However, nearly everything else about the new Android application is the same as its mobile counterpart, including its search verticals of "web," "images," and "buzz" which sit above Taptu's search box on the app's main screen.

The "buzz" section contains real-time results pulled from sites like Twitter and Digg as well as from other social sharing websites, blogs, and data pulled from select panel of internet users who have downloaded the OneRiot toolbar and are anonymously sharing their web-browsing data with the company. This aggregate information is actually the most prominent source of real-time data for OneRiot's search service. As of September of this year, OneRiot claimed to have 3 million active toolbar users out of the 20 million or so who have downloaded the toolbar to date. Meanwhile, they're indexing around 20,000 links from Digg and 5 million from Twitter.

It's this data which powers Taptu's "buzz" section where you can find breaking news and other currently "hot topics" being discussed on the web. And unlike Twitter's trending topics, for instance, OneRiot doesn't link to raw tweets but to the actual news stories and blog posts that are sharing the information.

The main Taptu homepage also links to these trending items by way of a tag cloud whose colorful blue bubbles take you directly to the buzz section when tapped.

If you're interested in trying the new Android application, you can download a free copy from the Android Market on your mobile phone. If you don't own an Android device (or iPhone), you can still use Taptu via its mobile website available at www.taptu.com.

Microsoft's Live Labs has been the source of a few interesting projects: a 3D photo-stitcher called PhotoSynth, a bookmarking service called Thumbtack (which was shuttered just this month). Typically, the UIs have been slick, but user adoption has lagged.

In short, datasets are organized as collections. Results can be as granular or as big-picture as the user desires, and correlations and patterns are easy to see and examine through powerful but simple visualizations. Imagine browsing through thumbnails representing Kiva loans, then sorting the loans by the different types of businesses they helped established. Or, on a nerdier note, think about riffling through decks of Magic: The Gathering cards, zooming in for larger-than-life detail of the card's artwork and then zooming out to see how each was related or linked to others in the set.

This probably reminds you - as it did us - a lot of Wikipedia. But imagine Wikipedia as an infinitely scannable, shuffleable, expandable, retractable, linked, and yet still detachable deck of digital cards; and then you have an inkling of how Pivot looks and feels.

Collections can be created by anyone, including third-party developers. Types of collections include simple, linked, and dynamic, which are each progressively more difficult to create. Developers are also encouraged to create collections from existing online datasets, such as the Internet Archive or data.gov.

It's very exciting, indeed; and it's available for Windows users only at the moment. Mac users, we're sorry. Why don't you go write some complaint letters on your beautifully designed, virus-immune machines? We'd love to rub it in some more by posting a few screenshots with gloating captions, but we're too busy trying to get this machine to stop being so Windows-y and just run the software

Right now, the service is invitation-only. We encourage you to Google around for your invite codes or check in here later to see if the kind folks at Live Labs have passed along any to us.

I've written previously about how social search won't replace traditional search, how social relevancy rank can be used to deliver good results, and why the concept of social search is a return to a familiar state rather than something to fear. Today, I'll get more specific about the three flavors of social search that will improve user search experiences.

Collective Social Search

"Collective social search" is similar in concept to the wisdom of crowds, in that search is augmented by trends shared on a network (a la Twitter Trends) or results ranked against the real-time buzz of a group. Why might this be useful? Well, in some instances, we can't immediately find the information we're looking for; and pooled, aggregated data from the collective may point us to new avenues that expand our discovery process.

As of yet, no major search systems are doing this very well - and we don't know what type of interface would be optimal for sharing this information. The Cloudlet plugin inserts tag clouds (based on keywords) into search results; but tag clouds are known to be more of a distraction than a utility. BingTweets has been touted as such a resource, but it really only offers Twitter and Bing results on two separate pages. OneRiot shows only collective data from the real-time stream, although it may be integrated with Yahoo! results soon. And we are still waiting to see how Google and Bing integrate the Twitter firehose into their traditional search results - as opposed to merely including them as additional document-like resources.

