Anyone who comes up with a 10% more effective method for recommending products to shoppers at Overstock.com will win $1 million. Overstock and its recommendation technology vendor, RichRelevance, are collaborating on the contest, modeled after a $1 million challenge by video rental e-retailer Netflix.
Overstock.com is offering a prize of up to $1 million to computer researchers who come up with a way to improve how the online retailer automatically recommends products to customers.
RecLab Prize on Overstock.com challenges researchers to advance the state of the art in product recommendations with new privacy-secure cloud environment
San Francisco – May 12, 2011 – Overstock.com (short cut: O.co) and RichRelevance® today unveiled the RecLab Prize on Overstock.com. The Prize provides a cash award totaling up to $1 million to the researcher or research team who can achieve a measurable lift over existing product recommendations in a wide variety of shopping contexts on Overstock.com. The RecLab Prize rewards the highest performing individual or team based on the results they are able to deliver within a defined judging period (up to $1 million for a 10% or greater lift). Complete details about eligibility for registering and competing for the Prize are available at http://overstockreclabprize.com/
RecLab Prize contestants gain immediate access to a high-quality and comprehensive synthetic dataset via RichRelevance’s open-source RecLab project, a highly scalable platform for research code. The RecLab approach enables researchers to develop their algorithms against synthetic data and then test against real data. Top performing algorithms will be exposed to real data and will run live within the RichRelevance cloud environment (as real product recommendations to Overstock.com’s customers). This groundbreaking approach enables researchers to solve a real-world problem with real-world constraints, while never exposing data to an outside system, thereby preserving data security and eliminating privacy concerns.
“We are excited to support the academic research community, bringing state-of-the-art analytics to our business through our partners at RichRelevance,” said Overstock.com CEO Patrick Byrne. “This is a phenomenal opportunity to benefit our customers, who will get early, exclusive access to the most advanced recommendations possible through the participation of top educational and research institutions worldwide.”
Online product recommendations are among the shopping tools most widely used by consumers who need to easily find relevant and enticing products from the millions available online. Overstock.com has worked with RichRelevance since 2009 to present shoppers with dynamic recommendations that grow smarter over time and accurately reflect more than 60 different ways that people shop on the site (by price, by brand, by category). Now Overstock.com is partnering with RichRelevance to open up this real-world business challenge to researchers. The RecLab Prize on Overstock.com breaks rank with previous prizes to present researchers with a complex, multi-dimensional problem facing retailers – not to simply predict how a consumer will rate a product but to effectively pinpoint the most appropriate product array to show shoppers at any point in the research and purchase process. The Prize demands that researchers craft approaches that quickly identify and adapt to contextual clues and maximize every available piece of data.
“The Netflix Prize did a great job of mobilizing the research community around a new and interesting problem. The RecLab Prize on Overstock.com takes the next step by offering researchers the chance to solve a multi-dimensional, real-world problem and see how their best algorithms perform when put in front of live shoppers,” said Darren Vengroff, RichRelevance Chief Scientist and RecLab creator. “The academic community has been clamoring for access to live real-world data and live user interaction to drive their research, and we are giving them more and better access than ever before using a unique approach that absolutely preserves the privacy of shoppers.”
A board of judges, including senior engineers at RichRelevance, Overstock.com, and well-known members of the machine learning community will determine the prize winners. In order to win the $1 million prize, a researcher or team must deliver at least a 10% lift over existing product recommendations on Overstock.com. If no one in the round hits this mark, then the judges will award a pro-rated prize to the team who achieves the highest lift as a percentage of the lift they achieve. For example, if the winning team achieves an 8% lift, it will receive $800,000.
In addition, should the winning team be affiliated with an educational institution, RichRelevance and Overstock.com will grant a separately funded Institution Prize valued at 25% of the winning prize to the educational institution. The RecLab Prize is also open globally to non-commercial teams.
About Overstock.com
Overstock.com, Inc. (short cut: O.CO) is a Savings Engine offering brand-name merchandise at discount prices. The company offers its customers an opportunity to shop for bargains conveniently, while offering its suppliers an alternative inventory distribution channel. Overstock.com, headquartered in Salt Lake City, is a publicly traded company listed on the NASDAQ Global Market System and can be found online at http://www.overstock.com and http://www.o.co. Overstock.com regularly posts information about the company and other related matters on its website under the heading “Investor Relations.” Overstock.com® is a registered trademark and O.co™ and Savings Engine™ are trademarks of Overstock.com, Inc. All other trademarks are the property of their respective owners.
