SearchCap: Bing Shopping Campaigns Updates, SEO For Local Businesses & Google’s Halloween Doodle

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Below is what happened in search today, as reported on Search Engine Land and from other places across the web.

From Search Engine Land:

Recent Headlines From Marketing Land, Our Sister Site Dedicated To Internet Marketing:

Search News From Around The Web:

Industry

Local & Maps

Search Marketing

Searching

SEM / Paid Search

SEO

The post SearchCap: Bing Shopping Campaigns Updates, SEO For Local Businesses & Google’s Halloween Doodle appeared first on Search Engine Land.

Last Chance to Enter the SocialPro Biggest Social Geek Contest

Enter the second annual SocialPro Biggest Social Geek Contest, sponsored by Marin Software. The contestant who can answer the most questions in the shortest amount of time will win the grand prize – a flight and hotel accommodations for two to Marketing Land’s SocialPro conference in Las Vegas, Nevada on November 18-19, 2015. The winner will also receive their choice of an Apple iPad Mini, Sony PlayStation 4, or an Xbox One.

The 2015 contest is open to contestants in the United States, United Kingdom, Canada, France, Germany and Australia and ends on October 30, 2015 at 11:59 p.m. Pacific Time.

Time is running out! Play now and prove you’re the geek to beat:

 

http://www.biggestsocialgeek.com/

 

The post Last Chance to Enter the SocialPro Biggest Social Geek Contest appeared first on Search Engine Land.

Micro Niche Authority Sites Generating $100+/month

Micro Niche Authority Sites Generating $100+/month

Quality Authority Sites Earning $100+/month

  • Earn in Less then 7 days of full site delivery ( From Organic Traffic ONLY )
  • 100% Genuine Methods. (Lots of Solid white hat, a small amount of grey hat, NO BLACK HAT)
  • 100% Satisfaction Guarantee
  • Lightening Fast Host
  • 90+ Google Page Speed Score
  • Min $100+ Earning Per Month

While we are new to Source Market we have been selling these exact same types of monetized blogs on another platform for $497 with a 100% satisfaction rating. 

What is the difference between the Micro Niche package for $397 and the Super Micro $997 package?
The $397 package will be for micro niches that will likely only average $100-$200 per month long-term.
The $997 package is for Super Micro Niches and have a $500-$600+ per month potential. Some earn $1500+

I’m going to still offer the Super Micro Niche as an upgrade on this listing.

Important things to keep in mind: 

While we know how to build out blogs that earn $1000-$2000+ per month quickly we choose not to for a very important reason. Anyone with the knowledge and the right tools can build those “turn and burn sites” that earn money for a couple of months then are de-indexed and the revenue stops cold. 

Instead, we build them with a more long-term goal in mind:to earn steadily month in and month out for years to come.

Hi, my name is Scott Lamon and I’m a real person. I don’t have more than 1 account on here like others do to give themselves ratings. 

I simply stand on the results I produce and let them speak for themselves. 

I am so confident in our services that I offer 100% Guarantee:

If the site does not earn $100+/month minimum in the 2nd month – We will replace the site or refund you money, Your choice.

Features Of Each Site

 

  • 1 Niche With 2000+ Monthly Searches .
  • 3-4 Sub niches.
  • Exact Match Domain ( .Com , .Net , .Org )
  • 5 Unique Articles.
  • Premium SEO Optimized Swift Theme.
  • Logo.
  • Privacy Policy, Disclaimer , Contact Us and About Us Page will be Provided.
  • Full SEO Optimization.
  • On Page SEO Will Be Provided.
  • Off Page SEO Will be Provided.
  • 1 Pinterest Board.
  • 1 Video.
  • Authorship.
  • Site Will be submitted to Google And All Major Search Engines.
  • Money Back Guarantee.
  • Minimum $100+ Revenue in Adsense per Month.

FAQs
Why don’t you just build them for yourselves? 
We do. But there’s also money in providing the service to others.

Is Adsense the only revenue option?  No, we start with Adsense but add other income streams like Amazon affiliate, CPA, etc. that fits that particular micro niche.

