A fresh look into store operations - opening hours and staffing

Katerina Bukhvostova

Opening hours and staffing

Earlier this week, I’ve had a chance to do a brisk shopping at one of the major shopping centres in the Helsinki city centre. With only a quick browse needed in search for a simple item, I’ve spent about an hour popping by several major fast fashion brands of a similar price range conveniently located next door to each other. It was not hard to notice, however, the difference in visitors at fairly similar stores.This has instantly made me question the main reasons of some stores being more of an attractive option than the other stores and whether retailers are doing anything to affect this.
Dozens of questions flooded my mind when I, an average millennial consumer, was walking along the rows of clothes without meeting a single person. Was I lucky to drop by at a good time? Is this store’s new collection simply boring? Maybe the brand is not trendy anymore? Is the staff not helpful? Luckily, my professional instincts prevailed, and I realised there could be hundreds of reasons why some stores are performing better and converting more. And what we do at Walkbase is directly related to that.  
While a lot of retailers out there have already taken firm steps towards learning more about their customers’ in-store behaviour by running IoT solutions at their stores, many of them are only looking into them. Before jumping into ‘the big unknown’, they continue relying on the irregular survey data and general assumptions, which is fine unless you are a multi-store retailer comparing individual stores’ performance. In this case, acting fast is something you have to consider if you wish to keep up with the tough competition. Being able to recognise the changes that need to be made immediately is crucial for attracting new customers and preventing the recurring ones from questioning whether you are doing well or not. 

“What are the immediate changes to store operations that could be made based on data?”

We get asked this question a lot. Even though there is no single formula which works for all, there are some good examples of the changes that were proven effective to some retailers: they positively affected their store performance and brought the conversion rates up. I will focus on the two of them in this blog post.

The change in the opening hours

In a perfect world, shoppers would arrive in similarly sized groups throughout the day, but the reality is far from this. A lunchtime, after work or a weekend shopping trip are far more appealing and doable options for most high street goers. However, it’s not the same for all the stores. A lot depends on the location, staff engagement, store layout and many other factors which you cannot predict by guessing. The foot traffic can be massively affected, for example, by the proximity of office buildings located nearby, or the travel hubs, or the lack of thereof.
Observing the patterns and the paths customers take, recognising the peak hours, high and low traffic times, passer-by window shoppers or repeat visitors is something that can be easily done with the IoT analytics in place. Having this valuable knowledge at hand would empower retailers to make data-driven decisions related to the opening hours, which would be focused on around the customers’ needs and bring some extra cash in. 

Staffing changes  

The staffing changes 

Not only being the face of your brand, educated and friendly staff directly impact the performance of every store in your patch. Avoiding the under- or overstaffing situations is one of the first things you can do based on the in-store analytics data. This will help you remain confident about the quality of the service you are providing and, at the same time, save the money by only having the needed amount of employees at a time. With the National Living Wage already hitting hard many high street retailers in the UK, this could be one smart move. To learn more about combatting the rise in staffing costs, check out this blog post.

On top of that, the real-time information on customer behaviour can incentivise staff to distinguish all visitors from the engaged ones and allows retailers set the whole new conversion metric, which is something Dune London have already implemented at their stores.

Quick fixes - what next?

After you start closely observing in-store customers behaviour in more detail, you will be able to do much more with the data. Establishing the set of metrics (KPIs) that are specific to your business are one of the key reasons why big chain retailers turn to detailed analytics when making high-level board decisions. Quality benchmarking gives senior management a great insight into the brand’s performance and helps to look at it in a unified way. 

There is a great article on working out the unique KPIs for your business, which I highly recommend you to check: Why every retailer should adopt new KPIs or risk losing sales.



Walkbase provides a retail analytics solution for improving the impact of marketing on physical stores and personalising in-store shopping experience.