Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Tom Anthony — ‘New Paradigms: Five Fundamental ...
Search
Distilled
November 18, 2015
Technology
0
580
Tom Anthony — ‘New Paradigms: Five Fundamental Changes in Search’
Distilled
November 18, 2015
Tweet
Share
More Decks by Distilled
See All by Distilled
Wil Reynolds — Paid Search Strategies SEOs will Love
distilled
0
97
Rand Fishkin — Search Ranking Factors in 2015 What Data, Opinions, and Testing Reveal
distilled
0
160
Larry Kim — The Top 10 Facebook & Twitter Advertising Hacks of All Time
distilled
0
130
Will Critchlow - Practical Tips for the Future of Search II
distilled
0
250
Tom Anthony - New Paradigms: Five Fundamental Changes in Search II
distilled
0
290
Aaron Friedman — ‘Google's Predictable Content Preference’
distilled
0
260
Aleyda Solis — ‘Unlocking Growth Opportunities with Search Analytics’
distilled
0
200
Anum Hussain — ‘Topics Over Keywords: An SEO-Driven Approach to Content Marketing’
distilled
0
260
Casie Gillette — ‘21 Must-Have PR Tools and Tactics’
distilled
0
150
Other Decks in Technology
See All in Technology
オープンソースAIとは何か? --「オープンソースAIの定義 v1.0」詳細解説
shujisado
9
1k
Shopifyアプリ開発における Shopifyの機能活用
sonatard
4
250
Oracle Cloud Infrastructureデータベース・クラウド:各バージョンのサポート期間
oracle4engineer
PRO
28
13k
【Startup CTO of the Year 2024 / Audience Award】アセンド取締役CTO 丹羽健
niwatakeru
0
1.2k
Making your applications cross-environment - OSCG 2024 NA
salaboy
0
190
100 名超が参加した日経グループ横断の競技型 AWS 学習イベント「Nikkei Group AWS GameDay」の紹介/mediajaws202411
nikkei_engineer_recruiting
1
170
第1回 国土交通省 データコンペ参加者向け勉強会③- Snowflake x estie編 -
estie
0
130
EventHub Startup CTO of the year 2024 ピッチ資料
eventhub
0
120
The Role of Developer Relations in AI Product Success.
giftojabu1
1
130
The Rise of LLMOps
asei
7
1.6k
TypeScriptの次なる大進化なるか!? 条件型を返り値とする関数の型推論
uhyo
2
1.7k
なぜ今 AI Agent なのか _近藤憲児
kenjikondobai
4
1.4k
Featured
See All Featured
5 minutes of I Can Smell Your CMS
philhawksworth
202
19k
ReactJS: Keep Simple. Everything can be a component!
pedronauck
665
120k
What's new in Ruby 2.0
geeforr
343
31k
What's in a price? How to price your products and services
michaelherold
243
12k
How to Think Like a Performance Engineer
csswizardry
20
1.1k
Automating Front-end Workflow
addyosmani
1366
200k
Designing for Performance
lara
604
68k
個人開発の失敗を避けるイケてる考え方 / tips for indie hackers
panda_program
93
16k
Building Applications with DynamoDB
mza
90
6.1k
4 Signs Your Business is Dying
shpigford
180
21k
ピンチをチャンスに:未来をつくるプロダクトロードマップ #pmconf2020
aki_iinuma
109
49k
The MySQL Ecosystem @ GitHub 2015
samlambert
250
12k
Transcript
FIVE EMERGING TRENDS IN ONLINE SEARCH Tom Anthony SearchLove London
2015
None
5 TRENDS
COMPOUND QUERIES IMPLICIT SIGNALS PERSONAL ASSISTANTS 1 2 5 WEB
SEARCH TO DATA SEARCH 4 KEYWORDS VS INTENTS 3
1 IMPLICIT QUERY SIGNALS 1
search query “london tube stations”
explicit aspect of query implicit aspect of query iPhone user,
on street in London “london tube stations”
TIME TOTAL SIGNAL INFORMATION explicit signal implicit signal
Device Location Browser Social Connections Time of Day Search History
Language
• NBED - WEARABLES IMPLICIT SIGNALS: WEARABLES
IMPLICIT SIGNALS: MODE OF TRANSPORT
• NBED - PHYSICAL WEB IMPLICIT SIGNALS: HYPER-LOCAL (BEACONS)
Mockup: Jack Morgan IMPLICIT SIGNALS: READING SIGNS
TIME TOTAL SIGNAL INFORMATION explicit signal implicit signal
My vision when we started Google 15 years ago was
that eventually you wouldn't have to have a search query at all. SERGEY BRIN GOOGLE
FACT Explosion of implicit signals is leading to more complex
queries and more granular results. QUESTION Which implicit signals could impact searchers trying to find your clients?
