped by 10% vs. the previous year. And store 5 had to cope with a 13% footfall drop but still managed to generate 96% of last years turnover. Pre-Covid, we considered it normal if a store faced with a 5-10% footfall drop still achieved the previous year’s turnover. It is a matter of fact that conversion rates increase when footfall drops.

But what does store performance look like today, in the middle of a pandemic? With pre-planned store visits and clear buying intentions of most consumers, the resulting increased conversion rates and average tickets, portfolios that currently show a FUI below 1.0 clearly have a problem!

What we see nowadays in terms of FUI and store performance is something like this:

Graphs showing turnover, traffic and FUI development of 10 stores

Post-Covid store performance (Graphic: Heike Blank)

Not a single store performs at a FUI < 1. Unsurprisingly, all stores managed to make more of their shrinking traffic. But we still see a big variance in terms of performance between stores. Store 6 and 7 experience almost the same loss in traffic (-40%), but while store 6 is also loosing 20% of last year’s turnover, store 7 achieves a slight increase in turnover vs. last year and therefore shows the best FUI. The FUI still gives a good indication of store and staff performance in comparison with other stores in a retail portfolio, even if consumer behaviours change drastically.

Covid-Shopping (Photo: DrStClaire auf Pixabay)

Covid-Shopping (Photo: DrStClaire)

And it will continue to be helpful once the situation begins to normalise post-Covid. With more and more consumers getting vaccinated, people will begin to enjoy shopping again without a clear buying intention. Thus, we will see an increase in traffic and a reduction of conversion rates, unit per transaction and possibly the average transaction value.

When looking at store performance in 2022 compared to 2021, it’s likely that all or a majority of stores will suffer from an FUI below 1. But even then it will show which stores do better and which worse, regardless of how long they were actually open. And it will show which stores need more management attention and perhaps a motivational boost or a critical review of shoppers’ in-store experience as described by Torben Valsted in his recent article.

About the Author:

Heike Blank has worked for big organisations such as VF Europe and s.Oliver but also for niche brands such as Ecko Unltd. and Zoo York. Her executive experience in establishing and managing own retail and partner stores, made her look for a retail-KPI which allows an objective comparison and evaluation of stores in multiple countries, different locations and of different formats. Please feel free to email her for further discussion on these topics. Or for more about her see here.

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