Hummingbird Unleashed Sugges&ng  a  new  SEO  methodology  

Gianluca Fiorelli - @gfiorelli1

Global  Associate  

Hummingbird is a complete rewrite of our

search system

It’s not me saying it, it’s this guy

Before talking about

we should talk about

and

Caffeine   Panda   Penguin  

Because a logic in the Google Updates sequence exists

The mobile revolution forced us to change how

we think

Mobile may overtake desktop for Google

searches within a year

(SMXW 2014)

It’s not me saying it, it’s this guy

Do you remember when Google what showing us “searches similar to…” in

the SERPs?

Usually it was for queries like:

“The best way of cooking a pizza with antichokes in a

electric oven”

(Long) Long Tails Verbose Queries

(Long) Long Tails Verbose Queries

Hummingbird =/

Humminguin

How Hummingbird (possibly) works

To take synonyms and Knowledge Graph and

other things

It’s not me saying it, it’s (again) this guy

SYNONYMS

Google is dealing with them since a

long time

Read  this  post  by  Vanessa  Fox  on  Search  Engine  Land:  hDp://itseo.org/OEJCDG    

Keyphrases don’t need to be in their original form. We

do a lot of synonym work, so we can find good pages

that don’t happen to use the same

words a the user typed (Matt Cutts)

The issue is that a word can be a synonym or not depending on the

Context

Coche Automóvil Carro

That Contest was the problem was clear since the beginning, as we can understand reading this patent by Amit Singhal: http://itseo.org/1gPt32l

The issue is that a word can be a synonym or not depending on the

Context

Hummingbird is how Google solves the Contest issue,

thanks to Search Entities and Semantics

Search Entities: http://itseo.org/1fwbfoL

Search Entities

•  A query a searcher submits; •  The documents responsive to the query; •  The search session during which the searcher submits the query; •  The time at which the query is submitted; •  Advertisements presented in response to the query; •  Anchor text in a link in a document; •  The domain associated with a document.

Suggested read: this post by Bill Slawski

Words =/ Things

Words = Verbal Representation of Things

Google transforms Words into Concepts thanks to Search Entities

And Concepts can be disambiguated over the base of their Context

This is what Google already started to do with Knowledge Graph

BEWARE! SEMANTIC SEO =/ SCHEMA.ORG

Schema.org is instrumental to Semantic, it’s not SEMANTIC

OTHERS THINGS… I suspect that the third factor are co-

occurrences

Consequences

Google understands better the queries and their

intentions

Google may expand the number of documents that respond significantly to a

query

If verbose query A = simplier query C and

If verbose query B = simplier query C and similar to verbose query A

then I’ll show just the SERPs answering to query C

Tl;dr: Simpyfing the queries,

Google also reduces the number of unnecessary

SERPs

And that’s good also in term of Adwords…

What about links? Won’t they be an

essential factor anymore?

Links are clearly an important signal about the

importance of your content. They’re still very

valuable

It’s not me saying it, it’s (again!) this guy

From theory to practice. For a new model of SEO

Mario has a small pizzerias’ chain in NYC

He has only a very small difficulty

The old way (not considering Local Search)

1) Pizzeria Tribeca; 2) Best pizzeria in NoLiTa; 3) Calzone Theater District; 4) Pizza Special Chelsea; 5) Where to eat the best pizza in Manhattan 6) etc etc

#FAIL

(not provided)

#FAIL

Penguin (monster)

#FAIL

Bounce Rate (tons of it)

#FAIL

Hummingbird (killing the long tail)

Il Nuovo Metodo

We identify the Entities related to our niche and how they are connected

We match them with our Audience interests

We creat Content Architecture based on Content Hub using Ontology

We conducts a Keywords Research and Mapping with Entities in mind

Entities identification

Freebase APIs: http://itseo.org/1h3RgOS

Entities identification

Yahoo Glimmer: http://glimmer.research.yahoo.com/

Entities identification

Bottlenose: http://bottlenose.com/

Entities identification

RelFinder: http://www.visualdataweb.org/relfinder.php

Audience Matching

Read this: http://itseo.org/1gYLi5q

Audience Matching (audience personas)

Followerwonk first

Audience Matching (audience personas)

And after we use Tribalytics: http://tribalytics.com/

Ontology & Taxonomy

Read twice this deck by Abby Covert: http://itseo.org/1oHVWjt

Ontology & Taxonomy (based on Entities Search and Audience Matching

Pizza

Thin

Thick Regular crust

Organic

Rossa Bianca Napoletana Romana

Content Hub Creation

Home

Tribeca

Our Stories

From the oven

People of Tribeca

Why we love Tribeca

SOCIAL

From Content Strategy to Content Marketing

Recipes > Schema.org > Rich Snippets Recipes > Video Marketing > VideoObject > Rich

Snippets Infografics – Data Visualization – Charts (passive link

building opportunities)

Guides > Long Form > Authorship > In-Depth Articles UGC Q&A

Protip – Newsjacking & Unconventional Marketing as a Plus

Keyword Research based on Entities

Much more ideas in this post by Dan Shure: http://itseo.org/1h479od

And if someone tells you that SEO is dead…