Google Seo Sandwitch Blog

Wednesday, April 23, 2014

Increasing Relevance of Co-Citations and Co-Occurrence

The SEO industry constantly tries to predict the way Google works. Apart from Black Hat SEO's who try to find loopholes into the actual algorithm system, genuine SEO's try and understand the reason behind why a specific website ranks higher than another one and instead of trying to manipulate the search results, they follow the Google's guidelines and plan their strategies in order to help the user.

Two of the biggest ranking factors that have been debated from a long time without any actual proof are Co-Occurence and Co-Citations. Backlinks as we all know are dominated by the presence of relevant anchor text which is open to spam. On the other hand, metrics like Co-Citations and Co-Occurrence are harder to manipulate. But, will they return accurate search results if implemented properly is still unkown.

This is the reason, Google still relies heavily on anchor text and backlinks. But, certainly these metrics are set to play a greater role in future and we cannot say either that they are completely ignored by Google.

Let us now understand, the meaning of these 2 terms.

Co-Citation Meaning with Example

Co-Citation- In short, these are your neighbourhood links.

You must have seen those references while reading any Wikipedia article on the web. These are nothing but Co-Citations, relationship between 2 documents.

Have a look at the example below:

In this example, the 11 resources cited by Wikipedia are all related to the topic "Co-Citation". Hence, this metric decides your neighbourhood links or your company. Now, its upto you to decide whether you wish to be cited in a relevant company or a spammy company.

Some webmasters tend to buy links from irrelevant sites that cites different sources together which bear no similarity to each other.

Considering a site linking to "buy inkjet printer" along with a link to "play online casino". These links cited by the source do not share a common similarity and thus play a devastating role in making Google believe that your site is spammy. Hence, the site providing the link and the site getting the link, all need to be careful in order to get a high relationship score.

Co-Occurrence Meaning with Example

Co-Occurrence- In short, these are brand or product name mentions in relation to a keyword.

Suppose, my name is often associated with my blog's name This means that Joydeep Bhattacharya (my name) has a high relationship score with the keyword "seosandwitch". This is what co-occurrence does.

Google Semantic Search Algorithm and The Role of Co-Citations and Co-Occurrence

The hummingbird algorithm started a fresh new beginning for Google which started to return answers instead of web references. This algorithm was based on searcher's intent and not keywords. Semantic search analysis involved understanding the intent of the user before presenting the search results. The metrics Co-Citations and Co-Occurrence play an exciting role here. Google can easily determine the relationship between Barack Obama and America using Co-Occurrence metric. This is what semantic analysis does.

Please note that there is still no proof that Google is using these factors in its main algorithm but they must certainly be given a second thought.

Also See:

Deeper Understanding of Knowledge Graph
How Does Google Applies Semantic Search?
Latent Semantic Indexing
Facebook Graph Search Optimization
Universal Analytics
Learn Seo Step by Step
Hard Time Ahead for Black Hat Seo's
Seo Factors That Have the Biggest Impact on Rankings
Utilizing Tf-Idf Score to Increase Site Rankings
Why Brand Matters in Seo
How to Clean Your Link Profile?

Monday, April 21, 2014

6 Tricks You Never Thought Was Possible With Google Plus

Here are some awesome tricks that you can do with Google Plus.

1- Create Ripples for Your Post

Ripples do not happen for every post but instead they happen for posts that attain a decent level of publicity through reshares. Suppose if your post gets shared and then reshared by several people then that post will create what is known as Ripples. A post that generates Ripples is of a high quality and generally receives much visibility.

2- Animated Gif's As Your Profile Pic

Love animation? You can use a moving image as your profile pic to grab more eyeballs.

3- Search Pictures Using the Advanced Search Feature

Yes, you can easily search pictures shared on your Google Plus profiles by using the advanced search feature.

4- Send a Private Post to Anyone

You can share your post privately to any one just by entering the email address of that person even if the person is not a member of Google Plus. By default all the shares are done public but you may choose your own private sharing options as per your needs. Make sure to diable reshare of the post.

5-Take Backup of Your Pictures with 5 GB FREE Space

Google Plus offers a 5 GB FREE space to keep all your pictures on Google Plus (a threat to Flickr and Pinterest). You can upload your favorite pictures using any mobile devices. It's really easy dude.

6- Use a Vanity URL for Your Own profile

Google Plus allows you to create a vanity URL for your own profile. Instead of displaying unmeaningful text and numbers, you may allow Googlle Plus to display your name as your profile URL.

Also See:

Sunday, April 20, 2014

Biggest SEO Myths Debunked by Matt Cutts

There are several SEO myths that are a talked about topic among the seo industry. Some of the biggest seo industry myths are highlighted in this exciting webmasters video with Google web spam team head, Matt Cutts.

Myth 1: Buying Ads Can Increase Your Organic Rankings or The Opposite is True?

Explanation: Both are false. Buying ads or not buying them do not play any role in increasing the organic rankings of any website. Google always wants to present the best search results to the users so that they keep coming back. All the changes that Google makes towards its algorithm or the SERP presentation is related to this mental model only.

