The team over at http://www.simplifiedses.com sent us word last night that their new product has been launched. Cloaked Site Builder. We look forward to writing an in depth review in the coming days.
A lot of networks these days don’t allow direct linking (forced clicks as they like to call them). They want to see the source of your traffic, and beyond that, it needs to be a legit source of traffic. This can be a problem if you have less than clean sources for your traffic. A lot of networks no longer accept myspace, facebook, or craigslist traffic for example. So, how can we quickly and easily get around that?
Landing Pages!
The concept is simple enough:
traffic source ——>Landing Page——–>Affiliate offer
The biggest problem is time. If we are promoting 100 new offers with dozens of products each, it would take weeks if not months to build decent landing pages. This is where a piece of software called Landing Page Builder comes in. With LPB we setup our landing page domain then import a csv that contains all of our product info. This includes descriptions, prices, affiliate url’s, product name, and images. The software has a built in token mapper which allows us to map the csv columns to tokens that we can use in our templates.
Here we can manage and view the mapped tokens:
So, next we need to setup a template. We need something that is simple and to the point. We want everything to lead the person to click through to our affiliate product without scaring them off. Use phrases like “more info” or “read reviews”, even “compare prices” instead of “Buy Now”. People shy away from clicking buy now links, and our goal here is to get the visitor onto the merchants site so we set our cookie and have the opportunity to sell the product. So, we create our template with that in mind and insert our tokens using the built in template editor.
Now, the true power of this software comes out. The software is all dynamic, meaning the landing pages are generated on the fly. You don’t need to build 10,000 pages, you just create your template and upload the csv. Now you have 10,000 Landing Pages created in a matter of a few minutes each with a url like domain.com/product-keyword.
So, how do we filter our traffic through these landing pages? Easy, we just send it all to the main index page of the domain. domain.com in our example. The software analyzes the referrer string to find out what the user was searching for, it then generates a Landing Page with that products info and of course links for the user to click through to the affilaite page. The affiliate or cpa network now sees the landing page as the referrer and your traffic is 100 percent legit. On top of that, your EPC goes through the roof because you have prequalified the visitors to the affiliates offers. The pages all exist and can be requested, so everything looks fine. If you prefer you can also redirect your traffic to a particular page if you prefer that over the dynamic system. If the network allows it you can even use a double meta refresh to blank the referrer, masking the source of your traffic completely.
You can get Landing Page Builder here You can even get a 10 percent discount using the following coupon code: BHLPB10
The latest version of the Black Hat SEO Crash Course E Book has been released. To download, head on over here:
Black Hat SEO Crash Course V11
Or the torrent link:
Do patents, white papers, and other publications authored by search engine employees provide clear guidance to how to optimize Web pages? A panel of experts debated the issue at a recent Search Engine Strategies conference.
Software engineers and other staff at the commercial web search engines publish academic papers and apply for patents, which may or may not give proof about how search engines find and rank web pages. Dissecting whether understanding patents helps search optimizers were panelists Jon Glick, Senior Director of Product Search and Comparison Shopping at Become.com; Rand Fishkin, CEO of SEOmoz.org; and Bill Slawski, President of SEO by the Sea, Inc.
Search engine patents: proof or no proof
Many search engine optimizers regularly monitor search engine patent applications and use this documentation as proof that their methodologies help web pages rank. However, patent applications often offer limited, and even misleading, information.
“What search engines put into patents is often more like brainstorming,” said Glick. “It’s every approach that they can think of versus what they are actually doing, or even have a technology to do.”
Search engine staff file patents with the idea that they might use certain features in the future yet prevent their competitors from utilizing the same features. “Search engine staff know that their patent applications will be read by competitors and SEOs,” he continued. “You don’t actually have to use the features in the patent to be granted a patent, nor does anyone have to disclose all features in a patent application.”