Do I need hosting? Yes. We can help you with that. Your new site will be hosted on our lightning fast servers which we recommend you keep it on but that is completely up to you.

Can I choose my own Niche? Yes. But it is usually best to use a profitable Micro Niche we’ve found already.

What’s the upkeep on the sites? The upkeep is your typical site maintenance. Hosting and domain fees, etc…once we finish with the site and you start earning, we’ll hand it over to you and it’ll be yours to take care of from then on. There should be no need to spend anything on getting backlinks or anything like that.

Is the earnings consistent? Yes, this isn’t a cheap $35 service. While earnings may fluctuate slightly you’ll keep earning every month. 5%-10% growth every month is very common. 

When can I expect to earn? Users have experienced earnings of $100+ within the 1st month. If you’re expecting something sooner, please look somewhere else. We build long term earning sites only.

Do I need an Adsense Account? Yes. Don’t have one? Order here – http://market.source-wave.com/services/2227?affid=dd357b

What if I’m impatient and want a site quicker? Don’t order from us. We build quality and it takes time.=]

Can I see a demo site? Drop us a message. We have a strict policy of not sharing URLs of previous customers but would be happy to send you a link to one we are building currently. 

Enterprise Call Analytics Platforms – New Marketing Intelligence Report

Marketing Land and Digital Marketing Depot have recently published a new Market Intelligence Report, “Enterprise Call Analytics Platforms 2015,” that examines the market for call analytics platforms.

The flood of mobile calls to U.S. businesses continues unabated, changing the way brands view the telephone as an inbound marketing channel. As consumers increasingly use their smartphones to research, browse, and connect with businesses, brands are developing a new found respect for the inbound call as an integral part of the conversion path.

This report examines the current market for enterprise call analytics platforms and the considerations involved in implementing this technology. If you are considering licensing an enterprise call analytics platform, this report will help you decide whether or not you need to. It provides relevant statistics on market growth, developing market trends, recommended steps for making an informed purchase decision, and profiles of leading enterprise call analytics vendors.

Click here to get your copy.

The post Enterprise Call Analytics Platforms – New Marketing Intelligence Report appeared first on Search Engine Land.

Bing Brings On Halloween With a Spooky Map, Cortana Costume Suggestions & A Horror Movie Game

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Bing is gearing up for the holiday weekend, launching Halloween-related Cortana searches and a spooky Bing map that includes locations for haunted houses throughout the US, UK and Canada.

 

For anyone who still doesn’t have their costume figured out, Bing recommends asking Cortana, “What should I wear for Halloween?”

 

Bing cortana what should i be for halloween

 

Cortana also has a new “Guess the horror movie” game to keep you occupied while you’re waiting to go trick-or-treating — the phrase “guess the horror movie” prompts the quiz.

 

Bing cortana halloween game

 

The Bing Maps team is getting in on the Halloween fun, as well, releasing a new spooky map with a “frighteningly fun color palette and a new set of Halloween-themed icons” that users can opt in to use. Haunted house locations are included on the US, UK and Canada versions of Bing’s Halloween map.

 

Bing spooky map 2015

 

Bing says costume images from e-commerce sites that show up in searches will include its shopping cart badge to note how many sites have the costume for sale. Food images will also have the recipe badge to help users find recipes for specific Halloween treats.

 

Bing Halloween shopping cart badge

 

Bing is also planning a special Halloween treat for its home page that it will release on October 31.

The post Bing Brings On Halloween With a Spooky Map, Cortana Costume Suggestions & A Horror Movie Game appeared first on Search Engine Land.

FAQ: All About The New Google RankBrain Algorithm

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Yesterday, news emerged that Google was using a machine-learning artificial intelligence system called “RankBrain” to help sort through its search results. Wondering how that works and fits in with Google’s overall ranking system? Here’s what we know about RankBrain.

