Download - Hummingbird Proof eCommerce SEO Planning - #BrightonSEO April 2014

Hummingbird Proof

How Conversational based search is set to shape eCommerce in a post Hummingbird World

eCommerce SEO Planning

@KunleTCampbell

What was Hummingbird all about?

“A Major Change in the Way Google Interprets or Rewrites Long, Complex Search Queries”

@KunleTCampbell


…it was a rewrite of Google’s Entire Search Engine or Algorithm for voice and mobile search …biggest ever since 2000 – Amit Singhal

@KunleTCampbell

“…a new engine built on both existing and new parts, organized in a way to especially serve the search demands of today (from mobiles), rather than ten years ago”


@KunleTCampbell

The Translation of a Search Query

Google Search Timeline

EMD

@KunleTCampbell

What was Hummingbird all about? Precision & Speed of a

Hummingbird

@KunleTCampbell


Precision & Speed

“answer your questions about the world” - Tamar Yehoshua, VP, Search

Answers Queries

Knowledge Graph

Conversational Queries

Voice Search

Anticipate Queries

Google Now follow up

context queries

@KunleTCampbell

Entities Classes

Micro-data

schema.org

Freebase

Object Oriented Approach

metaweb Things

Nodes & Edges (in Facebook) Wikipedia data

Labeled data

Semantic network

Topic modeling

Sets of topics

Resource Description Framework (RDF)

Understanding of THINGS not just STRINGS

Answers Queries

topics

Knowledge Graph

@KunleTCampbell

Remember relational databases?

Understanding ENTITIES and RELATIONSHIP between entities

Knowledge Graph

@KunleTCampbell


Knowledge Graph

@KunleTCampbell


action

Subject Object

has a

ENTITY PROPERTY

Knowledge Graph

@KunleTCampbell

Context of a Query rather than String Match

Information Card

A major change in the way Google Interprets the way we Search

Knowledge Graph

@KunleTCampbell


Information Card

Knowledge Graph

@KunleTCampbell


Knowledge Graph

@KunleTCampbell

Answer Cards

Knowledge Graph

@KunleTCampbell

Is Google not a scraper site?

No…a search engine like Google is ‘an amazing Swiss

Army Knife’ ;)

h#ps://www.youtube.com/watch?v=HViSQjZxhnY

@KunleTCampbell

Knowledge Graph is Not Perfect…

Vs

@KunleTCampbell

Conversational ‘Voice’ Search

“…someday, having to pull out a cell phone from your pocket and search would feel as

archaic as a dial-up modem” - Amit Singhal

– Head of Google’s Core Ranking Team


Voice Search

@KunleTCampbell

Conversational Queries…

Algo rewrite…for conversational search from: mobile devices and wearable tech i.e. ‘google glass’


Voice Search

@KunleTCampbell

Search used to be about using queries that hopefully matched content that was out there…

Conversational Queries…

Search today is also about asking complex questions in a conversational format with the hope of getting a direct answer ?


Voice Search

@KunleTCampbell

Talk to Google…

Siri Google Now Cortana


Voice Search

@KunleTCampbell

Hot-wording Google

“Okay Google”


Voice Search

@KunleTCampbell

Google is also teaching us a new set of commands

Read more: h#p://bit.ly/PQg3zq


Voice Search

@KunleTCampbell

As we learn these commands, Google might better Anticipate our follow up Queries...

Anticipate Queries


context queries

@KunleTCampbell

Query Reviser Re-Writing Engine Based on Identifying ENTITIES and the SYNONYM ENGINE...

