Online shopping gathered momentum in the last decade and registered all time high growth during the Covid-19 pandemic. e-Commerce grew 25% in 2020, and sales touched almost US$ 5 trillion in 2021. However, the growth trajectory was not similar across markets. The European Union is a classic example of how each country has unique online shopping dynamics. This is mainly due to differences in consumer preferences and buying behaviour. 

Shifts in commerce across Europe

Figure 1

Traditionally, West European countries, including the Netherlands, Germany, and France, have more active online shoppers compared to the rest of Europe (Figure 1). 

Retailers in West Europe earn 25% of their revenue from digital channels. They have invested significantly in technology to boost omnichannel sales, and offer flexible buying and return options, including click-and-collect/ return in-store. Social commerce, in-store interactive screens, and self-checkout apps are used to engage and retain customers. 

Artificial intelligence (AI), machine learning (ML) and augmented reality (AR) technologies have also been leveraged to enhance the customer experience. For instance, Amazon’s ‘Just Walk Out’ technology monitors the items added to and removed from a shopping cart in real-time, ensuring convenient checkout at grocery stores. French retailer Carrefour has also implemented similar technology at its Flash 10/10 stores. 

But that is yesterday’s story. Today, consumers have refined tastes and expect personalised services and enhanced and convenient shopping experiences. They are willing to experiment with different retailers in search of the best experience. Leaving retailers to rely heavily on data to satisfy customers’ requirements and ensure they have no reason to switch loyalties.

Data underpins the shopping experience  

Retailers across product categories and store formats can enhance the shopping experience by investing in analytical systems and recommendation engines that convert data into rich insights. Leading retailers make smart use of customer data to enhance convenience, maximise the basket size, and even personalise the product offering.

Case in point: Adidas AM-4 shoes are designed and manufactured for runners of specific cities.For instance, data collected from primary research of runners needs in New York is used to make personalised running shoes for local customers.

At the same time, Tesco tracks customer buying behaviour to understand factors that influence the purchase of individual products as well as products that are very often purchased together. Tesco leverages data insights to deliver a more convenient in-store experience.

The ability to understand personal behaviour and buying patterns helps retailers optimise product strategies and improve customer engagement. However, it needs to be noted that customer consent is a prerequisite for collecting and using personal data.

Retailers monetising customer data directly or indirectly should comply with General Data Protection Regulation (GDPR) for acquisition, retention and sharing of personally identifiable information. Retailers need to integrate a robust data privacy policy with opt-in marketing strategies.  

Fulfilment-first retail

A deep understanding of the shopping habits of customers helps retailers not only deliver a personalised experience, but also resolve inventory issues and potential supply chain disruptions that may dilute the experience. Data solutions track inventory levels and real-time sales, which is used by modelling systems toaccurately predict SKU-level demand. 

Analytical insights help supply chain professionals identify bottlenecks, streamline inventory management, and amplify supply chain efficiencies at the backend. Amazon and Walmart implemented advanced systems to align transaction and sales data with real-time inventory. The approach drives prompt fulfilment and provides a competitive advantage.

AI / ML-driven data solutions streamline supply chain operations and improve cost efficiency. A digital thread connects the enterprise, enabling retailers to ship items directly from the manufacturer’s warehouse, when it has run out of stock. Analytics tools also help enterprises make informed decisions to reduce the carbon footprint through smart routing and logistics. 

Multiple purposes and cultural preference  

The Nordics show a tilt towards visiting physical stores which has prompted technology investments focused on enhancing in-store experiences. A Swedish retailer developed an app that provides health information on a product when scanned. The same app used in a competitor’s store allows the shopper to compare with the said retailer’s prices. 

AI solutions provide brick-and-mortar stores as well as e-Commerce enterprises with actionable insights to drive sales and improve omnichannel fulfilment. For instance, self-checkout functionality, flexible payment options, or value-added services can be implemented to grow revenue. 

As more customers gravitate to digital channels, there will be an influx of unstructured data from primary and third-party sources. Retailers should capitalise on data to better understand customer needs, and design personalised programmes to deepen engagement, increase wallet share, and develop strategies to enhance the shopping experience. 

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