R.I.D.E. enables better use of your data and tech-enhanced business decisions to help you sleep soundly
R.I.D.E. scours live sources for retail purchase data
Shopin’s patent-pending A.I. processes the data.
Actionable insights reveal opportunities and trends
- Dominant Industry Brand
- Leading Jeans Brand
- Yoga Brand
- Shapewear Brand
- Clothing Brand
Sport brand coocurrence
R.I.D.E scoured the retail web to reveal how dominant sport brands pair in purchases with other brands, revealing opportunities never seen before.
Beyond just the perceived dominance of the brand in the market, Shopin discovered how the addition and removal of products would positively or negatively affect sales.
Shopin’s CTO Georgi Gospodinov, inventor of R.I.D.E., and previously Artificial Intelligence thought-leader and Director of Analytics and Insights at Walmart, shares his industry insights that lead to the birth of Shopin’s Retail Intelligence Data Engine.
In my career, I worked with some of the world’s largest retailers. One of them once dropped a simple 50 cent item off of its shelves, and a huge, unanticipated ripple effect impacting sales took place.
Because it was no longer available, the retailer experienced unexpected drops in sales among dozens of other items, and even lost some customers entirely.
RIDE helps you understand relationships among the merchandise in many different categories you sell, and avoid making decisions which set off negative ripple effects. And, RIDE helps you understand merchandise to add because it motivate sales, online and offline. RIDE helps you generate more sales and keep customers happy.
Be the first in line to plot Shopin’s Retail Intelligence Data Engine.
Delve deeper into the power of Shopin’s patent pending Retail Intelligence Data Engine. We’ve assembled a F.A.Q. list below, addressing many of the most commonly asked questions about our product.
Shopin’s Retail Intelligence Data Engine (R.I.D.E.) is a recommendation system built on comprehensive customer purchase data from across the retail industry. The recommendations help retailers and brands improve strategic and tactical decisions to grow their catalog and brand portfolio. The data-driven analytics engine infers insights from billions of transactions, tens of thousands of brands and thousands of retailers.
Yes. Shopin’s team built R.I.D.E from the ground up. We have applied for two patents for the product.
R.I.D.E. is a data-driven recommendation system using proprietary algorithms and patent-pending data architecture. The primary scope of the product is to capture and interpret interactions between brands, categories and items which are revealed as customers shop. R.I.D.E looks for trends across the comprehensive retail data we collect to reveal strong support among brands, categories and items.
The Retail Intelligence Data Engine is the brainchild of Shopin’s CTO Georgi Gospodinov and the patents are co-authored by Eran Eyal (Shopin Founder and Co-CEO), Mark Plaskow and Dr Richard Linares (M.I.T.)
R.I.D.E. is powered by purchase data, proprietary visual artificial intelligence and proprietary algorithms. We focus on purchase data as an “oracle of truth” in retail. Instead of modeling correlations based on hypotheticals such as “someone looked at this item so he may be interested in buying it”, R.I.D.E models recommendations based on merchandise shoppers purchase, and items that shoppers purchased with additional items or brands.
Purchase data is an ultimate data protocol, because it reveals intent that recommendation and predictive systems can rely on. With purchase data, we know actual merchandise purchased, additional items bought and paired with an item. R.I.D.E. examines relationships among purchase data, not only within one retailer or one brand, but across the comprehensive retail ecosystem.
R.I.D.E. incorporates our proprietary Visual Artificial Intelligence to identify merchandise across a comprehensive landscape of retail, placing the items into a universal taxonomy which our system analyzes. In upcoming versions, clients will be able to upload their catalog, have it analyzed and identify actionable insights on how competitors or collaborators are selling their products, how shoppers are buying their products and which products shoppers are pairing for purchase. These insights help unveil for retailers and brands opportunities for growth, both within a retailer’s or brand’s online properties, and across the online retail ecosystem.
R.I.D.E is a comprehensive recommendation system for retailers and brands designed to help increase sales. R.I.D.E. helps businesses enhance their shopper experience because we collect data reflecting billions of transactions, tens of thousands of brands and thousands of retailers. The data reflects shopper activity and a rich ecosystem of purchase data, aggregating a comprehensive view of the retail industry.
For a limited time, R.I.D.E. will be free to select pilot customers. We are dedicated to providing our customers with the highest quality product and service.
To get started with R.I.D.E., please schedule a demo by clicking on “Request a Demo” above to experience an overview and specify the best next steps to getting started together. We offer rigorous Proof of Concept design experiments to help assess the impact of R.I.D.E in answering specific questions relevant to a retailer or a brand.
Absolutely. By integrating your data with the R.I.D.E platform, we are able to tailor the model to address your brand portfolio, business needs and strategic decisions to help you grow sales.
R.I.D.E is designed at scale and currently provides recommendations with aggregated purchase data. The recommendations are based on comprehensive customer transactions from across the retail industry. In order to increase the power of the recommendation system and reveal personalized, customer-level recommendations, we would like to partner with retailers and brands to incorporate your customer data and transaction history within the R.I.D.E. system.