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Archive for category Local Search

CUIL – No self respsect

Jul 29

Posted by fmapap in Local Search, Search | No Comments

I was reading a few articles about CUIL the “next great thing” in search engines.  As pointed out in this article by the Local SEO Guide, a lot of the searches you make with CUIL return some rather interesting results.

I think the most interesting is if you search for the term “CUIL” itself, try it here,  it doesn’t seem to know about itself.  At the time of this posting the results don’t show any results about the website.  It doesn’t seem to even know about itself.  However if you Google for CUIL, there it is CUIL.com.  I love irony.

I find all of this hype of CUIL interesting, especially for the local search market, because they claim that one of the benefits of CUIL is that it does not collect any private information, but to me that isn’t a positive thing (all the time) as it limits the ability of the site to personalize itself, the way, at theSUGGESTR.com do!

CUIL Google Local Search Search theSUGGESTR

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Your Personal Concierge

Jul 24

Posted by fmapap in Local Search, theSUGGESTR | No Comments

theSUGGESTR Integrates with OpenTable

theSUGGESTR.com has always focused on giving you personalized suggestions using our unique suggestion algorithm. Now we take things one step further with our partnership with OpenTable. Now after we suggest a great restaurant for you (and just for you), you can quickly and easily book a reservation using the “Make A Reservation” link that will connect you to Open Table.  theSUGGESTR.com is now like your own personal concierge, but unlike a real concierge theSUGGESTR.com takes your personal tastes into account when suggestion a place for dinner or drinks!

Take a peek at the Rainbow Room for an example of how we’ve integrated with OpenTable.

New to theSUGGESTR? Click here to learn more.

Local Search personalization reservations suggestions suggestr

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Beyond Search is Suggestion

Jul 21

Posted by fmapap in Collaborative Filtering, Local Search, theSUGGESTR | No Comments

Beyond Search is Suggestion

In our previous posts we discussed how the lack of personalization and lack of incentives for a review to be honest and fair, reduced the value of local search reviews by themselves. At theSUGGESTR.com we’ve decided to use a technique called collaborative filtering to provide a more personalized experience by being able to provide personalized suggestions not just search results. Our suggestion engine starts by calculating similarity scores between every pair of users and every pair of businesses. This allows us to ’score’ how similar the taste’s of two users are as well as score how similar two businesses are. These scores are then used in our proprietary algorithm to predict how well our users will like a given business. We believe, as do others, that the future of local search is more of a personalized experience and if you can personalize searches then you begin to enter the realm of suggestion.

Let’s look at a simple example of how this may work. Let’s say User A has rated 5 restaurants in New York, and User B has rated the same 5 restaurants with the SAME SCORE as User A. That would make User A and B have a high similarity score. Now let’s say User A from NY is going to San Francisco for the first time, but User B has been there, theSUGGESTR.com will be able to suggest restaurants to User A based on User B’s rating. Now imagine that process for every combination of users and businesses in our database. The data is combined using our unique algorithm so that we can accurately predict your ratings.

Collaborative Filtering in Action

We realize that our vision of local suggestion will be a marathon not a sprint. We do think we’ve made some great initial steps with features like our similarity meter which allows registered users to quickly see how similar their tastes are with others. Imagine being able to quickly identify which reviews come from people with similar tastes to you.

Similarity Meter

Also our predictive search allows us to predict how much you’ll enjoy a given business and even explain WHY we’re making the prediction.

Suggestions

We know their are lots of improvements still to be made and we should have some great new features available at theSUGGESTR.com shortly! In the meantime let us know what you think we should do to improve our site.

Local Search Recommendations suggestions theSUGGESTR

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Profile of a Local Search Reviewer

Jul 18

Posted by fmapap in Local Search, theSUGGESTR | 1 Comment

In our post yesterday we talked about the lack of personalization in local search and how that is one of the major weaknesses in many local search sites. Another flaw in many local search sites is that many of the reviews come from people with various motives, and little incentive to give reviews that are fair and honest. Think of it like this, what motivates someone to login to a site like Yelp and spend time writing reviews about a restaurant? Well one common reason is to complain about poor service. Another may be to help promote a friend’s business. There are also users who write reviews to boast their presence in the online community.  Many people have debated whether or not business reviews are helpful to the readers who read them. Other’s have discussed which sites and formats are more conducive to accurate and valuable reviews.

