I’m Charlie Hornberger, and I’m heading up the buzz.com project for AT&T Interactive. We’re opening our public beta of buzz.com by letting users outside of AT&T Interactive use buzz.com for the first time.
What is buzz.com? buzz.com is the newest local search experience developed by AT&T Interactive that helps users tap their existing social networks (starting with Facebook) for local recommendations. Talking about the best places to go or best businesses to work with is a conversation that is already happening online. Think of buzz.com as social bookmarking for your local world.
Check out this video for a taste of the user experience:
Our internal group of alpha testers gave us a lot of valuable feedback, and although we are still in the process of addressing feedback by tweaking the user interface and adding features, we think it is time for input from a much wider base of users. That’s why we’re opening the site – by invitation only – to external users now. We’re hoping the feedback will reinforce the functions before we begin promoting buzz.com more widely.
How do I get an invite?
If you’re interested in joining, sign up on buzz.com to receive an invite as we expand access. We hope to share some invites with our Beta Labs readers, too, so stay tuned.
As we get more feedback from users and continue to build out the experience, we’ll keep you posted here on our latest updates or follow us on Twitter and Facebook .
When writing the retrieval & ranking code that’s at the heart of any search engine — code that answers the question what results should be returned for this search, and what order should they be in? — engineers have a plethora of algorithms to choose from. And given the critical importance of getting relevance right, one might reasonably wonder whether, by now, the search industry has settled on a standard automated measurement of relevancy. (That would certainly help us choose the right search algorithms!) This is not the case. While some work has been done to analyze server logs to report proxy measures such as click-through rates and page dwell time, automated tools have yet to replace human raters. This is largely because relevancy is highly subjective.
Many local search engine firms have specialized in-house teams whose job it is to judge the relevance of the results produced by their engine in response to real-world queries from users. But this raises some questions: Are the scores from a group of ‘professional judges’ applicable to the general population? Without local knowledge, can the testers determine whether an ambiguously named business is properly categorized or whether the most popular restaurant in a neighborhood is ranking appropriately? Are the testers aware of colloquial differences in names for businesses or products? Do the testers understand local preferences around how far people are willing to travel for a particular type of business?
One way to address such concerns is simply by asking for direct feedback from real users. So today, yp.com is launching a tool to gather relevancy feedback on individual search results. Next to any business listing show on a search results page on yp.com, you’ll notice a pair of Yes/No buttons under the words “Listing relevant?” We hope you’ll take the time to click a few of them — especially when we return the wrong stuff, but also on those occasions when we manage to get it right, too!
Today we’re revealing a sneak peak at another twist to our search relevance algorithm — one that strikes a balance between our traditional sponsored listings approach and pure distance-based sorting, both of which you can use on YELLOWPAGES.COM today.
The new approach is simple — we take the listings that would normally be returned by a search for a business category on YELLOWPAGES.COM, and group them into five distance bands, or rings, based on their proximity to the geographic center of the search. (We already do something similar for searches for business names; we’re experimenting with this new approach only for business/product categories.)
So if you search for “lighting fixtures” in Fremont, CA, you first see the businesses that are located within 1 mile of the center of Fremont, then the businesses within 3 miles, then 5 miles, then 10, and finally within 20 miles.
By treating all businesses within a given band as equally close to the target location, we eliminate the effect of distance within the band. So a listing that’s 4.9 miles away might appear higher in the results than one that’s 3.1 miles away, but neither of them would appear before one that’s 2.5 miles away. We can think of this as a technique for reducing the impact of small differences in distance, where the definition of “small” changes with each band. (As the distance from the center-point of the search increases, the sensitivity to differences in distance decreases. Intuitively, it’s easy to understand that the difference between 0.4 miles and 1.4 miles is much greater than the difference between 10.4 and 11.4 miles).
This approach isn’t perfect. For some business categories — particularly service-oriented ones — geographic proximity isn’t much of an issue, so it’s inappropriate to put *any* significant weight on distance when ordering the results. In others, we believe this “compromise” sorting method may do a good job of serving the needs of both users and advertisers. As always, please use the comments section below to let is know whether you think it works, and why or why not!
As we mentioned in Where You At?, it is an unfortunate fact of life that not all searches arrive at the yellowpages.com servers neatly divided into two parts: the what part (“pizza” or “plumbers”) and the where part (“albuquerque” or “anchorage”).
These untidy queries arrive as an undifferentiated jumble of text—e.g. “pizza los angeles ca”—and while it’s obvious to a human what that means, it’s not so perfectly transparent to a computer. So it’s up to our search engineers to write programs that figure out which parts are the what of the user’s query, and which parts are the where.
We have recently done a bit of work on this front, and would like to share an initial implementation; it’s not perfect, but we hope it handles many common cases. (It works by comparing the sub sequences of words in the query string against known addresses in our database; we use the matches in order to distinguish the geographic terms in the query from the rest. Call it separating the where from the chaff …)
If you’d like to try it out, you can use the field below:
As usual, please use the comments to let us know if you find cases where it ought to work, but doesn’t.
It may not come as a great surprise to learn that here at yellowpages.com, we’re constantly looking for new ways to extend our ability to connect consumers with businesses.
In the past, we have inked lots of deals with big-name sites in order to “further our reach” on the web —basically, to make sure that if you’re a business who does business with us, you appear on more top-tier web sites than just yellowpages.com.
But we’re getting ready to try a new approach. In the near future we hope to launch a new self-service initiative that allows individual publishers, no matter how large or small, to embed yellowpages.com business search functionality into their sites.
The best part is that it requires a truly miniscule investment of effort. (And no contracts! Unless you count the EULA )
All you have to do is pick the size, color and (optionally) default search region for your search widget, and our handy-dandy tool will generate a snippet of HTML code that you can easily insert into your web pages.
When writing the retrieval & ranking code that’s at the heart of any search engine — code that answers the question what resu
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All you have to do is pick the size, color and (optionally) default search region for your search widget, and our handy-dandy tool will generate a snippet of HTML code that you can easily insert into your web pages.