Is location a factor in the bankruptcy of a retail outlet?

This article has been published in Vastgoedmarkt as well.

Four very different Dutch retail chains, who had hoped to secure the future of their stores with good end-of-year sales, have recently had to shut their doors for good. Unfortunately sales seem to have been less than expected, and the chains have had to give up on their retail dreams this year.


The media have given several explanations for the chains’ failures. The most commonly mentioned is competition from online stores. This doesn’t just impact the volume of retail sales, but puts pressure on prices as well.

Intertoys in particular will have been impacted by online competition. For CoolCat and Sissy-Boy, the exceptionally long summer seems to have had a negative impact. Consumers started buying their winter clothes later than usual, and ended up buying less overall. The Op=Op chain seems to have overstretched itself by expanding (too) quickly.

Location strategy as an explanation

These are all very plausable solutions, and as always multiple factors are at play in the failure of a retail chain. So, too, is the chain’s location strategy. Whether this was a factor for these particular chains has been examined with the use of our Retail Risk Index. This index provides an indication of the survival rate of a particular store on a particular location. The higher the likelihood that this store will be gone by the end of the year, the higher the risk score.

The calculation of the risk score is based on a number of criteria. For this particular question we have looked at three factors:

  • The Street: a lot of vacancy, a lot of shop mutations, and the frequent repurposing of shops into apartments all have a negative impact on the character of a street. Eventually, this will cause lower numbers of shoppers. Fewer shoppers means fewer sales opportunities – making it difficult for the shop to continue making a profit. Shops that stay in the street often get into trouble later on and thus have a high ‘Street risk’.
  • The Sector: in the changing retail landscape of the Netherlands, we see that certain sectors are slowly disappearing from certain shopping areas. Take, for example, clothes shops. These are gradually moving away from smaller shopping areas. A clothes store in the village centre thus has a high ‘Sector risk’.
  • The Market: we make an estimate of the market pressures faced by the shop based on the shop’s catchment area. Relatively high numbers of competitors means higher market pressures. Together with the quality of the shop’s location, this determines the ‘Market risk’.

The four failed chains

In the case of Intertoys, the sector especially was very risky. Nevertheless, the riskiness of toy stores depends on the shopping area in which they are located. In inner city centres and large-scale shopping malls the risk is significantly lower than it is in the shopping areas of medium-sized cities and towns. In contrast, Intertoys is relatively speaking more strongly represented in medium-sized cities and towns than it is anywhere else. The chain therefore has an above average Sector Risk. The chain would probably have benefited from moving away from certain areas sooner.

For Op=Op the choice of location seems to be the most obvious explanation for the chain’s problems. Almost half the stores are in a high-risk street; in the sector as a whole, this is at a third of all stores. It seems that Op=Op has mainly chosen for cheap locations, and has not paid enough attention to the development of their chosen streets. Does such a location have enough potential in the long run to continue to function as a retail location? As the chain is going into its announced restart, and likely reorganisation, this is a factor to consider very seriously when assessing which stores to continue with.

The Sissy-Boy chain is mostly found in retail areas with a very high levels of competition. Sissy-Boy has mostly chosen shopping areas where lots of other fashion outlets are also represented. In those shopping areas, they have usually chosen the less desirable locations. In addition, the chain has not managed to differentiate itself enough in comparison with their competitors.

CoolCat, on the other hand, is an outlier. The chain scores well on all risk indicators. CoolCat has chosen for the right shopping areas, and usually also for the right streets in those areas. The Market Risk is average, and certainly no worse than that of their competitors. In this case it seems the chain mostly needs to be refreshed. The chain just isn’t as popular with young people as it used to be. The risk factors described here cannot explain the failure of CoolCat.

What can we learn from this?

In three out of four cases, the chains can improve their choice of location. This is not strange – the shopping street is changing at a rapid pace. Locations that were fine ten years ago are often not viable anymore.

We can draw three conclusions from this:

  1. Every chain needs to review its locations frequently, and not (as often happens) just when the rental contract comes to its end.
  2. A five-year contract is long, but looking ahead 10 years is almost impossible. Real estate owners’ desire for security is understandable, but unfortunately for them the retail market has become so unstable that no retailer should be forced to tie itself down for such a long period of time.
  3. We live in a time when data is becoming all-important for every business decision. Choice of location is not an exception, but rather a good example of this rule.

Locatus is happy to help you take the right decisions on your retail locations. Send us an email or give us a call when you want to know more about the Retail Risk Index or the Retail Road Map – the step-by-step guide to create your optimal retail network.

Retail Risk Index (RRI)

The Retail Risk Index sketches the risk profile of shops and shopping areas in the Netherlands. This information reduces uncertainty about the future of store locations - but what exactly is the RRI based on?

Gertjan Slob

Gertjan Slob is the Director of Research at Locatus. He is responsible for the entire data course. During his work, he is constantly analysing data, and frequently flags interesting trends and developments.