The information covered below comes from three sources. First, the Bloomberg story that broke the news about RankBrain yesterday (see also our write-up of it). Second, additional information that Google has now provided directly to Search Engine Land. Third, our own knowledge and best assumptions in places where Google isn’t providing answers. We’ll make clear where any of these sources are used, when deemed necessary, apart from general background information.

What Is RankBrain?

RankBrain is Google’s name for a machine-learning artificial intelligence system that’s used to help process its search results, as was reported by Bloomberg and also confirmed to us by Google.

What Is Machine Learning?

Machine learning is where a computer teaches itself how to do something, rather than being taught by humans or following detailed programming.

What Is Artificial Intelligence?

True artificial intelligence, or AI for short, is where a computer can be as smart as a human being, at least in the sense of acquiring knowledge both from being taught and from building on what it knows and making new connections.

True AI exists only in science fiction novels, of course. In practice, AI is used to refer to computer systems that are designed to learn and make connections.

How’s AI different from machine learning? In terms of RankBrain, it seems to us they’re fairly synonymous. You may hear them both used interchangeably, or you may hear machine learning used to describe the type of artificial intelligence approach being employed.

So RankBrain Is The New Way Google Ranks Search Results?

No. RankBrain is part of Google’s overall search “algorithm,” a computer program that’s used to sort through the billions of pages it knows about and find the ones deemed most relevant for particular queries.

What’s The Name Of Google’s Search Algorithm?

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It’s called Hummingbird, as we reported in the past. For years, the overall algorithm didn’t have a formal name. But in the middle of 2013, Google overhauled that algorithm and gave it a name, Hummingbird.

So RankBrain Is Part Of Google’s Hummingbird Search Algorithm?

That’s our understanding. Hummingbird is the overall search algorithm, just like a car has an overall engine in it. The engine itself may be made up of various parts, such as an oil filter, a fuel pump, a radiator and so on. In the same way, Hummingbird encompasses various parts, with RankBrain being one of the newest.

In particular, we know RankBrain is part of the overall Hummingbird algorithm because the Bloomberg article makes clear that RankBrain doesn’t handle all searches, as only the overall algorithm would.

Hummingbird also contains other parts with names familiar to those in the SEO space, such as PandaPenguin and Payday designed to fight spam, Pigeon designed to improve local results, Top Heavy designed to demote ad-heavy pages, Mobile Friendly designed to reward mobile-friendly pages and Pirate designed to fight copyright infringement.

I Thought The Google Algorithm Was Called “PageRank”

PageRank is part of the overall Hummingbird algorithm that covers a specific way of giving pages credit based on the links from other pages pointing at them.

PageRank is special because it’s the first name that Google ever gave to one of the parts of its ranking algorithm, way back at the time the search engine began in 1998.

What About These “Signals” That Google Uses For Ranking?

Signals are things Google uses to help determine how to rank Web pages. For example, it will read the words on a Web page, so words are a signal. If some words are in bold, that might be another signal that’s noted. The calculations used as part of PageRank give a page a PageRank score that’s used as a signal. If a page is noted as being mobile-friendly, that’s another signal that’s registered.

All these signals get processed by various parts within the Hummingbird algorithm to ultimately figure out which pages Google shows in response to various searches.

How Many Signals Are There?

Google has fairly consistently spoken of having more than 200 major ranking signals that are evaluated that, in turn, might have up to 10,000 variations or sub-signals. It more typically just says “hundreds” of factors, as it did in yesterday’s Bloomberg article.

If you want a more visual guide to ranking signals, see our Periodic Table Of SEO Success Factors:

Periodic Table Of SEO Success Factors 2015

It’s a pretty good guide, we think, to general things that search engines like Google use to help rank Web pages.

And RankBrain Is The Third-Most Important Signal?

That’s right. From out of nowhere, this new system has become what Google says is the third-most important factor for ranking Web pages. From the Bloomberg article:

RankBrain is one of the “hundreds” of signals that go into an algorithm that determines what results appear on a Google search page and where they are ranked, Corrado said. In the few months it has been deployed, RankBrain has become the third-most important signal contributing to the result of a search query, he said.

What Are The First And Second-Most Important Signals?