COMPOUND QUERIES IMPLICIT SIGNALS PERSONAL ASSISTANTS 1 2 5 WEB
SEARCH TO DATA SEARCH 4 KEYWORDS VS INTENTS 3
COMPOUND QUERIES 2
Query Algorithm Response Revised Query Algorithm Response A SEARCH QUERY
Query Algorithm Response Revised Query Algorithm Response OLD MODEL: INDEPENDENT
QUERIES
HUMMINGBIRD Credit: mikebaird on Flickr
brought to you by… https:/ /youtu.be/JfJOFvKDNu4
brought to you by… https:/ /youtu.be/X8K2ccNBZYU
NEW MODEL: DEPENDENT QUERIES Query Algorithm Response Additional Input Algorithm
Revised Response
None
https:/ /youtu.be/M1ONXea0mXg
https:/ /youtu.be/M1ONXea0mXg
COMPOUND QUERIES ARE LIKE FACETED SEARCH
FACT Queries are no longer single expressions of intent followed
by static responses. QUESTION What compound queries might your visitors be trying?
COMPOUND QUERIES IMPLICIT SIGNALS PERSONAL ASSISTANTS 1 2 5 WEB
SEARCH TO DATA SEARCH 4 KEYWORDS VS INTENTS 3
KEYWORD FOCUS TO INTENT FOCUS 3
Example from: Rand Fishkin, Moz KEYWORDS & INTENTS
Source: /u/UpboatOarKnotUpboat SEARCH HISTORY OF A 5 YEAR OLD
KEYWORDS INTENT
KEYWORDS INTENT IMPLICIT SIGNALS COMPOUND QUERIES
brought to you by… https:/ /youtu.be/Cv_EzsI7x34
CONTEXTUAL SEARCHES http:/ /selnd.com/1MnLlF8
FACT Intent is not just ‘better keywords’; it is determined
from implicit signals and across multiple queries. QUESTION Do you know which landing pages serve which intents on your site?
COMPOUND QUERIES IMPLICIT SIGNALS PERSONAL ASSISTANTS 1 2 5 WEB
SEARCH TO DATA SEARCH 4 KEYWORDS VS INTENTS 3
WEB SEARCH TO DATA DRIVEN SEARCH 4
SHIFT AWAY FROM ‘WEB SEARCH’: ENTITIES
SHIFT AWAY FROM ‘WEB SEARCH’: DIRECT ANSWERS
SHIFT AWAY FROM ‘WEB SEARCH’: GOOGLE NOW
FROM WEB TO APP INDEXING & DEEP LINKS
WHERE ARE WE HEADED? ?
CROSS DEVICE TASKS & SEARCHES source: http:/ /services.google.com/fh/files/misc/multiscreenworld_final.pdf (thanks, Dr
Pete)
CROSS DEVICE: APPLE HANDOFF
CROSS DEVICE: SHARED SCREENS
DIRECT ANSWERS & CARDS
CARDS: UNITS OF DATA
CARDS: ADAPT EASILY CROSS DEVICE dicddic
CARDS: NEW MOBILE INTERFACE
CARDS: DATA SOURCES Knowledge Graph Data Partnerships Everything Else ?
CARDS: DATA SOURCES Knowledge Graph Data Partnerships Everything Else YOU!
DIRECT ANSWERS: FEATURED SNIPPETS
FACETED SEARCH 2.0: CROSS DEVICE CARDS?
FACT Direct answers and cross device search are driving us
towards a ‘data driven’ model where cards are key. QUESTIONS Is your data accessible to Google? Why should Google choose you as a data source?
COMPOUND QUERIES IMPLICIT SIGNALS PERSONAL ASSISTANTS 1 2 5 WEB
SEARCH TO DATA SEARCH 4 KEYWORDS VS INTENTS 3
PERSONAL ASSISTANTS 5
GOOGLE’S MISSION
‘PERSONAL INDEX’: PHOTOS
‘PERSONAL INDEX’: CALENDAR
‘PERSONAL INDEX’: DEVICES
‘PERSONAL INDEX’: EMAILS
EMAIL STRUCTURED MARKUP
A single interface for all searches.
NOT JUST GOOGLE
MICROSOFT CORTANA
PROACTIVE SIRI
FACEBOOK ‘M’
HOUND
We are in a Post-PageRank world.
FACT We will increasingly search both personal and public indexes
via a single interface. QUESTION How can we prepare to be the most useful source from a personal assistant app’s perspective?
TAKEAWAYS
COMPOUND QUERIES IMPLICIT SIGNALS PERSONAL ASSISTANTS 1 2 5 WEB
SEARCH TO DATA SEARCH 4 KEYWORDS VS INTENTS 3
Intent is more than just ‘keywords done better’; consider the
implicit signals and compound queries. Data Driven Search is coming; start considering what steps to take to prepare. The rise of ‘Personal Assistants’ is an opportunity; optimise on another axis (that isn’t PageRank based). 1 2 3
None
THANKS @TomAnthonySEO