Anticipate Queries


context queries

via: h#p://www.seobythesea.com/2013/09/google-‐hummingbird-‐patent/

SYNONYM IDENTIFICATION BASED ON CO-OCCURRING TERMS United States Patent: 8,538,984 Filled on: September 17, 2013 Assignee: Google Inc. (Mountain View, CA) http://1.usa.gov/1i900HL

@KunleTCampbell

The Vast and Ever Expanding Size of Knowledge Graph and the Semantic Web is Constantly Improving Query Re-Writing

Anticipate Queries


context queries

via: h#p://www.seobythesea.com/2013/09/google-‐hummingbird-‐patent/

SEARCH QUERIES IMPROVED BASED ON QUERY SEMANTIC INFORMATION United States Patent: 8,577,907 Filled on: November 5, 2013 Assignee: Google Inc. (Mountain View, CA) http://1.usa.gov/1nosfFP

@KunleTCampbell

Anticipate Queries


context queries

The Vast and Ever Expanding Size of Knowledge Graph and the Semantic Web is Constantly Improving Query Re-Writing

@KunleTCampbell

Advances with Google Now, shows Google’s Ambitious long-term goal

of progressing from a search engine to an ubiquitous artificial-

intelligence answer machine

Anticipate Queries


context queries

@KunleTCampbell

How Should e-Tailers Prepare for the Impending

Change?

@KunleTCampbell

Understand the Context of a Query

@KunleTCampbell

User Data from Query logs

Here’s How Google Attempts to Understand the ‘Layers of Context’ in a Query

Search Entity information – Knowledge Graph has 570 million objects with data on 18 billion+ relationships

Clicks and CTR history on SERPs

Co-occurrences of words within queries and query sessions

Queries and query refinements with a query session

Location and device cues

Was the search via Voice or typed in?

@KunleTCampbell

Here’s How Google Attempts to Understand the ‘Layers of Context’ in a Query

“A search query for a search engine may be improved by incorporating alternate terms into the search query that are semantically similar to terms

of the search query, taking into account information derived from the search query.”

-  U.S. Patent 8,577,907 Abstract Search queries improved based on query semantic information

http://1.usa.gov/1nosfFP

@KunleTCampbell

“the context for a particular query term included at the beginning of the search query may be defined by a query term located at the end of the search query”


SYNONYM IDENTIFICATION BASED ON CO-OCCURRING TERMS United States Patent: 8,538,984 September 17, 2013 Assignee: Google Inc. (Mountain View, CA) http://1.usa.gov/1i900HL

where can I buy a playstation 4

@KunleTCampbell

Mobile OR Desktop? Local business OR on an e-Tailer? Context might be different…


The defining query

where can I buy a playstation 4

@KunleTCampbell

Non local Results from a mobile device

“where can I buy a playstation 4”

eCommerce AND article results

@KunleTCampbell

Query String Match Results from a mobile device

“where can I buy a playstation 4 in oxford”

@KunleTCampbell

Search from a mobile device

“where can I buy coffee”

Prominent Local results

@KunleTCampbell

Search from a desktop on Google.com

“where can I buy coffee”

Prominent Local results

@KunleTCampbell

Strive to become an

ENTITY

@KunleTCampbell

Work on Your Brand Until it Earns the Right to Become a Global ‘Entity’

@KunleTCampbell

Which means striving to ethically earn a Wikipedia Page

@KunleTCampbell

Which Gets You Into Freebase

@KunleTCampbell

Understand the Context

of a Query And an Answer Card…

You also get to become an entity in

your retail niche!

It is not just the preserve of the ‘big boys’

@KunleTCampbell

Don’t GAME Wikipedia

From the Wiki page of a prominent UK and

Global Fashion

@KunleTCampbell

Understand How ENTITY ATTRIBUTES

Influence Rankings

@KunleTCampbell

Don’t Just List your Retail Business on Wikipedia; ensure that it is in the right

category and that it has as many schema attributes are completed

@KunleTCampbell

Complete Schema Profile

@KunleTCampbell

Check Out Amazon’s Freebase

Listing to see how detailed Attributes

can get

Also Check out Google’s Freebase

Listing http://www.freebase.com/m/045c7b

http://www.freebase.com/m/0mgkg

@KunleTCampbell

A UK e-tailer that Deserves a Wikipedia Page

Listed on the AIM

@KunleTCampbell

No Information Card or Knowledge Graph Data…

@KunleTCampbell

Build RELATIONSHIPS

with other ENTITIES

On Freebase

@KunleTCampbell

Added as Supplier’s of ASOS

On Freebase

Added as ASOS as ‘Major Customer’