Google won’t tell us what the first and second-most important signals are. We asked. Twice.

It’s annoying and arguably a bit misleading that Google won’t explain the top two. The Bloomberg article was no accident. Google wants some PR about what it considers to be its machine-learning breakthrough.

But to really assess that breakthrough, it’s helpful to know the other most important factors that Google uses now, as well as was was knocked behind by RankBrain. That’s why Google should explain these.

By the way, my personal guess is that links remain the most important signal, the way that Google counts up those links in the form of votes. It’s also a terribly aging system, as I’ve covered in my Links: The Broken “Ballot Box” Used By Google & Bing article from the past.

As for the second-most important signal, I’d guess that would be “words,” where words would encompass everything from the words on the page to how Google’s interpreting the words people enter into the search box outside of RankBrain analysis.

What Exactly Does RankBrain Do?

From emailing with Google, I gather RankBrain is mainly used as a way to interpret the searches that people submit to find pages that might not have the exact words that were searched for.

Didn’t Google Already Have Ways To Find Pages Beyond The Exact Query Entered?

Yes, Google has found pages beyond the exact terms someone enters for a very long time. For example, years and years ago, if you’d entered something like “shoe,” Google might not have found pages that said “shoes,” because those are technically two different words. But “stemming” allowed Google to get smarter, to understand that shoes is a variation of shoe, just like “running” is a variation of “run.”

Google also got synonym smarts, so that if you searched for “sneakers,” it might understand that you also meant “running shoes.” It even gained some conceptual smarts, to understand that there are pages about “Apple” the technology company versus “apple” the fruit.

What About The Knowledge Graph?

The Knowledge Graph, launched in 2012, was a way that Google grew even smarter about connections between words. More important, that it learned how to search for “things not strings,” as Google has described it.

Strings means searching just for strings of letters, such as pages that match the spelling of “Obama.” Things means that instead, Google understands when someone searches for “Obama,” they probably mean US President Barack Obama, an actual person with connections to other people, places and things.

The Knowledge Graph is a database of facts about things in the world and the relationships between them. It’s why you can do a search like “when was the wife of obama born” and get an answer about Michele Obama as below, without ever using her name:

obama wife

How’s RankBrain Helping Refine Queries?

The methods Google already uses to refine queries generally all flow back to some human being somewhere doing work, either having created stemming lists or synonym lists or making database connections between things. Sure, there’s some automation involved. But largely, it depends on human work.

The problem is that Google processes three billion searches per day. In 2007, Google said that 20 percent to 25 percent of those queries had never been seen before. In 2013, it brought that number down to 15 percent, which was used again in yesterday’s Bloomberg article and which Google reconfirmed to us. But 15 percent of three billion is still a huge number of queries never entered by any human searcher — 450 million per day.

Among those can be complex, multi-word queries, also called “long-tail” queries. RankBrain is designed to help better interpret those queries and effectively translate them, behind the scenes in a way, to find the best pages for the searcher.

As Google told us, it can see patterns between seemingly unconnected complex searches to understand how they’re actually similar to each other. This learning, in turn, allows it to better understand future complex searches and whether they’re related to particular topics. Most important, from what Google told us, it can then associate these groups of searches with results that it thinks searchers will like the most.

Google didn’t provide examples of groups of searches or give details on how RankBrain guesses at what are the best pages. But the latter is probably because if it can translate an ambiguous search into something more specific, it can then bring back better answers.

How About An Example?

While Google didn’t give groups of searches, the Bloomberg article did have a single example of a search where RankBrain is supposedly helping. Here it is:

What’s the title of the consumer at the highest level of a food chain

To a layperson like myself, “consumer” sounds like a reference to someone who buys something. However, it’s also a scientific term for something that consumes food. There are also levels of consumers in a food chain. That consumer at the highest level? The title — the name — is “predator.”

