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24. 11. 2020

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The future of brick-and-mortar stores: how to get customers back into them?

With the change in customers‘ shopping behaviour due to the effect of the coronavirus pandemic and the associated quarantine measures, many brick-and-mortar stores are asking themselves how they can accommodate their customers and start selling again like they did before the arrival of the pandemic. They’re struggling with reduced sales, and some face the decision of whether it even makes sense to continue operating brick-and-mortar stores.

But how to get customers back into stores? People walk the streets, but they don’t really want to go into stores due to health concerns. The stores have decided to fight this in their own way. For example, they’re testing the installation of smart technology in shop windows. Their offer is therefore significantly personalised, and changes according to who is looking into the whop window at the given time. For example, it responds to the customer’s age and gender. Thanks to the interaction, a potential customer can even get a discount in the shop window. All this has just one goal – to get the customer into the store.

The shops‘ interactive offer is also complemented by the installation of so-called smart mirrors. You can not only try on clothes in front of them, but also see how you would look in a different colour variant. Moreover, based on the store’s product range, the mirror can also offer you other accessories or items of clothing which would go well with what you’re trying on.  

Thanks to new technological possibilities, stores‘ approach to customers is changing. Thus, in the near future, traders will not be concerned primarily with sales, but with building loyalty and positive customer experiences. In addition, this opens up the possibility of linking with loyalty cards. Smart technologies will recognise the customer, and immediately offer them tailored products via shop windows or screens. Stores are also considering setting up coffee corners (which is already happening in book stores and boutiques, for example), as well as offering consulting and other additional services, so that people spend as much time in them as possible – while complying with prescribed hygienic conditions, of course.

Hobby markets are also battling the new situation. They’ve switched to e-shops, and are dealing with warehouse and logistics automation

Large hobby markets are also adapting to the new situation. Their customers are already accustomed to shopping online. The stores enable them to select goods on the internet, make the purchase remotely and then just pick the goods up in the store. However, what’s bothering the hobby markets is the lack of necessary and functional systems. While in the past customers searched for goods in the store themselves, today it’s done for them by so-called pickers. They pick goods, and prepare them for the customers to collect.

However, the pickers lack navigation and a good inventory update system. At any given time, hobby markets are selling online and offline simultaneously. In practice, therefore, it often happens that the pickers are running around the store and searching for goods which they don’t know are out of stock. Individual items aren't copied into the system in real time, and so the pickers can’t see goods which may be long dispensed or sold. What’s the result? Dissatisfied customers, inaccuracies in inventory, missing items in warehouses, pickers working inefficiently etc.

How to automate and accelerate the entire process?

  • invest in systems which link information and data in real time,
  • use applications which plan pickers‘ trips through the warehouse using artificial intelligence – saving time and minimising errors,
  • make transparent, and begin collecting information, regarding the turnover of goods on shelves, and thus have a better overview of goods,
  • monitor customer behaviour.

Investment in real-time system interconnection

In practice, we often encounter a situation where teams or departments don’t share information with each other. A customer recently wanted to create a system for us which would monitor which vehicle is located in which loading area. In the end, there was no need to create a system – all that was required was to share information. The company had information regarding where every vehicle is located, but it wasn’t being shared across teams.

Another customer has a planogram in one system, an overview of available goods in another and data regarding sales of goods in a third. That’s nothing unusual in itself, but in this case the data is transferred among the systems manually! This process increases the risk of errors, whether from inattention or fatigue. What’s more, the data from these systems doesn’t make its way to production, so the goods are manufactured using a kind of estimate.

We always ask companies what information they would need to obtain for more efficient work, and we often find they’re already collecting most of this information. The problem is that individual departments don’t share the information with each other. They’re wasting both time and money.

Therefore:

  • interconnect the data in one system,
  • and create clear reporting which everyone can find in one place.

Real Time Location System (RTLS)

In an ideal case, every picker/driver has a road map, and a system which automatically deducts goods from the warehouse.

In practice, there is a relatively high employee turnover in warehouses. New workers must constantly be trained. What’s more, it takes time for them to get to become familiar with the warehouse, and know where to find every aisle, place and product. Ultimately, most errors which occur in logistics are due to the human factor.

Therefore, we recommend the implementation of systems which:

  • know where the picker/driver is located in real time,
  • know where in the warehouse the goods are located, and in what actual quantity,
  • create an efficient loading route
  • and display clear information for the picker regarding what they should collect, and when and where they should collect it.

What’s more, based on the collected data, it’s possible to optimise routes and perhaps also warehouse floor plans, as well as place goods efficiently.

Turnover of goods

Were increased sales able to pay for your advertising at the point of sale? Do you know which location the most goods are sold from? At the moment, there are few companies that can answer these and similar questions positively.

That's why we supply them with systems which:

  • have information about the quantity of goods on every shelf,
  • and monitor the turnover of the given goods.

Not only do they know in what store and where the goods need to be replenished; when we know what the interest in the goods is, and when we monitor this information over time and link it with other data on marketing, the weather and the day of the year, we can also predict customers' needs. Apart from that, we also know whether the advertising campaign was successful.

The trader's shelves are full, but even more importantly they know their customers' shopping behaviour, they know how to support it, and they can sell more.

Monitoring customer behaviour

Many stores still determine customer behaviour by questionnaire surveys or on-site observation. Both methods are irregular and costly, and therefore only take place occasionally. What's more, they suffer from errors caused by the way the data is obtained and recorded.

On the contrary, new technologies can collect information about customer behaviour continuously. We know who the customer is – whether it's a man, woman, group of people etc. We know their customer path through the store. We know what goods they're interested in, and we know all of this comprehensively and in an anonymised manner.

On the basis of the data, the store's management can modify the opening hours and adapt the number of staff to the footfall, thereby efficiently managing payroll costs. It's possible to modify the branch layout and the way in which the goods are displayed, thereby maximising customer satisfaction and with it sales and profit.

When we enrich the data with information such as the day of the week or the weather, the information can be linked with behavioural predictions.

Article by Adéla Mikschiková -  IoT Business Developement Manager - was published in the IT Systems monthly, vol. 10/2020, and on the server systemonline.cz.

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Adéla Mikschiková

Business Development Manager IoT

Adéla Mikschiková

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