About RichRelevance
RichRelevance powers personalized shopping experiences for the world’s largest and most innovative retail brands, including Wal-Mart, Sears, Overstock.com and others. Founded and led by the e-commerce expert who helped pioneer personalization at Amazon.com, RichRelevance helps retailers increase sales and effectively monetize site traffic by providing the most relevant products, content and offers to shoppers as they switch between web, store and mobile. RichRelevance has delivered more than $1 billion in attributable sales for its clients to date, and is accelerating these results with the introduction of a new form of personalized advertising called shopping media which allows brands to engage shoppers where it matters most – at the point of purchase on the largest retail sites in world. RichRelevance is headquartered in San Francisco, with offices in Seattle and London. For more information, please visit www.richrelevance.com.
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This press release contains certain forward-looking statements within the meaning of Section 27A of the Securities Act of 1933 and Section 21E of the Securities Exchange Act of 1934. Such forward-looking statements include, but are not limited to, statements regarding the amount of the prizes and the forecasted benefits of the contest results. Our Form 10-K for the year ended December 31, 2010, our subsequent quarterly reports on Form 10-Q, or any amendments thereto, and our other subsequent filings with the Securities and Exchange Commission identify important factors that could cause our actual results to differ materially from those contained in our projections, estimates or forward-looking statements.
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RichRelevance to take over operation and development of CNET’s Intelligent Cross-Sell™ technology, which incorporates deep product data with personalized recommendations in key vertical categories
San Francisco, CA – April 20, 2011 –– RichRelevance®, the leading provider of dynamic e-commerce personalization for the world’s largest retailers, and CNET Content Solutions, the world’s leading independent source of technology product information, have entered into a strategic partnership to offer CNET’s Intelligent Cross Sell™ as a RichRelevance solution. Under the terms of the agreement, RichRelevance will sell, support, and enhance Intelligent Cross Sell™, a product-recommendations solution specialized for the technology, consumer electronics, and office products categories. CNET will provide industry data, domain expertise, and sales support to RichRelevance for customers in these categories.
In addition, RichRelevance will license CNET’s DataSource™ for use with Intelligent Cross-Sell and the RichRelevance personalization suite. Through DataSource, RichRelevance will integrate the industry’s most comprehensive database of product attributes and compatibility data, covering more than five million tech, consumer-electronics, and office products worldwide into its personalized recommendations and Shopping Media offerings.
“RichRelevance is the established leader in retail personalization,” said Sean Murphy, VP and General Manager of CNET Content Solutions. “Their broad knowledge and reach is unsurpassed in the industry and, when combined with our vertical offering, will deliver powerful personalization for the largest retail sites on the Web. After careful consideration, it is clear that RichRelevance is the right strategic partner to continue to evolve our Intelligent Cross-Sell technology.”
RichRelevance currently serves more than 350 million product recommendations each day for a world-class client base that includes Wal-Mart, Sears and Office Depot. Moreover, with this partnership, RichRelevance will now serve seven of the top 10 online retail chains as ranked by Internet Retailer magazine based on revenue and volume.
RichRelevance CEO David Selinger explains: “CNET has established itself as a recommendations leader in verticals like technology, consumer electronics, and office products. These are critical categories for the largest sites on the web, so it’s natural for us to integrate that specialty into our offering, particularly as we continue to build out relationships with big box retailers in the electronics vertical. This partnership provides best-in-class and category-specific technology, product data, and intelligence that will be an important differentiator as the recommendations and personalization space evolves.”
Technical Fit
CNET’s data and technology provide a unique extra layer of intelligence for recommendations and personalization. Whereas RichRelevance’s flagship personalization offering RichRecs™ works mostly from anonymous profiles of people’s browsing and buying behavior, Intelligent Cross-Sell adds deep product profiles that include specs, compatibilities, and merchandising rules. This combination of insight about people’s behavior and products’ attributes is unique in the marketplace.
Wave of Consolidation Within Personalization Space
Industry watchers predict that a wave of consolidation will hit product recommendations in 2011. Writing in November 2010’s “What You Need to Know About Third-Party Recommendation Systems,” Forrester Vice President, Principal Analyst Sucharita Mulpuru stated: “While the venture capital community gets credit for keeping afloat the number of recommendation engine offers that currently exist, the industry is saturated and the next 24 months should see less outside capital, which will mean the coming of a long-awaited industry shakeout.”
