![]() empower comparison using distance from you.empower comparison using both average review and number of reviews.The popularity that is hinted at by a high volume of reviewers inspires confidence. Including the number of reviews is also important - 600 reviews for a 3.5 star restaurant will almost certainly always beat out 25 reviews for a 4 star restaurant. comparing how far away your chosen destination is from you is really what matters, isn't it?.losing the map location allows you to space out overlapping spots.it allows you to devote the saved axis to another data type.I believe it is worth trading the map location (a 2-axis plot that overlaps data points) for proximity (a single-axis plot) because: I like seeing restaurant locations on a map - but it should not be the starting point for your Yelp search (are you picking out a foody neighborhood or the perfect restaurant?). The LIST view displays a load of information for each restaurant - but makes it impossible to compare this information across restaurants: both because you can only look at five at once and further because there is no opportunity for quick pattern recognition comparison of multiple traits amongst the restaurants.ĭo we really care about a lousy picture and detailed address when considering a venue at this level? Also, the map has a north-south bias because of the dimensions of the screen: number 15 on the example above (the Eno River Eatery) is 4.7 miles north of the searcher, and would certainly not appear on the map if it was 4.7 miles to the east. Displaying so few pieces of data, it still manages to hide some hits behind others because restaurants are often clustered into the same blocks. The MAP view only displays location (and by a quick extension, proximity to me) and the Yelp ranking which lumps everything else into one number, which I don't completely trust. Here is a short list of items that are of interest to me when choosing a restaurant, all of which get baked into Yelp's algorithm: With this black box algorithm in mind we see details of the top five restaurants on the first screen - and must scan through several screens worth of similar details to see information for just the top 20 restaurants. based on a number of different factors including review text, ratings, and number of reviews. In addition to ratings and number of reviews it most certainly also includes proximity to the searcher and probably also weighs for more recent reviews (I care more about a review written last week than one written three years ago). How does the Yelp ranking work? Who gets to be number one? Yelp answers this question on its FAQ page: Yelp's search results are based on an algorithm. While the number 1 spot stands out, both 2 and 4 are hidden under other restaurants! This unsatisfying cluttered map prompts two actions: zooming into clusters for a closer look and tapping on individual spots for more information, or toggling to the LIST view (on the right) to see more details. However, half of the hits are obscured by overlapping brunch spots. ![]() 20 hits are represented by location, tagged with their rank on Yelp's recommendation list (more on that soon). Both of these methods have fundamental problems, which we can investigate by a simple search for brunch spots near my favorite brunch city: Durham, NC:īy default. Yelp displays search results in two ways, on a map and in a list. What was missing? Yelp certainly commands a dazzling mine of data - but sometimes I feel it isn't being leveraged properly. I found that using the Yelp app on my iPhone was terrific in making some of the finer decisions (highlighting often remarked menu items & displaying pictures of dishes) but rather clumsy when making the most important decision: where should we go to eat? Yelp's restaurant rankings never struck the excitement that their menu highlights did, and certainly did not approach the confidence that comes from a local friend's recommendation. After spending a week eating my way through the Pacific Northwest I became intimately familiar with Yelp (as if I wasn’t already) as it guided me through a gastronomic amusement park.
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