The fundamental problem with sites like Yelp and Insider Pages (those that are focuses on a social community) is that there is little incentive to be honest about average experiences(which by definition is what most experiences are).  To improve status and stature in the community users are almost encouraged to be extreme (either positive or negative) in their reviews.  At theSUGGESTR users are encouraged to be honest since their ratings are used in the calculations and predictions that give theSUGGESTR.com a more personal feel. We think encouraging users to honestly and accurately rate businesses by providing them incentive, in the form of more accurate suggestions,  is a major advantage for us.

In the next few days we’ll lay out some other reasons why we feel that we offer some features that make theSUGGESTR more useful for user’s looking to find great businesses that they’ll love.

Local Search personalization suggestions suggestr yelp

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What’s Wrong with Local Search Sites

Jul 16

Posted by fmapap in Collaborative Filtering, Local Search, theSUGGESTR | 4 Comments

What’s Wrong with Local Search?

The local search market has become saturated with sites that basically do the same thing. They allow users to comment on places, give them ratings, sometimes tag them and if your lucky provide additional data that is useful about a local business. While this does generate a ton of content the problem is the quality and accuracy of the content is questionable at best. Often a review will contain many contradicting opinions, and why shouldn’t it, everyone’s tastes and experiences are different. My opinion of a great steak house is probably different than that a vegetarian.

There are lots of reasons why a person may like or dislike a given business, especially restaurants. The majority of the current local search sites don’t provide any personalization when it comes to the searches and results performed by their users. Two users with opposite tastes will get the same results if they enter the same search. Even more troubling is when reviewing the 100’s of reviews posted for some of the most popular business the user is often left to decide if they want to read the one that says that the restaurant is the “best place ever” or the one that says that the “service was horrible.”

Most sites do not provide any way to easily distinguish which user’s reviews are most likely to be shared by you! We believe, as do others, that the future of local search is not really search at all but personalized suggestions.

We’ll lay out our vision for local suggestions in a couple of days.

Local Search Recommendations search market suggestions theSUGGESTR

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MyFriendSuggests.com is now theSUGGESTR.com

Apr 29

Posted by fmapap in Local Search, MyFriendSuggests, theSUGGESTR | No Comments

In order to better reflect our core value as a site MyFriendSuggests.com has renamed itself theSUGGESTR.com.  The primary reason for this was to better reflect that our service provides you suggestions.  While we will maintain our friend network functionality we wanted to emphasize that even without a friend network theSUGGESTR.com is able to provide you accurate suggestions based on  your personal tastes and preferences.

We plan on officially (re) launching theSUGGESTR.com soon with our new focus on local suggestions.

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Yahoo Local Map Improvements

Apr 24

Posted by fmapap in Local Search, MyFriendSuggests | No Comments

As Mashable and Screenwerk’s blog reported, Yahoo Local has improved its mapping functionality allowing user’s to move a big blue circle around the map and have the site automatically make changes to their search results. I admit the UI is pretty slick. However I think it is another example of how local search sites continue to miss the bigger issues with local search, the lack of personalization. These systems use ratings as the primary sort order but how do you know if you’ll agree with the rater. Most people who post comments on these sites do so because they had either a really bad or a really good experience (or more likely they know the owner, or ARE THE OWNER). We believe that by predicting a personal rating for each destination is what seperates MyFriendSuggests.com from other local search sites.

Getting back on topic about Yahoo’s new search, I’m the first to admit the look and feel of this feature is pretty slick. However it’s frustrating that when you change any of the search criteria it reruns the search and shrinks the map again (forcing you to click expand). Other than that this feature is a welcome addition to Yahoo’s local search.

P.S. MyFriendSuggests.com’s search functionality also allows you to focus the scope of your search by zooming in or out on the map and clicking “Refresh in Map Area”. It may not look as slick as Yahoo’s but it seems to work well for me.

Local Search Recommendation

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