About RichRelevance
RichRelevance powers personalized shopping experiences for the world’s largest and most innovative retail brands, including Wal-Mart, Sears, Overstock.com and others. Founded and led by the e-commerce expert who helped pioneer personalization at Amazon.com, RichRelevance helps retailers increase sales and effectively monetize site traffic by providing the most relevant products, content and offers to shoppers as they switch between web, store and mobile. RichRelevance has delivered more than $1 billion in attributable sales for its clients to date, and is accelerating these results with the introduction of a new form of personalized advertising called shopping media which allows brands to engage shoppers where it matters most – at the point of purchase on the largest retail sites in world. RichRelevance is located in San Francisco, with offices in Seattle and London. For more information, please visit www.richrelevance.com.
About CNET Content Solutions
CNET Content Solutions, (www.cnetcontentsolutions.com), a division of CBS Interactive, is the world’s leading independent source of product information. With detailed content on more than 5 million technology products in 15 languages, CNET Content Solutions helps thousands of resellers and retailers convert shoppers into buyers every day. From standardized content delivery to hosted services and custom solutions, CNET Content Solutions empowers businesses of all sizes to maximize the value of product information to improve their customer experience and bottom line. Customers include more than 2,100 e-commerce partners and websites, including CDW, Computacenter, Dabs.com, Dell, Hewlett-Packard, Insight, Microsoft, OfficeMax, PC World Business and Tech Data.
Darren Vengroff to detail RichRelevance’s new open-source project designed to spur innovation in retail personalization through the cloud
San Francisco, CA – April 19, 2011 –– RichRelevance®, the leading provider of dynamic e-commerce personalization for the world’s largest retailers, today announced that Chief Scientist Darren Vengroff has been selected to present on RecLab, an open-source project designed to spur retail innovation via the cloud. Vengroff’s session will detail how RecLab takes full advantage of the cloud and the implications for all kinds of research communities, focusing on the ways that the cloud can help researchers avoid the pitfalls that have historically made it difficult to work with real data and live traffic. The session takes place virtually on April 22 at 3 p.m. EDT, and will be available to conference attendees through the CloudSlam site, http://cloudslam.org/.
“Innovation in this space has been stifled to date, as researchers have lacked the environment to test their hypothesis and algorithms against actual consumers,” said Darren Vengroff, Chief Scientist at RichRelevance and head of RecLab. “Through RecLab, we’re giving them the opportunity to go after actual industry challenges, including one of the most basic problems in retail: will someone buy this or not? By leveraging the flexibility and reach of our secure cloud, we’re enabling them take their best shot at coding a solution, testing it, ensuring it works, and then allowing it to run in a real retail environment. This is a huge spur to innovation and one that underlines the power that the cloud offers. I am extremely excited to join CloudSlam and showcase this novel approach to innovation through the cloud.”
RecLab is an open-source project operating under the Apache 2 license. It defines all of the key Java interfaces and APIs for interacting with the RecLab environment. It also provides simple implementations of these APIs that allow developers to design, test, and debug their algorithms quickly and efficiently without having to take the time, effort, or expense of setting up a large cluster of their own.
The project supports a wide variety of contextual and behavioral data, both at model build time and at runtime. Code running in RecLab has access to both immediate click-by-click and a wide variety of past shopping behavior. In RecLab, researchers begin with synthetic data sets, derived from probabilistic models, not real shoppers. However, once code has been written, tested, and debugged it can be submitted to run live against a small segment of traffic on a live retail site through the RichRelevance cloud. More information on the environment, as well as a tutorial on building models within the environment, can be found here.
About CloudSlam
This hybrid conference, April 18-22, is a global event, covering latest trends and innovations in the world of cloud computing. Conference panels, workshops, and tutorials are selected to cover a range of the hottest topics in cloud computing. More information on the agenda and registration can be found here.
About RichRelevance
RichRelevance powers personalized shopping experiences for the world’s largest and most innovative retail brands, including Wal-Mart, Sears, Overstock.com and others. Founded and led by the e-commerce expert who helped pioneer personalization at Amazon.com, RichRelevance helps retailers increase sales and effectively monetize site traffic by providing the most relevant products, content and offers to shoppers as they switch between web, store and mobile. RichRelevance has delivered more than $1 billion in attributable sales for its clients to date, and is accelerating these results with the introduction of a new form of personalized advertising called shopping media which allows brands to engage shoppers where it matters most – at the point of purchase on the largest retail sites in world. RichRelevance is located in San Francisco, with offices in Seattle and London. For more information, please visit www.richrelevance.com.