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RetailNext Showcases Next-Gen Machine Learning Analytics and Releases 2020 Holiday Season Analysis at NRF’s Big Show

Onboard demographics are introduced as part of the enhanced machine learning capabilities, along with a Holiday 2020 recap report

The measurement of the real-time condition of physical locations has become more important than ever. Data such as traffic and occupancy is key to the safe and efficient operations of retail stores”
— Alexei Agratchev, CEO and co-founder, RetailNext
SAN JOSE, CA, UNITED STATES, January 12, 2021 / -- Today, RetailNext Inc., the worldwide expert and market leader in smart store retail analytics for optimizing shopper experiences, announced general availability of its enhanced onboard machine learning analytics, further extending the capabilities of the Aurora sensor. RetailNext is showcasing its innovative solutions and industry leading expertise at NRF 2020, Chapter 1, presented by the National Retail Federation in a virtual format, beginning today.

“Throughout the pandemic that affected all of us over the past year, RetailNext has continued to be a trusted partner to over 450 retailers around the world. The measurement of the real-time condition of physical locations has become more important than ever. Data such as traffic and occupancy is key to the safe and efficient operations of stores and has been critical to power consumer-facing applications such as virtual queuing, store location based occupancy metrics, dynamic digital signage, and digital marketing based on the real-time condition of the store. We believe these types of applications will live well beyond the pandemic and we look forward to what the new year brings all of us,” said Alexei Agratchev, co-founder and CEO of RetailNext.

Expanded Platform Capabilities
Already an innovative market leader in delivering the complete view of how people navigate physical stores and other locations, the enhanced machine learning capabilities extend the value of the Aurora sensor through the onboard capabilities to classify demographics as part of the RetailNext Traffic 2.0 solution. Combined with RetailNext’s existing abilities to deliver extremely precise data on shopper activity, this innovation increases both the accuracy bar and adds to the set of contextualized data available for entrance analytics.

“From the beginning, we have always looked for ways to future proof a retailer’s investment in our platform, and the introduction of the onboard machine learning capabilities does just that. In the past year we have seen exponential growth in retailers’ use of our advanced analytics capabilities, particularly as they evaluate the role of the store in the post-Covid world. By layering in new analytics to their existing Aurora infrastructure, RetailNext is able to deliver more data, more accurately without additional hardware or deployment costs,” said Arun Nair, co-founder and CTO at RetailNext.

Release of Holiday 2020 Trend Report
RetailNext is also pleased to announce the publication of the Holiday 2020 Trend Report: “A Season Like No Other”, in collaboration with Mastercard. Drawing on Mastercard SpendingPulseTM, which measures overall retail sales across all payment types, this report provides a comprehensive look at in-store and online holiday sales performance in the United States—across sectors, geographies and time periods.

Addressing key questions about how the pandemic impacted shopping activity across the nation this holiday season, the report also features an analysis of RetailNext’s Performance Pulse insights on foot traffic and average transaction sizes across geographies and store type. Key findings includes:
- In spite of the expected traffic decreases, which came in at -35% to last year, shopper yield increased 26% as compared to 2019
- Conversion also increased by 4% points compared to last year, signaling more mission-based shopping
- Shoppers gravitated towards outdoor malls, outperforming overall trends at -28% to last Holiday, and within that, strip malls carried the category at -22%

“Holiday 2020 was as dynamic as the year itself, with more mission-specific shopping than we’ve seen in prior years as evidenced by the strong shopper yield and conversion performance,” said Lauren Bitar, Head of Retail Consulting and Customer Experience Insights at RetailNext.

About RetailNext
The first retail vertical IoT platform to bring e-commerce style shopper analytics to brick-and-mortar stores, brands and malls, RetailNext is a pioneer in focusing entirely on optimizing the shopper experience. Through its centralized SaaS platform, RetailNext automatically collects and analyzes shopper behavior data, providing retailers with insight to improve the shopper experience real time.

More than 450 retailers in over 90 countries have adopted RetailNext's analytics software and retail expertise to better understand the shopper journey in order to increase same-store sales, eliminate unnecessary costs and mitigate liability risks. RetailNext is headquartered in San Jose, Calif. Learn more at

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