At this event, we had the pleasure of having two fantastic presenters.
Elli Bishop, Director of Earned Media at Clearlink and her presentation Outreach from scratch: how to hire the right people to earn the coverage you need.
Bill Slawski, Director of SEO Research ay Go Fish Digital and his presentation Anchor Text, Phrase-Based Indexing and Semantic Topic Modeling
28.
#UTAHDMC
@alisagammon
Purple has been nominated for a Webby Award and
needs your help! Purple is sitting in third place.
Voting closes Thursday, vote now:
http://bit.ly/purplewebby
31. PENNA POWERS, SLC
Senior Digital Media Buyer
‣ Manage paid social, paid search, video, and display
‣ 3+ yrs of digital media planning
‣ Medical, dental, life, 401k w/match, profit sharing, etc
‣ https://pennapowers.com/senior-digital-media-buyer/
#UTAHDMC
32. BIG LEAP, LEHI
Director of Creative Services
‣ Lead and manage team of creative services professionals
‣ 2+ years experience in agency or other fast-paced setting
‣ Tons of benefits
‣ https://bigleap.bamboohr.com/jobs/view.php?id=28
#UTAHDMC
33. PURPLE, ALPINE
‣ Lead the organic marketing division of the acquisition team
‣ 3+ yrs content marketing management experience
‣ Free mattress, 401k w/match, medical insurance, dental, vision,
life, etc
‣ http://tinyurl.com/purplejob
#UTAHDMC
Content Marketing Manager
34. HELIX EDUCATION, SLC
‣ Execute and plan paid search campaigns for higher ed clients
‣ 2-4 yrs experience + Bachelors degree
‣ https://bit.ly/2JaDaSC
#UTAHDMC
Senior Paid Search Specialist
35. BAMBOOHR, LINDON
‣ Manage paid search and paid social channels for BambooHR
‣ 2+ yrs paid search and social
‣ We pay you to go on vacation, health insurance, medical,
dental, video, 401k w/match, etc
‣ https://company.bamboohr.com/jobs/view.php?id=835
#UTAHDMC
Paid Search/Paid Social Specialist
36. EXTRA SPACE STORAGE, SLC
‣ Analyze website structure, optimize for SEO
‣ 3-5+ yrs experience + Bachelor's degree
‣ Medical insurance, dental, 401k w/match, on-site fitness
center, free drinks, etc.
‣ https://careers.extraspace.com/technical-seo-specialist/job/
10784392
#UTAHDMC
Technical SEO Specialist
37. VITALSMARTS, PROVO
‣ Strategy and execution of marketing automation
‣ 3-5yrs exp in B2B demand gen + Bachelor's degree
‣ Award-winning training products for 300 of the Fortune 500
‣ https://careers.twentyeighty.com/job/TWENUS988/Marketing-
Automation-Lead
#UTAHDMC
Marketing Automation Lead
38. UTAHDMC.ORG/JOB-BOARD
PUT YOUR JOB IN FRONT OF OUR AUDIENCE!
‣ EMAILED TO 4500+ CONTACT DATABASE
‣ SHARED ON TWITTER, FACEBOOK AND SLACK
‣ ANNOUNCED AT MONTHLY EVENT
QUESTIONS? EMAIL AJ@UTAHDMC.ORG
#UTAHDMC
40. ELLI BISHOP
OUTREACH FROM SCRATCH: HOW
TO HIRE THE RIGHT PEOPLE TO
EARN THE COVERAGE YOU NEED
DIRECTOR OF EARNED MEDIA
CLEARLINK
SALT LAKE CITY, UT
TONIGHTS 1ST PRESENTER:
#UTAHDMC
41. Outreach
from Scratch
How to Hire the Right People to
Earn the Coverage You Need
@elbell09
#outreachfromscratch
#UtahDMC
42. Elli Bishop
Director of Earned Media, Clearlink
elli.bishop@clearlink.com
slides: Slideshare
@elbell09
#outreachfromscratch
#UtahDMC
127. 87
Measuring
What are the KPIs?
What kind of links do I need?
What does reporting look like?
How do I structure the team?
128. Links
Build links to drive organic traffic growth.
Referral Traffic
Drive referral traffic through content
creation, promotion, and placement.