Equally important will be understanding when collective social data should be shared with users: while performing the search or after? And for which types of searches?

My research on search strategies begins to address this question. Collective guidance may be useful when users are exploring a search space, possibly because the search domain is not familiar to them (i.e. they lack knowledge of how to drill down to an answer), or because they are passively exploring a problem. I find myself doing this all the time when I prepare recipes to cook. I want to browse recipes from many different sources before I decide what my own recipe will consist of. I don't have a specific recipe in mind (it's not an urgent, active request), and therefore I don't necessarily know when I've found what I'm looking for.

That said, it's hard to determine from keyword strings how active or passive a user's search is; i.e. it may be quite difficult to determine the type of search they're performing or how far along they are in their search process ("exploring" or "narrowing"?). Furthermore, the utility of collective social data for mainstream consumers will be limited, mainly because it doesn't come from trusted sources, unlike "friend-filtered social search" (see next section).

Friend-Filtered Social Search

Friend-filtered social search is approximately what Google is doing with its social search experiment: providing social data that your peers, friends of friends and wider "social circle" have shared. This data could appear alongside traditional search results (as with Google) or be exclusive results from within your peer network (as with TuneIn).

This is useful if your friends have shared relevant links, blog posts or tweets about a topic that you're searching for. If you were gathering ideas about, say, "the future of the desktop," you would see thought pieces, write-ups and links to projects from the main search algorithm, as well as stuff your friends are saying about applications they've encountered recently. If you trust your friends, they may serve as reliable filters, pointing you to relevant information.

The three major limitations of this approach are:

1. Your friends may have no archived social content that's relevant (or available) to your query. Searching within your Facebook network quickly demonstrates this problem. For this reason, augmenting traditional algorithms with friend-filtered social data may be better, rather than relying exclusively on data from one person's small exclusive network.
2. Current implementations are limited to keyword matching; whereas, searches that retrieve related posts based on topic, theme or timeframe might expose a wider set of results and combat the niche-social-network problem. This approach would be computationally harder than keywords alone, and exposing enough of the appropriate context remains a problem (see next item).
3. Understanding the context in which a post or link was shared is important. Without this, keyword- and even topic-matching might not convey to the user the relevance of a search result. Google provides limited context at the moment (showing only how you know a user, the source of the post and a short snippet). More testing is needed to learn how much and what kind of context is appropriate for social search content.

Similarly there is the issue of when friend-filtered social search would be relevant during a search. My instinct is that it will be useful throughout a search and for many types of searches (it is, after all, just another type of search result). This is critically different from collective social search and collaborative search.

Collaborative Search (a.k.a. Question-Answering)

"Collaborative search" is when two or more users work together to find the answer to a problem. This could look like IM-based question-answering (a la Aardvark ), Yahoo! Answers (which is relatively passive and asynchronous) or over-the-shoulder two-person search. In all of these cases, people speak to each other using natural language, which is incredibly useful for open-ended queries (e.g. "What is 'design thinking'?") or queries about unfamiliar domains (e.g. law, health, business, depending on your background). Such conversations, even not real-time ones, can assist people who don't know the right keywords to use (what's known as the "vocabulary problem").

My research has looked at the benefits of question-answering and at people's processes and preferences during search. Many users report that they want to attempt to search on their own first, or don't wish to interrupt their colleagues before they have given it a shot independently. This suggests that early social support should be passive (as with presenting collective or friend-filtered social data).

But later in the process, if the searcher gets stuck on a problem, they often turn to a colleague for help. If systems had a way of identifying difficult queries or search-process inefficiencies, they could offer more explicit social support to searchers. Perhaps the system could identify a domain-specific expert from the user's extended social circle. Information that this person has shared could be presented to the user, or this person could be suggested as a resource to chat with or email (depending on availability and preferences).

It should be clear by now that these three flavors of social search are complementary. Each has its pros and cons and is appropriate for different kinds of searches and during different stages of the search process. A powerful "social search engine" would be "smart" by making use of all three, while also exploiting the value of traditional algorithms.

