Lunch.com, the recommendations website that takes a deep look at your compatibility with others’ tastes, is launching a new feature called Trust Points, based on its proprietary Relevance Graph.  It takes the source of a recommendation into consideration, heightening the relevance behind it.  This builds on a core concept of Lunch’s website, but aims to improve recommendations in this manner by making it even easier for a user (or non-user) to benefit from the comments and reviews others have left on the site.

A great example from Melissa Cunningham, Vice President of Marketing at Lunch, would be a recipe recommendation from your mother.  Sure, it’s got sentimental value, but if mom’s a good cook, you’re even more likely to take that recommendation to heart.  The same goes for a film recommendation on Lunch’s site–if you consider the source of a review, you’re better able to determine if that recommendation is worth your time.

With Trust Points, while reading a review of the movie “Black Swan,” a reader can instantly see that they agree with the reviewer on films they loved, like “Inception” and “Fight Club,” but strongly disagreed on a film like “Avatar,” which they didn’t like at all.  This gives context for the reader to decide if that movie recommendation is personally relevant to him or her.

As you can see with the screen shots above, there’s a different experience for logged-in users and non-logged in users, though both aim to provide as much value as possible. The way Trust Points makes this a simplified effort on your part is by offering the bulk of the information you need to make your determination at-a-glance.  This transfers much of the “trust” factor in a user-generated content site back to the users themselves, but in a way that doesn’t require additional digging and research on your end.  By showing specific, related topics where members agree and disagree, as compared to the review’s author, anyone can now see how personally relevant each review is to them.  This solves the most pressing issue currently facing content online, answering the question: “Can I rely on this?”

Of course, Lunch’s recommendations work optimally when you’re logged into the site, and are active enough to have put your stamp on your profile.  The more interactive you are, the better recommendations you’ll receive.  Helping you choose the right content on Lunch’s site is a matter of engaging users as effortlessly as possible, and in the case of Trust Points, context is king.