Primary
Outreach KPIs
129. Secondary
Outreach KPIs
Links on new domains
Links from domains that link
to your competitors
Links from your competitors
Brand mentions
Number of broadcast media
spots
Branded query clicks &
impressions in GSC
191. BILL SLAWSKI
ANCHOR TEXT, PHRASE-BASED
INDEXING AND SEMANTIC TOPIC
MODELING
DIRECTOR OF SEO RESEARCH
GO FISH DIGITAL
SAN DIEGO. CA
TONIGHTS 2ND PRESENTER:
#UTAHDMC
196. @BILL_SLAWSKI
PHRASE-BASED INDEXING RELATED PATENTS
Phrase-Based Searching in an Information Retrieval System (US Patent 9,990,421)
Phrase-Based Detection of Duplicate Documents in an Information Retrieval System (US Patent 9,037,573)
Phrase-Based Personalization of Searches in an Information Retrieval System (US Patent 9,037,573)
Automatic Taxonomy Generation in Search Results Using Phrases (US Patent 7,426,507)
Phrase-Based Generation of Document Descriptions (US Patent 7,584,175)
Index server architecture using tiered and sharded phrase posting lists (US Patent 9,652,483)
Information retrieval system for archiving multiple document versions (US Patent 9,817,886)
Multiple index based information retrieval system (US Patent 9,817,825)
Integrated external related phrase information into a phrase-based indexing information retrieval system (US
Patent 8,631,027)
Detecting spam documents in a phrase based information retrieval system (US Patent 8,078,629)
Phrase identification in an information retrieval system (US Patent 7,580,921)
Query phrasification (US Patent 10,152,535)
Phrase extraction using subphrase scoring (US Patent 9,355,169)
197. @BILL_SLAWSKI
PHRASE-BASED SEARCHING IN AN
INFORMATION RETRIEVAL SYSTEM
Inventor: Anna Lynn Patterson
US Patent Application 20060031195
Published February 9, 2006
Filed July 26, 2004
199. @BILL_SLAWSKI
COMPLETE MEANING PHRASES
THAT PREDICT
Incomplete: “President of the”
Not Meaningful: “Top of the Morning”
Predictive (Whitehouse): “Oval Office” “Rose
Garden” “Secretary Of State” “President of the
United States”
200. @BILL_SLAWSKI
FROM TOP N RANKING PAGES
What meaningful complete phrases co-occur frequently
on the Top N ranking pages for the same meaning of
The term you may want to rank for?
201. @BILL_SLAWSKI
PHRASE INVERTED POSTING LIST
Index server architecture using tiered
and sharded phrase posting lists
Google Knows where the Phrases are on the Web
https://www.slideshare.net/ChaToX/
text-indexing-inverted-indices-56364695/8?src=clipshare
202. @BILL_SLAWSKI
RANKING APPROACHES
How Search algorithms work
The Meaning of a Query – Uses Language
Models to understand meanings, and has
Improved search by 30% Sounds a lot like the
Neural Matching that Danny Sullivan announced
On Twitter.
Meaning
Authority
Context (location, seasonality)
Freshness
203. @BILL_SLAWSKI
ORIGINALLY A RERANKING
APPROACH, BUT…
3. The method of claim 1, wherein a document with a low
frequency of query terms but a plurality of related phrases for the
first phrase ranks higher than a document with a higher
frequency of query terms but with no related phrases.
Phrase-based searching in an information retrieval system
Inventors: Anna L. Patterson
Assignee: Google LLC
US Patent: 9,990,421
Granted: June 5, 2018
Filed: February 2, 2017
205. @BILL_SLAWSKI
PHRASE-BASED INDEXING AND
BODY HITS
The search system 120 provides a ranking stage 604 in
which the documents in the search results are ranked, using
the phrase information in each document's related phrase
bit vector, and the cluster bit vector for the query phrases.
This approach ranks documents according to the phrases
that are contained in the document, or informally “body
hits.”
206. @BILL_SLAWSKI
ANCHOR HITS & EXPERT
DOCUMENTS
Sorting the documents on the outbound score component
makes documents that have many related phrases to the
query as anchor hits, rank most highly, thus representing
these documents as “expert” documents
207. @BILL_SLAWSKI
ANNOTATION TEXT - UPDATED
ANCHOR TEXT PATENT
Anchor tag indexing in a web crawler system
Originally Filed in 2003, Updated in 2019
…identifying, in the source document, annotation text, the annotation text being
text within a predetermined distance of an outbound link to a target document
and the annotation text including at least one term, storing in the index an
association between the term and the source document, storing in the index,
responsive to identifying the annotation text, an association between the term
and the target document, identifying, responsive to receiving a query that
includes the term, the source document and the target document as associated
with the term in the index