Photos by: Who Wants to Be?, Claudia Lim and brewbooks.

Guest author: Brynn Evans is a PhD student in Cognitive Science at UC San Diego who uses digital anthropology to study and better understand social search.

Using the OneRiot API, Taptu's new homepage presents a mobile-friendly search engine interface complete with search box and verticals for searching just the web, images, and now, "buzz." Previously, the site included verticals for music and video searches too, but those have seemingly been done away with in an effort to simplify the interface.

The new "buzz" section is where you can find the real-time results. Here you'll find content pulled from sites like Twitter, Digg, other social sharing sites and the company's own panel of users who have downloaded the OneRiot toolbar and are sharing their web-browsing data in anonymous aggregate.

While Twitter is clearly a source of breaking news, we've always found it a bit odd that OneRiot includes Digg in its "real-time" search engine. We've never thought of Digg as anything near real-time - in fact, it pales in comparison to Twitter when it comes to the speed with which information spreads. With the immediacy possible on today's web, sites like Digg seem much slower - painfully slow at times - often taking hours on end to feature the news that had already been buzzing on Twitter for half a day.

That said, Digg and other social news sharing sites can sometimes unearth news that had been overlooked by major media outlets, especially when focused on a particular niche like technology. For example, just think of how many stories you read on someone's personal blog or Reddit and never saw anywhere else on the web. By tracking niche websites like these as well as Facebook, MySpace, Bebo, social bookmarking sites like Delicious and StumbleUpon, microblogs and URL-shortening services, Oneriot can discover links that may have otherwise gone unnoticed.

Taptu's new mobile search engine interface currently works on major touch-enabled devices including the iPhone, iPod touch, G1, Nokia N97 and 5800, and the BlackBerry Storm 1. The Taptu iPhone application will also be updated soon to include the additional functionality. You can test the new service yourself starting at 9 AM EST by pointing your mobile browser to www.taptu.com.

This is a strange story, but no one said the path to the future wouldn't itself be strange. So consider suspending your disbelief so you can see what Leapfish has to offer.

Leapfish searches for user queries across 25 different services, from Google and Yahoo to Yelp, Digg and some Real Estate sites. The service determines which sources are providing the most relevant results and constructs a search results page accordingly. If users love Leapfish enough to marry it they can turn on as many as 35 different widgets to interact with things like their Facebook and Twitter accounts on the Leapfish home page.

The design of the site and results pages are quite nice and the fundamental idea is a good one. But how could Leapfish already be set to bank $10 million in revenue this year?

The Pleasanton, California company says it has 100 employees; 50 are listed on LinkedIn and almost every one of them are in sales.

The sales pitch is this: Leapfish is small today, but the keyword prices that companies (like this lady) are paying will be a bargain if Leapfish can really grow. It's an investment, and as such it's a very affordable one. Some companies have already resold the keywords they bought from Leapfish for a profit, the company says.

One part of what's being invested in is, no doubt, a vision of the future. Check out this absolutely cathartic video the company made about the real-time web.

Unfortunately, in our tests Leapfish doesn't work very well. Search results are often off-topic, there are software bugs in some of the most basic parts of the site on the day of its grand unveiling and the compelling vision isn't that exciting in reality. Check out our 5 minute tour of the site to see what $10 million in ads have been bought against over the last year.

The Bing team also added a few new features to the generic mobile search. Users can now search for NFL teams and players and get real-time updates about games, stats and scores while a game is on. This feature is only available in the U.S.

In addition, Bing has implemented a flight search feature. You can now type in the airline code and flight number and Bing will return the latest gate information and departure and arrival times.

But Will Anybody Use It?

The new mobile interface for the iPhone and similar devices looks a lot better than the earlier version and is also more usable. Given that users can only switch between Google and Yahoo as their default search providers on the iPhone, however, it's questionable how many iPhone users will actually use Bing's mobile search.