For example, personal data is not likely to be used as part of a search engine algorithm. Many people might use the same computer (such as computers in libraries, universities, and Internet cafes); therefore, the personal data is often inaccurate and does little to enhance the search experience. Nonetheless, this information can be a part of the patent application.
“People should realize that looking at patents and white papers might describe things that never happen,” echoed Slawski.
However, some items in a patent application can be useful, such as the frequency of change of links, or evaluation of out-links. Web site owners do not have control over how other sites link to their site, but they do have complete control over their content and the sites they choose to link to. “Traditionally, search engines have ranked a web site based on who links to the site, not who the site link to,” said Glick. Both Google and Yahoo! use out-links for spam evaluation, and next-generation algorithms are using them.”
According to Fishkin, search engines recognize manipulative link-building techniques by looking at links and link flow.
“Manipulative links are built for search engines, not (human) users,” said Fishkin. “They are built automatically rather than by hand. They are not an editorial vote for the quality of a page and are influenced by financial or less ‘legitimate’ incentives.”
Search engines use algorithmic techniques for identifying and combating manipulative links. Some of these techniques might include:
* Spotting link networks
* Similarity identification
* Trends and search data evaluation
* web analytics and user surfing data
“If you’re concerned about privacy,” added Fishkin, “you have to question where the data from Google Analytics goes.”
Even expert SEOs can be easily confused with patent information. For example, some SEOs believe that having an RSS feed will automatically give a site a boost in rankings. However, if a site has an RSS feed, it might be crawled more frequently because the site is likely to have fresh content. “The rate of change in content mostly impacts crawl frequency, not ranking,” said Glick.
Evolution of search engine algorithms
Search engine algorithms are constantly evolving. “Search algorithms are getting better and better at understanding what the content on pages actually means,” Glick stated. “A few years ago they were just blindly indexing the words on a web page, but now they are beginning to understand what some of those words mean and what the page represents (store, news article, etc.) For example, (650) 555-1212 is a phone number.”
Slawski sees search engine algorithms evolving in stages. Stage 1 was a “one size fits all approach,” which, as Glick mentioned, was not very effective.
Stage 2 algorithms developed through understanding users. “Search engines are looking more into search query data, which involves analyzing search queries, collecting searcher information, and matching searcher intentions,” Slawski said. “With Stage 3, search engines are taking a step forward, not only looking at interactions but at people themselves.”
Should SEOs regularly monitor patent applications, white papers, and other publications that are authored by search engine software engineers and scientists? Absolutely. Search engines constantly try to improve the search experience, and information provided in these documents can help web site owners improve the search experience on their own sites. However, realize that patent information might not always offer the solid “proof” of an algorithm that one might believe.
Today, Microsoft publicly unveiled its soon-to-launch search engine Bing. It will become available over the next few days, and be fully launched by June 3. On the surface, Bing has a distinct gloss. The home page features a rotation of stunning photography, for instance, which can be clicked on to produce related image search results. But the most significant changes are under the covers. “We have taken the algorithmic programming up an order of magnitude,” says Microsoft senior vice president Yusuf Mehdi. Each search result page is customized according to what type of search you do (health, travel, shopping, news, sports). The algorithms determine not only the order of results on the page, but the layout of the page itself, concluding what sections appear. These sections can include anything from guided refinements and a list of related searches in the left-hand pane to images, videos, and local results.
I’ve been playing around with a preview version of Bing for about a week. It is designed to be “more of a decision engine,” says Mehdi. Bing helps people make decisions through guided search and a focus on task completion. In a time when a new Website is created every 4.5 seconds, information overload is becoming a real problem. ” People are getting hundreds of thousands of links but not getting what they want,” says Mehdi. Bing tries to alleviate problem by offering up different experiences depending on the search.
