Google has unveiled several updates to its search to mark the company’s 15th year anniversary.

Most prominent among the new features is Google’s new search algorithm called “Hummingbird.” It is designed to sort through all the information it has when you search and come back with answers returning better results. In general, Hummingbird Google says — “is a new engine built on both existing and new parts, organized in a way to especially serve the search demands of today, rather than one created for the needs of ten years ago, with the technologies back then.”

What type of “new” search activity does Hummingbird help? ‘Conversational Search’ is one of the biggest examples Google gave. People, when speaking searches, may find it more useful to have a conversation. 

For example: “What’s the closest place to buy an apple computer near my home?” A traditional search engine might focus on finding matches for words — finding a page that says “buy” and “apple compute”.  Hummingbird might focus on the meaning behind the words. It might understand that the word “place” means you want a brick-and-mortar store. It might know that “apple computer” is a particular type of computer carried only by certain stores. Knowing all these meanings may help Google go beyond only finding pages with words that match. The whole sentence or meaning — is taken into account. The end goal is to find the pages that correspond to the meaning in its entirety.

Google has been doing conversational search, but it had only been doing it really within its Knowledge Graph answers. Hummingbird is designed to apply the meaning technology to billions of pages from across the web, in addition to Knowledge Graph facts, which may yield better results.

The new algorithm doesn’t mean page rank or SEO is dead. Page rank is one of over 200 major factors that figure into the Hummingbird mix. Guidance remains the same, it says: “have original, high-quality content.”  Signals that have been important in the past remain important. Hummingbird just allows Google to process them in new and hopefully better ways.

Hummingbird was implemented about a month ago, but Google announced the change late last week.


You’ve just finished writing an article and can’t wait to publish it.  You really want to share what you have written. Should you publish your blog right away or should you wait for a specific time? Blogs can help you increase traffic for your business and time spent on your site. But will publishing at any time help you capitalize on this? There has been lots of research and comments on when blogs will generate the most traffic. So what is the best time to publish your blog or send out newsletters?

There are studies that show audiences are much more likely to read and comment on blogs at different points depending on the time and day of the week. KISSmetrics, with data collected by social media scientist Dan Zarella and Search Engine Land, says posting content during high traffic hours (day time) can lead to more visitors, comments and engagement but it’s more likely your post will be buried in the competition with other articles. When posting during low activity times (night time) you can expect more prominence within user feeds with less noise, but fewer visitors during off hours. The data also shows that most users read blogs throughout the day, with the highest percentage in the morning between 8am to 11am (peak blog views by hour). The average blog gets the most traffic on Monday but more comments on a Saturday when people aren’t generally working.

They also found: A higher percentage of men than women read blogs in the evening and at night. The average blog receives the most inbound links on Monday and Thursday.
The average blog receives most inbound links at 7am Eastern Time.

Data from Shareaholic study shows that posting between 9am to 10am increases the likelihood of both more page views and social shares.

Of course, don’t forget to take into consideration your own unique business and business sector.  It is important that you analyze your site traffic to determine what the best schedule for you is. Certain times might work best for some businesses and not others.  In order to capitalize on the benefits of blogging, use these studies as a starting point.  Combine them with your own analytics to capture the full potential of your audience!


Graph databases are gaining in popularity. Recently several of the major social media sites have introduced and been talking about graph search.  Google, Facebook and Twitter all are using graphs.  But graphs need not be just for the internet big wigs.  Commercial sites might consider them as well.

Unlike the more commonly used relational databases – Graph databases let you represent related data as it inherently is: as a set of objects connected by a set of relationships, each with its own set of descriptive properties. With a graph database the data stored in the database directly parallels the whiteboard representation. The developer can start coding immediately. Relational databases need to carry out a number of steps to determine whether and how things are connected, and then to retrieve related data records. Graph databases make the connection between relationships appear naturally.

Graph databases can provide an opportunity in many enterprise spaces.  It could be used by a company to help employees search the company’s social network to find their colleagues who have worked on specific projects. This would save them the time of having to go through databases manually and piece information together themselves. It might also be used to help sales teams identify connections to a prospective client. It can be used in geographic search to find points of interests and connect those interests with your social network. Graph Search is about giving users the ability to combine intent, social context and custom audiences.

Graph databases allow the database to naturally keep up with one’s business as it grows. Response times slow down as a relational database grows in volume, which causes problems as a business grows. However with a graph database, traversal speed remains constant, not depending on the total amount of data stored.

Traditional databases aren’t going away, but the development world is seeing an increasing number of applications where graph databases are being used. Relational databases are great when it comes to relatively static and predictable tabular data. Graph databases are being used to accelerate development and massively speed up performance. This is something any organization can benefit from.

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