Real-Time Web Crawling in the Future?

Although only briefly mentioned in the post, Google hinted that they may begin looking into other mechanisms such as PubSubHubbub, an open protocol that provides near-instant notifications of change updates. No further details were provided beyond the one sentence, but the announcement clearly shows that Google has seen the writing on the wall and knows that the real-time web is the future. This is one trend the company isn't planning to ignore.

The real-time web, heavily influenced by the speed of Twitter and other other rapid-fire social networking updates, has created a desire among internet users for faster access to information. This desire has, in turn, led to the creation of new real-time protocols such as the above mentioned PubSubHubbub and its counterpart RSSCloud. If Google began to use these technologies for scanning the web, their search results wouldn't just be updated faster - they would be updated in real-time. That means information would become available in the search results listings as soon as it was published to the web.

That, of course, would lead to a whole new series of challenges for the search engine - most notably, how to rank the real-time results? Given that Google's search algorithm has been built on top of the concept of PageRank, a way to determine the relevance of a website by what other sites link to it, ranking search results that are so fresh that there is an absence of links could prove a difficult feat. However, Google is already doing this to some extent now. Over time, the PageRank algorithm has evolved and can now reward sites with fresher, more fitting content and rank them higher than sites with more links on some occasions. And if anyone can figure out the proper algorithm for mixing in real-time content and ranking it appropriately along with static pages, it's got to be Google. In fact, we'll probably soon see exactly how they plan on addressing this issue, when they incorporate Twitter search results into their index, as announced last week.

...But Until Then, Google Delivering Faster, Fresher Results Instead

Although the PubSubHubbub mention may have been the most exiting part of the announcement, real-time search results aren't here just yet. In the meantime, we have to just be content with sped up results instead. The post advises website owners who are blocking Google's search bot software known as Googlebot from crawling their RSS/Atom feeds to unblock it via their robots.txt file. If unsure, webmasters can test their feed URLs with the robots.txt tester in Google Webmaster Tools, as the post recommends.

Yahoo Search continues its steady decline. Yahoo Search lost another 1% market share last month and has now lost a total of 5% since September 2008 when it still owned 18.8% of the market according to Compete. The total search volume on Yahoo was down 8% and Yahoo served 100 million less queries in September than August.

Google, Ask and AOL Hold Steady

Google's market share grew slightly from 72.3% to 72.6%, while Ask and AOL remained stable. Based on this data, Bing seems to be eating into Yahoo's market share, but isn't growing at Google's expense.

Searches Per Day

Compete's Marko Madjarac points out that Bing's numbers are even more impressive when we take into account that Bing's users tend to perform fewer searches on the service (5 searches per user per day) than Google's users (5.6 searches). Bing apparently lives up to its promise to get users to relevant answers faster than any other search engine. Yahoo users performed an average of 7.8 searches per day.

Both companies are hoping you'll come to their sites to search for what you're looking for, what people are saying about that topic and what your friends think. Microsoft is very much in the game, too. Here are some things to consider in this search war. It's a new fight - now including the real-time, social web!

The following is our attempt to piece all of this together, but the war rooms of each of these companies are no doubt buzzing trying to put together and understand the same details and more.

Google's new Social Search will allow users to opt-in to having search results from content created by their friends on social networks around the web included in Google search results. Those friend connections could come from any number of sites that you and your friends have listed in your Google Profiles - but it won't include Facebook. That means it won't include very much, unless Twitter and Google Profiles become a lot more integrated.

Microsoft announced today that Facebook status messages and other content from Facebook users with public profiles will soon appear in Bing search results. That's a huge change for Facebook. Bing also announced Twitter search integration, which is live now.

Google announced a deal with Twitter today as well. So Bing has Facebook and Twitter. Facebook has Bing-powered web search. Google just has Twitter, no Facebook search.