The internal codename for Bing is Kumo (which is what you see in the screenshots), and the current release is called Kiev. Rather than a spare, blank screen, Bing’s homepage surrounds the search box with a single beautiful image, such as the one of the tribesmen above or a kinkajou. You can hover over parts of the image to get factoids about the image or click through to an image search result page to explore more. The left-hand pane offers the option to narrow your search on images, videos, shopping, news, maps, or travel. Each of these has a different look and feel. A travel search will turn up a page based on Microsoft’s Farecast technology asking you where you want to go, with flights, hotels, and destination information. A news search offers up headlines, photos, videos, and local news in a column on the right. A shopping search will bring up products and is tied into Microsoft’s Cashback program.
Every search also generates a guide on the left to help you refine your search. A search for “kinkajou,” for example, lets you refine by images, facts, sale, breeders, care, diseases, and videos. A search for “Samsung LCD TVs” brings up an entirely different set of guided results: shopping, review, manual, repair, buy, stand, images, and videos. If you search for images of “butterflies,” it lets you sift to show just Monarch, Swallowtail, Viceroy, Owl, and other types of butterflies. All of this categorization and concept-matching is Microsoft’s early attempt to bring in some basic semantoc search technologies into a mainstream search engine. Each guided option is dynamically generated, just like the different sections of the search results page. “Google, tried to preempt this,” says Mehdi, referring to Google’s new search refinement options it launched last week, which is also in the left pane. Those Google options, which include the ability to search across different time periods or for related keywords, are “completely static,” criticizes Mehdi. “There is nothing new about it. It is a very minor rev, not as sophisticated as what we are doing. For us ever query is special.”
Bing also takes advantage of Microsoft’s acquisition of Powerset to provide better previews and snippets of text when you hover over a result. Also, whenever a search brings up a “reference” tab in the guided exploration pane, clicking on that will bring up an enhanced Wikipedia article with semantic tags.
Onstage at the D7 conference, Steve Ballmer acknowledges: “There is no way to change the whole game in one step.” But search “deserves a good feature war.” And Bing will be rolling out new features as it goes forward. But is it enough to get people to switch? Bing is certainly not a game-changer, but it does cut out a lot of the back and forth that happens with so many searches today. If Bing can help people find what they are looking for faster, it will put pressure on Google to keep advancing the ball as well.
Within the next few days, Microsoft is expected to unveil its latest attempt at trying to be a player in the world of web search. After it has failed to get live.com any traction against Google, it will apparently launch a new engine called “Bing” — the project formerly known by its working title “Kumo.” This should be unveiled at the D conference which starts today in Carlsbad, CA — but it looks like Microsoft may be giving us a peak at the logo a tad early.
While it appears that Microsoft may have already taken it down, I visited bing.com in my browser about 10 minutes ago and sure enough saw the favicon you see above. It’s a lowercase “b” with a yellow/orange dot in the middle. It would appear that this will be at least a part of the Bing logo. The light blue and yellow/orange color combination matches that of Kumo. I find that combination to be quite ugly — sort of like the Cleveland Cavaliers basketball uniforms (below) from the 1990s — but hey, that’s just personal taste. All that really matters is now the search engine actually performs.
This favicon, which again, may only be a part of the logo, also looks a lot like the logo for Blinkx, the video search engine. That features a red lowercase “b” with an eye in the middle.
Microsoft is spending some $80 to $100 million on a marketing campaign for Bing, according to Ad Age. That’s huge by any standard, but especially when you consider that Google only spent $25 million on all of its marketing last year. I don’t know what Microsoft plans to spend all that money on, but I get the sneaking suspicion that Bing Crosby will be involved in some way or another.
I’ve been quite busy for the past week or so, but that hasn’t stopped me from tracking results. There are 10 main key phrases that I consider vital for my traffic. As of this morning I am on the first page of Google for all 10. One of the more popular phrases has 54 million results and is quite competitive, so I have to say i’m quite pleased about that. Traffic is up, subscribers are up, and i’m ranking for all of the phrases I need at this point. Now that i’ve seen the results, all I need to do is target a few dozen other phrases and take things to the next level. Stay tuned.
