High Value, Low Contact: Emerging Retail Technology for a COVID-Influenced World
In this special guest feature, Melanie Nuce, Senior Vice President of Corporate Development at GS1 US, discusses extracting maximum consumer information from store traffic while also making the experience safe and contactless. Melanie leads a team that investigates new technologies, partnerships and business opportunities to increase the relevance and reach of GS1 Standards—the most widely used supply chain standards in the world. She oversees the exploration of collaboration opportunities to help businesses leverage emerging technologies including the Internet of Things (IoT), blockchain, and machine learning. She has more 20 years of retail supply chain experience, focusing in recent years on retail industry collaboration to improve inventory accuracy, exchanging standardized product data and achieving source to store supply chain visibility.
In mid-March, millions of Americans shifted their purchasing habits on a massive scale, causing unprecedented supply chain aftershocks still continuing today. Retailers have had to quickly act to ensure safe, contactless options are in place, while consumers crammed as much as eight years of spending growth into one month, according to the Shelby Report.
In many ways, the COVID-19 pandemic has been the unexpected driver of digital transformation that has been top of mind among the retail industry for years. Consumers now want to make the most of fewer shopping trips with as little contact as possible, and may be more open to personalization based on big data if it means more convenient and safer shopping experiences. This lessening “creep factor” could open up a new frontier for innovative brands, retailers and solution providers to launch and install high-value, low contact solutions that cater to the needs of pandemic-weary shoppers, while extracting maximum data for future engagement strategies.
To seize these new opportunities, CIOs and innovation managers need to take a thoughtful approach to new technology adoption and the data that supports it. They need to be certain these solutions are a win for brands and retailers, as well as the consumer long term. Here are three questions to ask to determine the most effective path forward.
Does the store adequately support the consumer’s needs?
In our COVID-influenced world, keeping shelves stocked–whether in store or online–has become a major challenge. Innovative startups with inventory management use cases are becoming more and more relevant to the needs of retailers who want to avoid a shelf availability scramble. In addition to predictability, brands and retailers can benefit from real-time reads on product movement and usage to fuel add-on and upselling opportunities.
Adrich, a smart consumer solution that provides real-time product use analytics, is one of the most promising examples of an emerging technology with relevance for our new normal. A thin, flexible label affixed behind a product’s regular label creates a feedback loop for brands and retailers to track consumer interactions with the product via the cloud and Bluetooth.
Tools like this pair quantitative and qualitative data to help create a deeper understanding of the consumer’s behaviors and solve immediate needs for inventory management. They create new sales opportunities through the use of data and enable store innovations that will help companies conduct more valuable, structured data collection.
Are we ready for “checking in” instead of “checking out?”
If the COVID-19 pandemic has taught us anything, it’s that consumers are adaptable when they need to be. Shoppers who tried curbside pickup once or twice before are now super users. In fact, 85% of shoppers have significantly increased curbside pickup since the pandemic began, according to a July-August survey from Incisiv and Manhattan Associates. Hitting the “check in” button on your phone for your curbside delivery is just as common as the decades-old practice of checking out at the traditional cash register.
This rapid digital transformation leads to even more opportunities to harness the power of data, and we should in turn see an uptick in the use of AI, IoT, and machine learning to help process it. For example, a German-based startup called rapitag utilizes an IoT platform in combination with digital product tags. Versatile in their use, the digital product tags provide in-store analytics and enable the convenience of a cashierless shopping experience with a built-in loss prevention tactic through the use of the smart tag. Once the consumer hits the “buy” button for a tagged product on their phone, the tag is released and the shopper is on their way. It’s these innovative ideas that will change our perceptions of checking out, while also making convenience a willing tradeoff for more data collection.
What will it take to turn Big Data into Good Data?
With increased data sharing in real time, now is the time for brands and retailers to standardize data to adequately prepare for more automation. Emerging technology solutions for the COVID era will require good quality product data to help them function as intended.
The foundational data required to match consumer demand with what’s contained in a store’s inventory ultimately rely on the common global format that standards provide. While technology and store experiences are changing, the same standards that have been widely used in supply chain and inventory management for decades apply to these solutions today. Emerging startups, who know they need to work with complete and accurate data sets, are often relieved when they discover that there’s no need to reinvent the wheel to standardize data. Standards bodies like GS1 US have provided guidance on the various uses of standards that have been engrained into retail since the barcode’s inception. Just like the barcode helps the product go “beep” in the checkout line, the standards that underpin those systems are applicable to reimagined store settings too. They provide a necessary bridge between the physical product and the data associated with it.
Stephen Hawking once said “Intelligence is the ability to adapt to change.” There must be a thoughtful approach to adapting to this new normal in order to solve short term challenges and build foundations for the future. Now is the time to consider the new possibilities for data to derive maximum value when new layers of technology are applied.
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