NEW YORK, Jan. 13, 2014 /PRNewswire/ -- RetailNext, Inc., the in-store analytics market leader, today announced the release of RetailNext 5.0, which includes new features specifically designed for retail marketing professionals. The 5.0 platform introduces a suite of ShopperBase analytics products, Department Path Analysis, Guest Wi-Fi and personalization, Mobile Browsing Analytics, a custom analyst package, and a number of user interface enhancements. The new releases significantly improve the depth and breadth of customer behavior analytics available to retailers and shopping centers worldwide.
"RetailNext is tackling some of the hardest retail marketing problems today with the new 5.0 release. We provide retailers with in-depth views of their customers and potential customers while in the store, whether engaged physically or through their smartphones, and offer a path to a personalized experience," said Alexei Agratchev, CEO of RetailNext. "By using this actionable data, marketers can improve the in-store experience, optimize new customer acquisition strategies, and increase the profit per shopper."
ShopperBase – At the core of RetailNext's 5.0 release is the ShopperBase analytics product suite. ShopperBase analytics addresses the needs of retail marketing professionals by uncovering valuable insights into who their shoppers are through shopper demographics, loyalty, lifestyle, and more.
"Today, retailers have a significant amount of information about who buys their products, but they lack insights into their potential customers who leave the store without a purchase," stated Maria Fernandez Guajardo, VP of Product Management, RetailNext. "RetailNext's ShopperBase analytics will lead the way in understanding who those potential customers are, how to attract more of them, and what it takes to convert them into buyers."
The suite expands previously available insights, such as gender and loyalty (new vs. repeat visitor and frequency), by including new shopper characteristics derived from the industry's largest variety of data sources. RetailNext can now report on shopper age, geographic origin, pre- and post-store visit history, and industry spend. With industry-first integration of the most complete in-store analytics data, retailers are equipped to measure and understand who their shopper segments are and how they change over time. These are the new metrics:
- Gender and Age – Adds shopper age as a new metric, complementing gender demographics.
- Geo-Origin – Shows the most common cities, states, and countries where customers reside, on a store-level and chain-level basis, and for a given timeframe. Users see changes in customer geographical origin based upon changes in key performance measures such as traffic, conversion, and shopper yield. They can also quickly overlay the percentage of local vs. non-local and domestic vs. international shoppers on top of metrics within the platform's Data Mining feature.
- Cross-Store Spending – Enables retailers to understand what other industries and stores customers shopped on the same day they shopped at a given store. As with Geo-Origin, the Cross-Store Spending snapshot lets users easily see how spending patterns change as traffic, conversion, average transaction value (ATV), and other measures change over time.
ShopperBase analytics is released in conjunction with RetailNext's latest set of performance analysis tools that enable retailers to easily identify top performing days, stores, and areas within each store. The interactive analysis tools help retailers test and measure marketing campaigns, drive advertising strategies and real estate planning based on geo location, evaluate complementary stores for cross-promotional opportunities, and understand the link between key performance indicators (KPIs) and shopper profiles to replicate best practices across all stores chain-wide.
"In previous years, the tasks of testing, measuring, and analyzing various marketing programs in brick-and-mortar retail was complicated, expensive, manually burdensome, and inefficient," says Maria. "ShopperBase analytics provides insights across all stores, at all times, offering a true view of the retailer's local shopper base and marketing effectiveness – and in an easy, automated, and cost-effective way."
Department Path Analysis – Using existing Wi-Fi networks or dedicated sensors, RetailNext 5.0 can determine the position of smartphones and tablets inside a retail store and visualize the path to purchase through each department. Historical data can be used to identify a shopper's interests based on dwell time in each department, understand traffic flow between departments, measure loyalty (repeat vs. first-time visits) by department, and identify lost purchase opportunities. Real-time department-level location data are included in RetailNext's Personalization API to add context to in-store digital interactions, such as promoting nearby products through SMS or mobile apps.
Guest Wi-Fi and Personalization – Guest Wi-Fi is an attractive way to engage omnichannel shoppers as they look for product information and "socialize" the shopping experience using Facebook, Twitter, Instagram, and other sites. With poor cellular coverage in many shopping centers and increasingly restrictive data plans, omnichannel shoppers are eager to take advantage of Wi-Fi whenever possible. Following the company's acquisition of Nearbuy Systems, RetailNext has integrated the first location-based Wi-Fi Analytics platform able to manage guest-Wi-Fi services and provide a real-time personalization API that integrates shopper data for more targeted and personalized marketing. More than 100,000 new shoppers opt in daily, enabling retailers to engage with them on a one-to-one basis and influence purchases through personalized campaigns while they are in stores. Partnered with CRM database, marketing database, marketing automation, and loyalty program providers, RetailNext helps marketers ensure that communications and promotions are timely and relevant across channels.
Mobile Browsing Analytics – The opt-in customer base product contributes to RetailNext's robust mobile browsing analytics, which analyze sites and products being browsed, search terms being used, social media activity within the store, and more. Retailers are able to quantify the impact of "showrooming" on the business, gleaned from deep insights about shopper mobile browsing behaviors while they are in the store and engaged with the brand.
Custom Analyst Package – The 5.0 release provides data to scientists, consultants, and other retail analysts, with access to the underlying data that feed all the RetailNext metrics via a pre-packaged, structured format that offers the deepest understanding of how customer behavior influences buying. To optimize the value of the findings, RetailNext has formed a Professional Services Team of retail experts to aid customers in adopting the emerging technologies that are critical for today's retail organizations.
RetailNext is the leader in Applied Big Data for brick-and-mortar retail, delivering real-time analytics that enable retailers, shopping centers, and manufacturers to collect, analyze, and visualize in-store data. The company's patented solution uses best-in-class video analytics, Wi-Fi detection, Bluetooth, data from point-of-sale systems, and other sources to automatically inform retailers about how people engage with their stores. The highly scalable RetailNext platform easily integrates with promotional calendars, staffing systems, and even weather services, to analyze how internal and external factors impact customer shopping patterns, providing retailers with the ability to identify opportunities for growth, execute changes, and measure success.
RetailNext measures the behavior of more than 800 million shoppers per year by collecting data from more than 65,000 sensors in retail stores and analyzing trillions of data points. Headquartered in San Jose, CA, RetailNext is a growing global brand operating in 33 countries.
RetailNext, Inc. and RetailNext are trademarks of RetailNext Inc. in the United States.