Five SEO stratagies . . .

No recipe exists for creating a search engine optimization (SEO) strategy that will perfectly suit everyone's business. However, most recipes will feature similar ingredients. So, take the best elements of the various recipes and come up with the best plan for your own customers' taste and liking.

An infographic by GoBeyond SEO provides one type of plan for developing an SEO strategy. It features seven steps.

The first step is to begin with the end in mind. Ask yourself the purpose for your SEO. You won't know whether your SEO goals are achieved if you don't even know what they are.



Next, be sure to use keywords that your customers type when they search for what your company provides or for how they refer to your company. Take time to research the topics that your customers and would-be clients are discussing.

The third step is to bake in the on-page SEO. Use the aforementioned keywords in your titles, subtitles, captions, copy... all in a natural, flowing content. Then create that awesome content.

Once you've created fantastic content that's rich with SEO, make sure to share what you've created. Don't forget to make it easy for your customers to share the content as well; provide social sharing buttons whenever possible.

The sixth step is to make sure you get permission from your clients to contact them again. For example, consider creating an email auto-responder series. Build your relationships with clients.

Last, get links the smart way.

Need another recipe for creating SEO strategies? The second infographic, by Act-On, provides additional tips, such as getting quality links, setting a canonical URL, and creating a site with a responsive design.

SEO for birds- Hummingbirds !!!!

I was moderating a roundtable session at SES Chicago last week when the conversation turned to Hummingbird and how – according to the young lady I spoke to – it effectively means "Google is simplifying the query from long tail to shorter terms."
I've heard this point of view a few times over the past few weeks, and fundamentally disagree.
To (hopefully) put a different lens on the simplification argument, I'm laying out a few concepts for discussion. "Simple Queryists" please feel free to slice, dice, dissect, and discuss below.

Do a search for [Where can I buy a Larry Bird shirt]. Simple Queryists think that Google will shorten the query to something like "Buy Larry Bird Shirt" and match a result accordingly.
I don't believe this is what's happening. Rather, Hummingbird is adding a layer of understanding to the query that acts more like an expansion of the query, so that its meaning is clearer.
In this example, I'm thinking Google would interpret the query as the following:

Where (Place: User is located) can I buy (Intent: Purchase) a Larry Bird (Person: basketball player) shirt (Product: [via Association of Product to Player to Team] Boston Celtics shirt #33)

Not exactly shorter.
Let's break that down a little further, most importantly to see the implied connection between person and product.
With better meaning and context of understanding, I believe Google is connecting, via their Knowledge Graph, Larry Bird the basketball player with the context of the team he's most famous for, and the product that matches the shirt number he wore. The query is then more exact, and should return a more exact and relevant result. By using prior search data along with "big data," – other user behavior factors – the new more intelligent algorithm can predict the best match of content to a user's intent.
And that's a fundamental difference. Intelligence through experience and predictability is applied to improve results. And, if it's not exactly a match, real-time user behavior – clicks, query modification, dwell time and page interactions – can help finesse future results.

Google's Hummingbird Algorithm Ten Years Ago

Added 2013-11-10 – Google was granted a continuation version of this same patent (Search queries improved based on query semantic information) on November 5th, 2013, where the claims section has been completely re-written in some interesting ways. It describes using a substitute term for one of the original terms in the query, and using an inverse document frequency count to see how many times that substitute term appears in the result set for the modified version of the query and for the original version of the query. The timing of this update of the patent is interesting. The link below points to the old version of the patent, so if you want you can compare the claims sections.

Back in September, Google announced that they had started using an algorithm that rewrites queries submitted by searchers which they had given the code name “Hummingbird.” At the time, I was writing a blog post about a patent from Google that seemed like it might be very related to the update because the focus was upon re-writing long and complex queries, while paying more attention to all the words within those queries. I called the post, The Google Hummingbird Patent because the patent seemed to be such a good match.

Google has been granted a number of patents about query re-writing, sometimes also referred to as query expansion or query broadening, which try to make it more likely that the search engines will return results closer to what a searcher is looking for, even if they might not necessarily use the best choice of keywords to find the information that will fill their needs. I had also recently written about some other patents describing how Google might re-write queries and it seemed like they were putting together a framework that involved looking at search interactions to better understand probabilities for ranking pages.

Knowing that Google had been working upon patents involving re-writing queries for a number of years, I took this statement as a challenge. Could I find a patent that looks like it describes how Hummingbird might work filed around a decade ago? I searched around, and there was one that was co-invented by Google’s Head of Search Quality, who was involved in making the recent Hummingbird announcement, Amit Singhal. While the technology described in the patent was very similar, it definitely is simpler, and doesn’t seem to focus as much on the need that mobile searches might have for responding to conversational spoken searches. Instead, it tells us:

Interestingly, this older patent may have been filed back in 2003, but it wasn’t granted until 2011. The patent is:

Search queries improved based on query semantic information
Invented by Amit Singhal, Mehran Sahami, John Lamping, Marcin Kaszkiel, and Monika H. Henzinger
Assigned to Google
US Patent 8,055,669
Granted November 8, 2011
Filed: March 3, 2003