Brick-and-mortar shoe retailers continue to face economic pressure, even though sales figures have recovered following the pandemic. The insolvency of several large shoe chains attracted particular media attention. Retail analytics are an indispensable tool for tailoring shoe shops even more closely to customer preferences and improving the shopping experience. In this article, we highlight how shoe shops are using retail analytics to prepare for the future.
The shoe market in transition
Total sales figures for the shoe market are now back to pre-pandemic levels. Around two-thirds of shoe sales are accounted for by brick-and-mortar shoe retailers, while online shoe retailers account for just under 20 per cent. The rest of shoe sales are accounted for by other types of businesses, such as fashion boutiques and department stores. Many shoe shops have failed to develop their business model and customer approach in recent years. Therefore, only some of the branch closures are a consequence of the coronavirus pandemic. The closures of large shoe chain stores were often due to unprofitability. Small shoe shops often lacked successors to take over the business. As a result, there are currently around 10,000 shoe shops in Germany that need to shape their future with innovative ideas and technologies.
Retail analytics as a tool for shoe stores
Many shoe shops still do not systematically analyse their customers on the sales floor. As a result, they are missing out on a lot of potential and falling behind the competition. With retail analytics, however, shoe shops can obtain a comprehensive picture of their customers and relevant performance indicators. Innovative 3D sensors that comply with data protection regulations and can be integrated into existing camera systems help to achieve this. Thanks to advances in artificial intelligence and image recognition, cameras deliver excellent results on customer structure and behaviour.
Modern technologies collect data in real time and evaluate it. In addition, the data obtained from the sales area can also be linked to other existing data, such as receipt and weather data. The data can be displayed and further processed on various output channels. This means that visitor frequency can be provided in real time via the web or mobile devices. Decision-makers can therefore view the most important key figures regardless of their location.
Data protection-compliant frequency measurement in front of and inside the shop
One key result of retail analytics is data on footfall, visitor frequency and customer frequency. Visitor frequency measurement determines how many visitors a store has and when visitor numbers are high or low. This data can be collected for different times and periods, enabling comparisons over time. Comparisons can also be made for the same periods for different branches.
The frequency data can also be combined with other company data to derive meaningful key figures. For example, visitor frequency and passer-by frequency can be used to calculate the capture rate. This indicates the proportion of passers-by who become visitors. In addition, aggregated data on the gender and age of visitors provides important guidance for the product range design of a shoe shop.
In-store optimisation: shop design and merchandising
Shop design, product placement and product presentation are not fixed in a shoe shop. They can be designed with extreme flexibility. There are no longer any classic seasons for shoes. This is because customer preferences are highly volatile in response to minor temperature fluctuations. It is therefore all the more important for shoe shops to place the right shoes in the right place at the right time and to have them in stock. Customer engagement and behaviour in the respective categories can be measured automatically and systematically using cameras and 3D sensors.
Highly and lowly frequented sales areas, average dwell times and typical customer routes are important data. Aisles and areas with high or low visitor traffic are easier to identify with retail analytics. As the data is available in real time, it helps to determine the success of changes within a short test period. The decision for or against a shop layout is then not based on gut feeling, but on facts.
Deploying staff efficiently in the business
As in many industries, there is also a shortage of staff in the specialist shoe trade. Existing staff must be deployed efficiently on the sales floor, at the cash registers and in the warehouse in order to perfectly meet customer needs and achieve company goals. Retail analytics helps with staff deployment planning based on visitor frequency and consulting requirements. Effective staffing is possible when shoe shops have knowledge of peak and off-peak times. In addition, modern sensor technology makes it possible to detect and predict queues. Store managers can, for example, define thresholds to avoid queues. If a threshold is exceeded, checkout staff are automatically notified via digital devices.
Sustainable footwear retail with retail analytics
Rising costs and sluggish consumption are putting pressure on shoe retailers. In addition, there are cross-industry challenges, including city centre development, skills shortages and bureaucracy. Personal advice and inspiration make buying shoes in a store an emotional shopping experience. Innovative technologies are essential to enable shoe shops to better align themselves with customer preferences. With data collected by cameras and sensors, shoe retailers can better understand the processes in a store and make data-driven optimisations. At Crosscan, we provide comprehensive advice on all technologies and potential areas of application. We look forward to hearing from you.
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