A/B testing : the most powerful way to turn clicks into customers /

• Κύριος συγγραφέας: Siroker, Dan
• Άλλοι συγγραφείς: Koomen, Pete, 1982-
• Μορφή: Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Hoboken : Wiley, 2013.
• Θέματα: Organizational effectiveness.; Multimedia systems > Social aspects.; Application software > Testing.; BUSINESS & ECONOMICS > Industrial Management.; BUSINESS & ECONOMICS > Management.; BUSINESS & ECONOMICS > Management Science.; BUSINESS & ECONOMICS > Organizational Behavior.; Betriebswirtschaft.; Research.; Electronic books.

 BA guide to delivering a better user experience through A/B testing/b iA/B Testing/i outlines a simple way to test several different versions of a web page with live traffic, and then measure the effect each version has on visitors. Using A/B testing you can determine the most effective way to increase conversion rate'the rate at which visitors convert into customers. The average conversion rate across the web is only 2%. That means 98% of visitors to most websites don't end up converting. Using A/B testing, companies can improve the effectiveness of their marketing and user experience and in doing so can sometimes double or triple their conversion rates. In the past, marketing teams were dependent on IT and engineering to implement A/B tests, and that proved to be a costly bottleneck. Today, the market for A/B testing is growing very fast, in no small part due to this transition from IT to marketing. ulliOffers best practices and lessons learned from over 100,000 experiments run by over 2,000 Optimizely customers/liliDetails a roadmap for how to use A/B testing to personalize your customer's web experience and a practical guide to start A/B testing today/liliAuthors Dan Siroker and Pete Koomen are cofounders of Optimizely.com, an user-friendly testing system that more than 2,000 organizations use /li/ul Marketers and web professionals will become obsolete if they don't embrace a data-driven approach to decision making. This book shows you how, no matter your technical expertise. 

 How A/B testing helped win the White House -- twice -- What to test -- Refine, explore, and refine -- Less is more : reduce choices -- Conclusion -- Acknowledgements.