Right now Twitter search is probably much bigger than Facebook (unless you're Facebook serving logged-in users), because only a tiny portion of the much larger number of Facebook users have opted-in to making their Facebook activity public. But Facebook has an explicit agenda to change that. One reason for that is that more public Facebook activity makes deals like the one it made with Bing today much more valuable.

More now than ever, Google needs Twitter data to combat Facebook's social dominance - Facebook is five to ten times as big as Twitter today.

Microsoft would rather you did all your searching from Bing but it does own a meaningful portion of Facebook. You can bet it wishes it owned more.

No one is set to be the clear winner here, but with far more social activity and a multi-layered partnership with the first qualified web-search challenger to Google in years (Bing) Facebook may in fact have the strongest hand.

It's going to be a wild ride and big moves are being made right now.

Facebook is opening up to a search engine - that's very big news. Only content from accounts marked public will be indexed by Bing, but it's a sea change none the less. Facebook has an explicit, acknowledged agenda to make more people comfortable sharing more information publicly - once they do, that information will be searchable on Bing. This 'aint your big sister's Facebook anymore.

You don't want to be public with your Facebooking? Facebook will respect that, but the company does hope you'll change your mind. Seeing some peoples' Facebook status messages show up in Bing search is likely to freak out people who aren't familiar with public profiles and have a strong interest in their own data remaining private.

Will the company make a similar deal with Google? Probably not. Twitter may have gone both ways, but Facebook's long-term ambition to challenge Google and its Microsoft backing will probably mean that the world's leading search engine will never be allowed to index activity on the world's leading social network. The public parts of profiles, yes, but activity? No.

Say hello to the new Facebook, now a partial player in one public part of the rest of the web.

Twitter can bring a new level of up-to-the-minute information to web search, but can Bing add value to Twitter search? We asked three User Experience experts for their opinions about what Bing would need to do in order to succeed in this integration from a UX perspective. They agreed that there was exciting potential here but that the implementation was rudimentary.

Bing now has real-time access to the full fire hose of Twitter data, that's a really valuable flow of data. It's clear that Twitter can provide some real opportunity for Bing, but what can Bing do for Twitter? Would Twitter users be better off just using Twitter search?

We asked three User Experience professionals for their opinions. They provided feedback as the announcement rolled out, through the Aardvark IM interface. (Which was awesome.)

Ben Thompson, Massachusetts-based financial services UX designer.

"The ability to integrate facebook and twitter streams and data is the next evolutionary step for search. To me it isn't a game changer like Google was but evolutionary in that real time was always desired. It's the next step."

Thompson is excited about potential use cases.

"The integration of the real time stream can bring pertinent information on live events. Say we are watching the next Presidential debate. Now people can search and get real streams from people and their thoughts about it instead of just listening to the pundits. The celebrity angle will allow people to get closer to the direct information from that celebrity instead of just news stories about them. Plus it will allow up-to-the-minute information."

"I believe Bing can add value to Twitter search by making people more aware of the power of Twitter. Many people think Twitter is just a silly place where people write about themselves in 140 characters - not understanding the true power of Twitter is in massive amounts of real time data. So Bing displaying twitter results will help bring that concept to the masses."

Thomas Vander Wal, Principal at InfoCloud Solutions.

"I would give Bing/Twitter a 70% good, but not too different from other things. I am wondering how they can or will disambiguate the Paris Hilton type problem (hotel & celebrity). I saw the photos of Carly Fiorina from W2S yesterday and dropped 'carly' into bing/twitter, but it did not disambiguate the 4 various 'carly's being tweeted about."

"Tag clouds normally are a large problem for finding and navigating, they work best on distinct objects, e.g. '2010 Ford Mustang.' Top level tag clouds normally work best for the things biggest and boldest, but most people don't see the other elements. Twitter's own list view of hot topics is easier for people to grasp. Tag clouds are more cool and fun (for those few that grok them) than helpful - any usability testing normally drops them from consideration for use."

