The so-called social Web has helped to change the very nature of the Internet by emphasising the role of our online experiences as new forms of content and service knowledge. User-generated content, from blogs and wikis to ratings and comments, all add an important layer of experiential knowledge to our online interactions. In this paper we describe an approach to improving mainstream Web search by harnessing the search experiences of groups of likeminded searchers. We focus on the HeyStaks system (www.heystaks.com) and look in particular at the experiential knowledge that drives its search recommendations. Specifically we describe how this knowledge can be noisy, and we describe and evaluate a recommendation technique for coping with this noise and discuss how it may be incorporated into HeyStaks as a useful feature. Experience is the name everyone gives to their mistakes. —Oscar Wilde