Entering that query into Google provides good answers, even though the query itself sounds pretty odd:

food chain consumer

Now consider how similar the results are for a search like “top level of the food chain,” as shown below:

top_level_of_the_food_chain_-_Google_Search

Imagine that RankBrain is connecting that original long and complicated query to this much shorter one, which is probably more commonly done. It understands that they are very similar. As a result, Google can leverage all it knows about getting answers for the more common query to help improve what it provides for the uncommon one.

Let me stress that I don’t know that RankBrain is connecting these two searches. I only know that Google gave the first example. This is simply an illustration of how RankBrain my be used to connect an uncommon search to a common one as a way of improving things.

Can Bing Do This, Too, With RankNet?

Back in 2005, Microsoft starting using its own machine-learning system, called RankNet, as part of what became its Bing search engine of today. In fact, the chief researcher and creator of RankNet was recently honored. But over the years, Microsoft has barely talked about RankNet.

You can bet that will likely change. It’s also interesting that when I put the search above into Bing, given as an example of how great Google’s RankBrain is, Bing gave me good results, including one listing that Google also returned:

What’s_the_title_of_the_consumer_at_the_highest_level_of_a_food_chain_-_Bing

One query doesn’t mean that Bing’s RankNet is as good as Google’s RankBrain or vice versa. Unfortunately, it’s really difficult to come up with a list to do this type of comparison.

Any More Examples?

Google did give us one fresh example: “How many tablespoons in a cup?” Google said that RankBrain favored different results in Australia versus the United States for that query because the measurements in each country are different, despite the similar names.

I tried to test this by searching at Google.com versus Google Australia. I didn’t see much difference, myself. Even without RankBrain, the results would often be different in this way just because of the “old fashioned” means of favoring pages from known Australian sites for those searchers using Google Australia.

Does RankBrain Really Help?

Despite my two examples above being less than compelling as testimony to the greatness of RankBrain, I really do believe that it probably is making a big impact, as Google is claiming. The company is fairly conservative with what goes into its ranking algorithm. It does small tests all the time. But it only launches big changes when it has a great degree of confidence.

Integrating RankBrain, to the degree that it’s supposedly the third-most important signal, is a huge change. It’s not one that I think Google would do unless it really believed it was helping.

When Did RankBrain Start?

Google told us that there was a gradual rollout of RankBrain in early 2015 and that it’s been fully live and global for a few months now.

What Queries Are Impacted?

Google told Bloomberg that a “very large fraction” of queries are being processed by RankBrain. We asked for a more specific figure but were given the same large fraction statement.

Is RankBrain Always Learning?

All learning that RankBrain does is offline, Google told us. It’s given batches of historical searches and learns to make predictions from these.

Those predictions are tested and if proven good, then the latest version of RankBrain goes live. Then the learn-offline-and-test cycle is repeated.

Does RankBrain Do More Than Query Refinement?

Typically, how a query is refined — be it through stemming, synonyms or now RankBrain — has not been considered a ranking factor or signal.

Signals are typically factors that are tied to content, such as the words on a page, the links pointing at a page, whether a page is on a secure server and so on. They can also be tied to a user, such as where a searcher is located or their search and browsing history.

So when Google talks about RankBrain as the third-most important signal, does it really mean as a ranking signal? Yes. Google reconfirmed to us that there is a component where RankBrain is directly contributing somehow to whether a page ranks.

How exactly? Is there some type of “RankBrain score” that might assess quality? Perhaps, but it seems much more likely that RankBrain is somehow helping Google better classify pages based on the content they contain. RankBrain might be able to better summarize what a page is about than Google’s existing systems have done.

Or not. Google isn’t saying anything other than there’s a ranking component involved.

How Do I Learn More About RankBrain?

Google told us people who want to learn about word “vectors” — the way words and phrases can be mathematically connected — should check out this blog post, which talks about how the system (which wasn’t named RankBrain in the post) learned the concept of capital cities of countries just by scanning news articles:

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There’s a longer research paper this is based on here. You can even play with your own machine learning project using Google’s word2vec tool. In addition, Google has an entire area with its AI and machine learning papers, as does Microsoft.

The post FAQ: All About The New Google RankBrain Algorithm appeared first on Search Engine Land.