Picture Dummy The efficiency of connecting advertisers and  customers is almost wholly determined by  how accurately the advertising reflects the  needs and expectations of the customer.  Nothing within the richness of modern  publication media has changed that. What  has changed is the ability to gather more  and more data about the market targets of  advertisers, so that one can improve the  efficiency of advertising value. In short,  increased advertising efficiency is simply  correlated with how precisely customers are  identified. The net-linx Presentation  Optimization Program helps you to  automatically create new sales proposals to  be used in nxPowerPac and nxWebPac. HOME > PRODUCTS > nxPOP nxPOP PROMOTION net-linx Europe GmbH Germany 01309 Dresden Käthe-Kollwitz-Ufer 76-79 Tel: +49 (351) 31875-0 Fax: +49 (351) 31875-550 e-mail: info@net-linx.com QUICK CONTACT Presentation Optimization Program Home | About us | Careers | Partners | Download | Contact Benefits: • Increase cross-sell and up-sell revenues by offering your customer personalized and tailored  recommendations that they’re likely to accept • Improve future sales  • Decrease training time   • Increase sales efficiency   • Better customer satisfaction and less customer complaints • Gain insight into all your sales activities including pipeline and forecasted revenue for better sales  planning  Features: • Guide agents to the “next best action” by providing them with customer-specific  recommendations, as well as customer history and acceptance likelihood so they can work out  which proposal to take to the customer • Dynamic recommendation generation based on in-session data, in addition to “staged”  recommendations  • Create both customer-specific and generic recommendations  • Save the sales interaction information as part of the respective customer’s record and incorporate  it into refining the next set of recommendations  Current advertising publication media are richer than ever before, and include a variety of print (e.g., Yellow Pages, newspapers, magazines), broadcast media (e.g., television, radio), Internet (e.g., advertising aggregators like search engines, targeted push advertising), and wireless/PDA (e.g., mobile phones, PDAs). But at an appropriate level of abstraction, the process supporting the business model of advertising revenue is the same: connect customers to advertisers.    How is advertising sold? The manner by which advertising is captured and sold has also considerably broadened. For example, the  introduction of so-called self-serve advertising on the World Wide Web, for example, Google's Adwords, has  developed into a highly profitable business that has permanently changed the face of retail commerce.  The new suite of net-linx hardware and software support embodied in the nxPowerPac / nxWebPac systems  is designed to exploit traditional advertising selling but couple it to modern rich media advertising, in order to  improve an advertiser's return on investment. This is done by providing sophisticated hardware support for  sales interaction with advertising customers, and by an underlying software architecture that uses the most  modern methods of modern computer science, including Artificial Intelligence and Machine Learning.   A fundamental advantage of modern digital advertising publishing is that one can gather more and more data  about how advertising and consumers interact, and use that data to improve advertising. This ability has  evolved very quickly since the days of Yellow Page call back numbers for counting printed page ad hits, and is  the basis of the modern methods for assessing user profiles for things like Amazon book suggestions, as well  as the growing number of targeting and re-targeting of advertising content.     nxPOP Technical Background The technical basis of the nxPOP sales system component uses a machine learning software architecture to  identify and capture advertising histories, construct a classification based on that history, and then make  predictions about how possible changes in new advertising publication will improve the efficiency of that  advertising.  As an example, one could use a historical database of previously sold Yellow Page advertisements published  on the Internet, gather statistics on their use, compare them with similar advertising of competitors (e.g., the  other advertisers in the same classification), and then make predictions about what kind of new advertising  portfolio would best improve that advertiser's return on advertising investment.  The development of nxPOP was done in collaboration with the Alberta Ingenuity Centre for Machine Learning.  The machine learning architecture has access to historical advertising sales and uses sampling to develop  predictive models, and then test the accuracy of those predictions against existing data. In this way, for  example, the number of customer hits on an online advertisement can be predicted to be improved by an  alternative placement (e.g., in another classification category), and that expected improvement can be  calibrated against existing historical data.    In the case of using nxPOP to create upsell recommendations for advertisers, the performance on historical  data can achieve over 90% accuracy against existing historical data. Thus, nxPOP is able to provide  advertising efficiency in the majority of new advertising placements.  • Benefits • How is advertising sold? • nxPOP Technical Background • Features • Download Legal Notice | Copyright © 2011 net-linx - All Rights Reserved