On Freebase

@KunleTCampbell

Build ENTITIES within your Store with

Marked-Up Data

@KunleTCampbell

Avoid Keyword Cannibalisation

URL Singularity Is Key Especially on Category and Product Pages

Rethink the excessive use of tag pages

What THING does your Category Page Represent? Mark-up Product & Category pages with Schema.org, Microformats, Open Graph

@KunleTCampbell

With Schema.org – Go Over and Beyond mark-up Required by Google

http://schema.org/Product

Also consider the data highlighter

tool to help establish entities

@KunleTCampbell

Establish Connections between ENTITIES with HYPERLINKS

http://schema.org/Product

Ensure URL Singularity to

maximum potential

Internal-link building 101

@KunleTCampbell

Optimise Product and Category Pages for Open Graph and the Social Web

Social Media Markups are

essential

@KunleTCampbell

Multichannel Retailers

should take their Local Presence Seriously

@KunleTCampbell

A UK e-tailer that Deserves a Wikipedia Page

@KunleTCampbell

BUT saved by their Google+ and Google Places Presence…

Most recent Google+ Post

Google Local

Other Local Related Entities

@KunleTCampbell

Multichannel Retailers Tend to have a more competitive edge due to their High Street Local Presence

Contextual Alternatives powered by Local Search

@KunleTCampbell

Be Prepared and Ready for

the Mobile Web

think beyond a Responsive

Website

@KunleTCampbell

If Google Changed its Engine in preparation for voice and mobile search, prepare for the storm ahead by going

mobile

@KunleTCampbell

Check the growth and share of mobile traffic and study your Multi-Device Attribution i.e. with Universal Analytics

+ +

@KunleTCampbell

Google is striving to become an Answers’ Engine – rather than a Search Engine with is gear to cover any and every computing device

+ +

servers, mobile phones, tablet computers, notebook computers, music players, e-book readers, laptop or desktop computers, PDAs, smart phones, or other stationary or portable devices

@KunleTCampbell

Start Optimising

for Questions

both on-site and off-site

@KunleTCampbell

People Ask Search Engines Questions

Infuse your brand in conversations offsite – i.e. reviews, press, video

EARNED MEDIA

@KunleTCampbell

STOP Optimising for STRINGS

and START

Optimising for

THINGS, CONCEPTS & Subjects

@KunleTCampbell

Keyword Research is NOT Dead in the water

RIP

@KunleTCampbell

Infuse Keyword Research into:

CONCEPT RESEARCH

Or SUBJECT MATTER

RESEARCH

@KunleTCampbell

Align On-site Content Marketing with Content that Addresses Pain Points at Each Stage of the Purchase Funnel

A

I

D A

AWARENESS

INTEREST

DESIRE

ACTION

Brand Awareness Efforts: Viral Video, Image, Advertising,

Sponsorship, Social Create Interest: PR, Events,

Guides, Blog, YouTube Video Series, eNewsletter, Q&As

Desire for Your Products: Brand Name Search, Product Search,

Direct Traffic

Action: Buy Product, Voucher Codes

THE AIDA MODEL

@KunleTCampbell

Answer Specific Queries that align with user needs

?

@KunleTCampbell

Go deep…

@KunleTCampbell

Optimize your on-site content for “in-depth articles”

@KunleTCampbell

eBay Goes Quite detailed in their User Guides

@KunleTCampbell

Argos on the other hand is quite thin on for it’s Pools Buying Guide

@KunleTCampbell

Invest in PLA Ads

@KunleTCampbell

Searchers are being trained to interact with Visual Answer Cards….

Yes SEOs, CTRs are Higher…

@KunleTCampbell

Small Screens and PLA ads are swipeable

Mobiles are worse…

J

@KunleTCampbell

Highly Targeted outreach gets Highly Relevant links matter even more now

Continue to do great SEO…

J

@KunleTCampbell

Contact Me to chat more…about eCommerce Marketing

email: [email protected] twitter: @KunleTCampbell web: www.2xmedia.co