With the proliferation of high-definition cameras, computer vision, and AI applications, retail stores can now get real-time insights while customers shop.
As a retail customer, I love personalization. When a retailer knows me and anticipates my needs, my shopping experience is so much better. It’s my passion to work with retailers to build the technology foundation to make personalization possible – both online and, more recently, in brick-and-mortar stores. That’s one reason I’m excited to share the information in this blog.
Retailers know that personalization pays off. However, personalization requires real-world customer behavioral data, its analysis collected and managed on a foundation of agile technology. During the last two decades, that has been accomplished effectively online. Now, modern technology is enabling those same capabilities in brick-and-mortar stores, all to the delight of customers.
Shaping the best customer experiences
One significant pivot in brick-and-mortar capabilities has to do with data collection. Traditionally, data collection had to wait until the customer checked out – when it is too late to act.
That’s all changing. With today’s proliferation of high-definition cameras and computer vision / artificial intelligence applications, retail stores can now get real-time insights while the customer is shopping. As a result, brick-and-mortar retailers can deliver more personalized experiences to their customers. Retail owners can shape improved customer experiences and new business strategies by gaining key insights in several areas, such as customer behaviors, demographics, foot traffic, dwell time, and customer service.
Simplifying the retail reboot
Acquiring the technology to improve in-store customer experiences could be called a “reboot” or “transformation” for a reason: the digital transformation required is not trivial. In short, it can require a lot of complexity and be fraught with challenges such as upgrading infrastructure, increasing compute at the edge, and deploying and managing applications throughout their lifecycle on heterogeneous hardware with differing lifecycles.
Simultaneously, brick-and-mortar retailers need these capabilities quickly to stay competitive.
To accelerate deployment, ease the challenges and simplify the complexities, Dell Technologies has launched Dell Validated Design (DVD) for Retail Edge with VMware. The solution brings the advantages of VMware and VxRail to consolidate existing workloads and simplify application lifecycle management.
Edge Solution Capabilities and Examples for Retail
To leverage data for actionable insights, Dell Validated Designs for Retail Edge with Deep North enables retailers to deploy in-store computer vision-based analytics. The solution uses advanced machine learning algorithms connected to existing cameras to gain real-time customer and employee insights. By leveraging the DVD for Retail Edge with VMware as a foundational solution, these analytics can be run isolated and alongside current retail workloads.
Product Interaction, Anonymous Path Tracking, and Dwell Time: For brick-and-mortar retailers to effectively compete, it is critical they understand how customers behave during in-store visits. The solution can capture the amount of time a customer spends looking at a specific product or category. If retailers know the path a customer followed through a store and non-purchased products they interacted with prior to making a purchasing decision, retailers can better predict customer interests and requirements and even provide tailor-made promotions and cross-sell strategies.
Gathering behavioral insight in physical locations can be fraught with privacy and regulatory implications. Deep North’s technology does not leverage any personally identifiable markers, and no video footage is ever sent offsite. As a result, it’s anonymous by design. Learn more about Deep North’s privacy capabilities (e.g., GDPR, CCPA) here.
Customer Demographics: As the cornerstone of any retailer’s business intelligence, demographic data helps retailers understand customer needs and tailor product selection and marketing efforts accordingly. Typically, demographic data is collected at a distance. However, with Deep North’s technology, demographics such as age and gender can be collected directly and anonymously based on actual shopper demographics.
Heat Map: Aggregating customer path data helps retailers understand where customers spent time and what products may have caught their attention. This can be represented as a heat map, revealing which areas of the store are of higher value in terms of traffic patterns, thus allowing for smarter merchandising.
People Counting: Counting people is key to generating conversion ratios, a primary metric for many retailers. With this metric, retailers can gain insight into areas such as how many passers-by enter their store, how many shoppers purchase, and how many people are standing in line at a register. In turn, this enables retailers to properly staff during peak retail times and when checkout lanes get too long.
Customer Service: Customer service metrics help store owners understand how to increase point of sale conversions and improve customer-to-employee interaction times. Using customer analytics, retailers can predict month-on-month, quarter-on-quarter, or year-on-year revenue and also analyze the impact of any crucial event on business to better prepare for events in advance.
Related: Center for Edge Computing and 5G
It’s time to reboot
The Dell Validated Design for Retail with VMware is purpose-built to meet the specific needs of modern retailers. The solution lays a strong foundation that consolidates existing workloads and deploys new applications with minimal disruption to existing store operations. Together with in-store analytics from Deep North, the solution enables safe, anonymous, and valuable analytics in real-time, which was not possible before. Brick-and-mortar retailers’ time has come! It’s time to reboot and fully optimize your customer experiences.
Learn more about Dell Retail Edge Solutions and additional retail edge examples here.