Myth 2: Building Backlinks (by way of articles, guest blogging, link wheels etc.) Simply By Believing a Group of People is a Bad Idea

Explanation: Building backlinks by way of article syndication, guest blogging or link wheels is not a good idea for the longer run. Many people use automated link building softwares which are not that efficient and must not be considered as a white hat seo method. Many people say they made a lot of money using these methods but the fact is if somebody makes money using any particular method then they won't share the idea with everyone.

Also See:

5 Ways to Boost SEO by Leveraging Google Brandvantage
ASO Guide With Tools
SEO Secrets
51 Secrets of Google
New Google Ranking Factors
Using  Google Plus Ones for Seo
3 Seo Tactics that Can Work Instantly!
50+ Seo Tips
Rich Snippets in Google
How to Add Ratings and Review Stars on Google Search Results

Friday, April 18, 2014

The Challenges Facing the World of Big Data

It seems like everyone is talking about big data these days. With businesses of all sizes starting to turn to the world of big data for information and guidance, even utilizing it to pick out future trends in their business, the onus is on businesses of all sizes to start getting ready for big data, or risk losing out on a competitive advantage.

So just what is so important about big data? What challenges do businesses face in implementing it? And how can they face those challenges to not only make themselves ready for big data, but make the most of it too?

Image Credit: Forbes

Big Data Has Big Benefits

The first question most businesses want answered is simply, what is big data? There's an adage that anything you can't handle using an Excel spreadsheet counts as big data, and there is certainly some truth to that.
Big data is data in huge quantities, gleaned from all kinds of sources, including:

Website metrics;
·     Social media;
·     Data from CRM systems;
·     Emails;
·     Payment history.
And much more….

There are many sources of big data and at first glance it can seem like a lot of noise that's not really worth the hassle.

So what's the big deal about big data?

The big deal is that big data can be used to give any company a competitive edge. By trawling the information and mining what is useful, a business can gain insights into the likes, behavior and characteristics of its customers.

This can then be used to do more of what works and fix what doesn't, giving businesses a chance to streamline their services. 

Take for example a company who wants to figure out which of their Facebook posts are performing best. Using big data - in this case information gathered from their Facebook account - they could analyze their content to get useful answers.

For example:
  • ·         Which kind of posts perform best: Offers? Pictures? Humor? Useful Tips?
  • ·         Which posts were more likely to lead to a sale or further dealings with the customer?
  • ·         Is there a particular time or day when posts perform best?
  • ·         Who is clicking on the posts? What can the business learn about their customers?

When it comes down to it, big data contains within it a wealth of useful information that can not only look deeper at customer behavior and business performance, but show up possible future trends too.
The difficulty for many businesses is how to overcome the challenges and implement big data.

Big Data Challenge #1: Skills

The first challenge facing companies who want to use big data is a lack of skills among their current team.
Big data involves a big learning curve - from learning the technology needed to process it to analyzing it and sorting the wheat from the chaff.

For businesses that need to start combatingbig data skills concerns, training is key.Businesses may well find they can draw the skills they need from their existing team without the need to employ a data specialist. Whether in-house or through an external provider, good training can help the whole team make sense of big data, and their place in their employer's big data plan.

Big Data Challenge #2: Planning

Talking of planning, figuring out what to do and how to do it is one of the biggest big data challenges facing businesses today.With so much data available it can be all too easy to rush in and start gathering data without much of an idea what it's all for. Now that really is like looking for a needle in a haystack.

To combat the tendency to gather it all and then find an unwieldy and disparate set of figures facing them at the end, businesses need a good plan.This needs to clearly answer the question: What data are we collecting and why? The data needed to increase sales to a specific segment will differ from the data needed to predict interest in an upcoming product, for example. Knowing the destination makes it easier to draw up a plan and avoid unnecessary diversions.

Big Data Challenge #3: Collection

If big data is fairly new in a business, getting it collected can be a hurdle. That's why planning matters - businesses need to lay out clearly what is to be collected, and who will collect it how, from where, and when. Getting good quality data should come as standard at this stage - low quality data now can lead to low quality results down the road.Along with collection comes the question of storage.The options for collection and storage vary and setting aside time to research options and figure out which are the best fit for the businesses current big data needs and future big data plans is key to success.

Big Data Challenge #4: Analysis

All the big data in the world won't help a business to grow or be worth the time spent on it if the analysis isn't smart, clear and very usable.As well as needing the technology to analyze it (more on that in a moment), skills also come back into play here.Whether a business hires a data expert or draws from their existing talent pool, the capability to analyze the data and get clear, true results are vital.

Big Data Challenge #5: Technology

One of the biggest worries for businesses adopting big data is the learning curve associated with the technology.One of the most common choices is Apache Hadoop, an open source software designed to handle large data sets. There are other options - IBM's InfoSphere is designed for real-time processing, and Twitter has even gotten into big data with its Storm application.

Investing in big data can have a big payoff, but for those not able to take that step yet, it's perfectly acceptable to start smaller with existing technology so long as there is a real and workable plan to go bigger.
As with any new technology, the key really is training and allowing enough time to learn new skills, along with clear motivation about why this matter, to the company as a whole and the trainees personally.

Getting ready for big data can seem like a daunting task, but it's one that businesses must nevertheless face if they want to stay competitive in their field. The keys to big data success are planning, a clear aim, and enough time for training. The results are well worth it. 

Also See: