In last week’s part 1, I shared my view on dynamic pricing on item-level and the mobile (no-line) checkout. Two topics that directly impact the shopping experience in the store. Today, I want to take a closer look at two more hidden technologies – Blockchain and Artificial Intelligence – and discuss how these topics relate to RFID in retail.
Blockchain seems to be “en vogue” if we stay in the area of fashion: everyone talks about it, few really understand it and success still needs to be proven. However, as nearly every day new messages circulate about that technology, mostly when it comes to the Bitcoin Index, it must be worth taking a closer look into it.
Shortly said, blockchain is a reliable, difficult-to-hack record of transactions. Blockchain is based on distributed ledger technology, which securely records information across a peer-to-peer network. Saying this, blockchain technology enables digital fingerprints and thus secure transactions among different parties without a central intermediary (e.g. a bank).
Blockchain entries are permanent, transparent and searchable.
With regards to retail, blockchain technology has the potential to improve transparency and accountability across the supply chain. More specifically, so-called “smart contracts” are self-executing agreements based on blockchain technology. They automatically trigger actions or payments once conditions are met. They can use real-time information, e.g. GPS data, to trigger an event, such as a transfer of ownership and funds. At every point where a product changes hands, throughout the supply chain from manufacturer to the point of sale, blockchain can record the transaction creating a real-time, permanent and un-corruptible history of that product along its journey.
Retailers are faced with the challenge to permanently accelerate lead times in order to bring new products and styles to the point of sale as quickly as possible. With Blockchain “see now, buy now” can get close, as the technology enables to instantly reduce time delays, added costs, and human error that plague transactions today.
To summarize, blockchain can facilitate greater visibility and trust in supply chains. This gets especially interesting in combination with EPCIS, the standard for event-driven tracking and tracing of individual items (ideally with RFID) along distributed supply streams and networks. However, at the moment, blockchain technology appears to be rather complex and still immature, but it is likely that the technology will play an important role in the future of product traceability in a connected world.
A while ago, “big data” was a huge buzzword in the retail world. Although everyone agreed on the potential of technology, it proves to be challenging to utilize the tools and create useful information out of tons of data. Still, or even more, than ever, combining different data streams to make better predictions about customer interests to influence their purchasing decisions is one of the hottest topics in retail. Most retailers realize that an insights-driven way of doing business leads to a competitive advantage, but also demands a different approach by putting artificial intelligence (AI) and customer insights (CI) at the centre of their business.
Drive conversion by combining contextual customer data and real-time inventory data.
As retailers have access to increasing amounts of data, there is a huge potential to combine the individual data sets and make more informed decisions. When, for example, all data from the e-commerce browsing and in-store shopping can be combined, retailers can continuously improve their (personalized) marketing campaigns (e.g. with “chat-bots” and “smart digital assistants”). Taking this one step further, retailers using RFID, who have item-level visibility of their inventory, can use the data to predict where their items need to be to make sure that "no sales" are effectively prevented.
I find this forward-facing way of doing business is extremely exciting, as it evolves traditional retail analytics to a more proactive – and in the future even predictive – approach. Combining the different data streams to make better predictive and prescriptive models like what will happen in a particular store tomorrow and generate recommendations along the lines of where new stores should be opened, what content is relevant for whom, and what products should be stocked in which store. This topic gets even more interesting as online retailers are continuing their journey towards offering automated commerce (a-commerce) – the next trend after e-commerce and m-commerce.
What does this mean for retailers with physical stores? This Trendwatching article puts it like this: “As millions of consumers come to expect their online retail to be truly AUTOMATED, they'll bring heightened expectations of convenience with them to your physical locations. The pressure will be on you to ensure a joined-up experience.”