Google has just launched a new “search options” feature on its main search page. When you click on “Search options” you can filter your search by different types of results (videos, forums, and reviews), by time (recent, past 24 hours, past week, past year), as well as seeing related searches, a “wonder wheel” view, or a timeline view.
At Google’s Searchology event, which is going on right now, Marissa Mayer listed the following as the hardest unsolved problems in search:
- Finding the most recent information
- Expressing that you want just one type of result
- Assessing which results are best
- Knowing what you’re looking for
- Expressing your searches in keywords
Notice that real-time search is the No. 1 problem. (Twitter and a bunch of startups from OneRiot to Tweetmeme are also working on it, with the latter two launching their own real-time search efforts today). And it certainly is a problem for Google, even with the new recent results option. Try searching for any of teh top trending results on Twitter right now like Miss California (vs. Twitter search results) or Star Trek (vs. Twitter results), and you don’t even get any Twitter results on Google.
While real-time search is still a big problem, it is not the only problem. Some of the new options address the difficulty of searching back through time. The recent results get as real-time as Google can get, but you can also expand the timeframe. And you can look at an actual timeline of results, which looks for dates within results and then places them chronologically (this is sort of hit or miss—just because a date is mentioned in a text does not mean the entire result is about or from that period of time). Google now also lets you see related searches as an option. And the Wonder Wheel is more of a visual aid to see how different related topics are clustered together. When you click on any spoke of the wheel, it then causes that search term to be at the center. We’ve seen many of these techniques in the past, but Google is giving them a higher profile by putting them in its main search page..
One of the next frontiers of search is taking all of the unstructured data spread helter-skelter across the Web and treat it like it is sitting in a nice, structured database. It is easier to get answers out of a database where everything is neatly labeled, stamped, and categorized. As the sheer volume of stuff on the Web keeps growing, keyword search keeps getting closer to its breaking point. Adding structure to the Web is one way to make sense of all that data, and Google is starting the tackle the problem with a Google Labs project called Google Squared, which Marissa Mayer mentioned earlier today at the company’s Searchology briefing.
Google Squared extracts data from Web pages and presents them in search results as squares in an online spreadsheet. Michael was at the event and got a personal demo (see video below). From Michael’s Searchology notes:
Google Squared is launching later this month in labs. Google Squared returns search results in a spreadsheet format. It structures the unstructured data on web pages. So a search for Small Dogs returns results with names, description, size, weight, origin, etc., in columns and rows.
Google is looking for data structures on the web that imply facts, and then grabbing it for Squared results. “It takes an incredible amount of compute power to create one of those squares,” she says.
This type of technology has obvious applications for many types of targeted searches, including product search, health search, scientific searches, you name it. There are dozens of semantic search startups trying to impose structure on the Web to perform similar tricks. Another high-profile search startup which is launching on Monday, Wolfram Alpha, takes a slightly different approach in that it simply ingests massive amounts of information into its own databases where it can query it to its heart’s delight. Already there is a bit of a rivalry between Google and Wolfram because getting back structured results is a major new direction for search.
Wolfram does a pretty good job parsing the information in its own databases, but those databases will never match what is available on the Web. Wolfram’s databases currently store only 10 terabytes of information, a tiny fraction of what is on the Web. (I will be posting my impressions of Wolfram’s search engine soon). Google Squared is an early attempt to take the messy data which exists on the Web and place it into simple tables. It is still very experimental and isn’t always on target, but you can see where this is going. Turning the Web into a giant database will crush any attempt to segregate the “best” information into a separate database so that it can be processed and searched more deeply.
In the video demo below, a search for “camera” sorts the results in different columns by images, description, and manufacturer, resolution, etc.. You can refine results by clicking on a particular column such as manufacturer. A search for “rollercoasters” sorts results by name, image, description, height, length, and number of inversions. But sometimes it gets confused. A search for “spaceships” turns up a Corvette and a missile carrier. It is going to be a while before this makes it out of Google Labs