Amadesa Unveils its Automated Product Recommendation Engine1
Amadesa Unveils its Automated Product Recommendation EngineCHICAGOIL-AMADESA
Amadesa (www.amadesa.com), a leader in end-to-end Web site optimization, today unveiled its intelligent Product Recommendation Engine, the fifth application released for Amadesa’s Web site Testing and Personalization Platform. It offers fast installation and implementation, clear reporting, and customizable branding, and, unlike other solutions on the market, requires no catalog integration or ongoing IT oversight.
Amadesa’s Product Recommendation Engine surpasses conventional recommendation solutions to more effectively up-sell and cross-sell first time visitors and recognized customers by moving beyond simple product-to-product and pre-defined associations, said Amadesa’s CEO and President David Efergan. Plus, with no catalog integration required and no ongoing IT maintenance to manage SKUs within our platform, we’ve fully automated a key element of a Web site success. It’s a new way of thinking about product recommendation, and it’s generating impressive results.
ToolBarn (www.toolbarn.com) saw the results first hand. The power tool and fastener distributor serves the construction industry and saw its average order value increase by 12 percent after tapping Amadesa’s Product Recommendation Engine to better personalize the experience it offered visitors.
Amadesa’s Product Recommendation Engine is part of a larger effort at ToolBarn to offer an increasingly personalized experience to shoppers visiting our site, said Chris Hughes, marketing manager for ToolBarn. We understand the value of providing helpful cross-sell and up-sell recommendations to site visitors, and partnering with Amadesa allowed us to do so in an effective, yet automated manner.
ToolBarn’s desire to personalize the experience and more effectively recommend up-sells and cross sells may be indicative of a larger trend. As product recommendation continues to gain steam, analyst firms tracking the online marketing industry predict e-commerce companies will strive to automate this process. In Which Personalization Tools Work for E-Commerce And Why,a December 27, 2007 report from Forrester Research (www.forrester.com), for example, Sucharita Mulpuru cites a Shop.org survey of nearly 200 online retailers executed by Forrester that found:
77 percent of retailers executed cross-sells by hand ,37 percent of retailers, however, said they will focus on automated product recommendations in 2008 .
Amadesa’s applications work in unison with one another on the Amadesa Web site Testing and Personalization Platform, offering a single user interface and increased efficiencies for sites leveraging several applications from the integrated suite. Other Amadesa on-site personalization applications currently available for use on the Platform include Shopping Cart & Forms Optimization, Segment Targeting, Multivariate Testing, and A/B Testing. Amadesa plans to release its Dynamic Personalization application for offer and promotional management, another integrated and algorithm-based application, early next year. Each Amadesa application integrates simply into existing site architectures since they require no catalog integration or ongoing IT oversight.
Amadesa delivers a Software-as-a-Service (SaaS) platform, the Web site Testing and Personalization Platform, which analyzes behaviors to guide user choices and outcomes, grow customer revenues and improve conversion rates. Amadesa Forms and Shopping Cart Optimization, A/B and Multivariate Testing, Product Recommendation, and Dynamic Personalization applications enhance users? online experiences to drive engagement and increase conversions. Companies turn to Amadesa to test, automate, refine and optimize content delivery and personalization processes, including customized shopping carts, forms, home pages, landing pages, product pages, category pages, and other online pages, advertisements and online content. Learn more at www.amadesa.com or follow Amadesa on Twitter at http://twitter.com/amadesa.