"This new integration does not sound like much of a value add to what Twitter already offers, just mashing it into something else. The basic level Information Architecture on the Bing Twitter search page is far from clear. The way that retweeting gets gamed I am not sure how valuable that metric is, but if weighted low in an algorithm it could have value."

"Playing with the site, it does not understand me in context. The 'most recent tweets about...' are pulling from the public stream and are not delivering quality results. It's not taking into account who I am, which means it is not pulling things related on following relationships."

"I am one of those outliers who deals with heavy information flows. Having something that can not sort through the volume of micro information without adding some contextual relevance is going to be tough for general users."

"If Bing learns interests to filter by context and interest then there is really something there."

Nicole Califano, UX Designer at The Barbarian Group in San Francisco.

"My first instinct is that there needs to be some really creative user preferences down the line, as this could get messy. This is all very exciting but I'm a little concerned with filtering these channels (so far I think Twitter & Facebook are unsuccessful at filtering).

"No doubt, Google will be integrating Twitter, Facebook and other social outlets to their search soon too. This is not a new idea, but the right execution has yet to be seen."

Can Bing step up its game with regards to Twitter search? The initial launch isn't very promising, especially when there are so many small startups doing much more interesting things with search on top of Twitter. At the very least the integration might bring real time into the consciousness of more consumers, though.

In our tests, Stinky Teddy performed pretty well, especially when we searched for politicians and celebrities. The only real disappointment was that the videos from Videosurf - which we like a lot as a video search engine - were often rather old. Sometimes, old search results also slipped into the news search. You can, however, filter results according to the type of source, so that Stinky Teddy displays only items from news sources, for example, or from real-time sources like Collecta and Twitter.

Bridging the Gap With Meta-Search

We have seen quite a few real-time search engines like OneRiot, Faroo, and Collecta recently, but it seems that every time the search engine market hits on a new concept, meta-search engines like Stinky Teddy come in to bridge the gap between existing products and the new generation of search engines.

In its current state, Stinky Teddy is definitely worth a look. It's still in its early days, and Hardtke is still actively tweaking the algorithms in the background; but the variety of sources make it a worthwhile alternative to other real-time search engines.

One of the most interesting feature of the app, besides the ability to quickly access all of the power that Wolfram Alpha now offers, is the fact that the company has found a way to make inputing queries very easy. Instead of a single keyboard at the bottom of the screen, the app actually displays two keyboards - one for numbers and symbols, and a regular QWERTY keyboard at the bottom of the screen. Given the nature of a typical query for Alpha, this makes perfect sense and we hope that others will follow Alpha's lead here.

A Web-Connected Graphing Calculator, But With Some Limitations

It's important to note that the app only works when a user is connected to the Internet. This could be a deal-breaker for some, but then, the app store already offers plenty of basic graphing calculators for those times when you don't have Internet access. Thanks to its vast database of chemical compounds, nutritional data, geographical information, financial data, and its ability to solve pretty much any math problem that a high school or college student will ever encounter, the app can do a lot more than any current graphing calculator can offer.

For some students, though, the problem could be that some teachers won't allow them to bring a full-blown Internet-capable device like the iPhone or an iPod touch into an exam. In addition, it's also important to note that the Wolfram Alpha doesn't offer the ability to write programs inside the app, though maybe somebody else will build an app that can do this based on Alpha's newly released API.

It's also important to remember that Alpha isn't as easy to use as Google. Alpha, and, by extension, the app, can be rather strict about how you structure a query, for example. If you don't capitalize a chemical formula, the app won't know what to do with these symbols. While Google has virtually no learning curve, Alpha works best if you invest some time into exploring the intricacies of how to structure queries. To help you along the way, the app features a demo video, lots of example queries, and an FAQ section.

Native App Offers a Bit More Than the Web Service, But Is That Enough to Justify the High Price?

In its press materials, the Wolfram Alpha team stresses that the app offers a number of features that the web app can't currently offer. The app can now make assumptions based on your location, for example. Wolfram also has added quite a few features that make using the app easier than using the web service. You can easily bookmark queries and the app keeps a running list of recent searches available as well. In addition, you can easily email queries or share them on Twitter.

