Customer data is a key factor in the success of retailers. The better they know their customers, the more precisely they can tailor their offerings to them. The collection and storage of customer data therefore places high demands on data protection. Retailers must therefore exercise particular care when selecting technologies. These must be compliant with data protection regulations and secure. Footfall measurement using 3D sensors is 100% compliant with data protection regulations, as no personal data is stored, processed or collected.
Data collection when shopping in retail stores
Retailers collect and process a great deal of data on their customers: whether it be data from card payments, loyalty cards, in-store orders or CCTV. Retailers must therefore always consider the question of exactly which customer data may be collected and processed. Not everything that is technically possible is also legally permitted. On the one hand, companies want to collect as much data as possible. After all, the more extensive the data collection, the better customer behaviour can be analysed and predicted. But on the other hand, the principle of data minimisation is important. Consumers have rights over their data and do not want to be completely transparent.
Personal data is subject to special protection. This refers to information that can be used to identify an individual. This includes, for example, customers’ names, addresses or email addresses. The use of such personal data is permitted only where there is a legitimate interest and the data is used for a specific purpose. Furthermore, its use must comply with specific security standards. Consequently, the storage, disclosure and use of personal data may only take place with the consent of the customers concerned.
Customer master data, customer behaviour and visitor behaviour
In brick-and-mortar retail, customer data is primarily collected and stored through loyalty schemes. This includes name, address, age, email address and payment details. This customer data enables customer segmentation based on socio-demographic factors and allows for a more targeted approach to customers.
Retailers can collect additional data during a transaction. Purchase behaviour primarily includes product and sales data, such as the number of products purchased, product categories and the total spend per purchase. This purchase behaviour data can be linked to customer master data. However, it can also be collected independently of personal data.
However, a retailer doesn’t just want to understand its existing customers better. After all, most visitors are non-buyers. With retail analytics, it is possible to analyse all visitors to a store.
Customer analysis with Retail Analytics: 100% compliant with data protection regulations
Retail analytics must comply with the General Data Protection Regulation (GDPR). It applies to the collection, storage and processing of personal data within the EU. These data protection regulations provide standardised protection for all EU citizens. However, the GDPR does not prohibit the collection of data; rather, it regulates how data is handled and protected.
Furthermore, there is plenty of customer data that does not breach the GDPR yet still provides a wide range of insights into customer behaviour. To achieve this, identifiable data must be anonymised. For example, when measuring footfall using 3D sensors over the network, no videos or images are stored or transmitted. Processing and anonymisation take place directly within the camera or software. Consequently, only the relevant anonymised data and timestamps are output and stored, which do not allow any conclusions to be drawn about individuals. This protects the privacy of the data subjects.
Conclusion
Customer data is key to a retailer’s success. This applies both offline and online. After all, if retailers do not know who their customers are and what they want, they miss out on opportunities. However, it is not enough simply to collect as much data as possible; the right data must also be collected. Furthermore, the data obtained must be aggregated, analysed and correctly interpreted. Important insights often only emerge from comparing data over time and combining different datasets. Our retail analytics technologies are 100% compliant with data protection regulations. We would be happy to advise you on how to use them.
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Crosscan Data Insights Blog
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