Is $50 Too Much?

At $49.99, there can be no doubt that Wolfram Research is pricing the app at the higher end of the spectrum. A spokesperson for Wolfram Alpha told us that the company wants to target the app at "serious users, and is priced as such." The team is clearly aware that this price could be controversial, especially given that the mobile web site offers a similar interface, though without the ergonomic benefits of the native app. In addition, Wolfram tells us that the team wants to use this price to make a statement about the "non-trivial nature" of Wolfram Alpha's capabilities.

While the company plans to offer regular discounts and sales, we can't help but wonder if the price isn't a bit too high. At $9.99 or even $19.99, the app would be more of an impulse buy, while now, even though it obviously offers more features than a user would ever expect from a high-priced hardware graphing calculator which would generally retail for more than $100.

Verdict

Wolfram Alpha launched to so much hype that a backlash was inevitable when it finally launched. As Schoeller Porter, the product manager for the iPhone app, notes, the company is also launching this app "as an opportunity to highlight how far the system has come since launch." Indeed, the Wolfram Alpha team continues to add new data sources and new ways to query them, making the service more useful with every new dataset it adds.

The high price will probably keep quite a few potential users from downloading the app, however. While we understand the company's rational behind this high price, users generally consider a $10 app to be a 'premium' product. $49.99 is a hefty price for this app, especially considering that the majority of features is available through the web service. If you are a student or engineer who really needs these features, though, the app is worth a look, but we recommend you try the web service and see how it works for the kinds of queries you would enter before you spend $50, especially given that the company will surely offer discounts or bring the base price down at some point.

Says Ask President Scott Garrell, "Searches for coupons on Ask.com have shot up almost 50% in 2009. With the holidays approaching, we know this service will help us make an impact with our users."

In early August, ReadWriteWeb covered Yahoo's recent Deals launch. Similar to Yahoo Deals, Ask Deals aggregates coupons and sales in a separate and easy-to-use shopping channel. However, when it comes to search, Yahoo redirects users to the Yahoo Deals page while Ask blends deals directly into standard results. In an effort to save consumers time, Ask also attempts to link directly to coupons and savings that are listed up front. For example, when you search for clothing, deals are listed from best to worst in terms of percentage of discount. From here users can share deals via Facebook, MySpace, Twitter, Delicious and Digg.

Sale news is available to members via the website, email and the Ask Deals Twittter account. Users can also install the Ask Deals homepage skin to see the featured "Deals of the Day". To install the skin visit Ask.com/skins.

There has been quite some discussion about whether this actually turns out to be true, though. Judging from this new study by Summit Media, there really haven't been too many changes to the rankings in Caffeine, though the Summit Media team did notice some interesting differences.

There was no major difference between the kinds of categories of sites Caffeine prefers compared to Google's 'vanilla' search. Caffeine, for example, doesn't give any more weight to price comparison sites than Google's current search infrastructure. One slight difference that the Summit Media study noticed was that slightly more co.uk domain names now appear in searches that originate from the US. The difference there, though, was only minor.

Difference: News Sites

One area where Summit Media noticed a difference, however, was sites that fall into the 'Information,' and 'News' categories. Here, at least for generic search terms, Caffeine shows a bias towards more timely information and seems to punish sites that don't update often and mostly consist of archived material.

Does it Help to Have a Keyword in Your Domain Name?

Summit Media also tested another popular SEO theory: does it help to have your keyword in your domain or page URL? Summit didn't find a difference between the Caffeine and 'vanilla' search results and maybe more importantly, having a keyword in your domain name doesn't seem to make a real difference when it comes to search rankings. According to Summit, only about 6% of all search results on the first three search results pages actually contain the specific keyword in the URL. That's a very small number, and, as the report concludes, it is also "a demonstration that SEO needs to be based on actual research - rather than perceptions over browsing a few pages of results."