This document contains the transcript of a presentation about incorporating machine learning into internal linking audits. The presentation discusses analyzing a website's internal link structure using machine learning techniques like topic modeling and fuzzy matching to identify opportunities for new or improved internal links. It provides a 6-step process for discovery, analysis, clustering content by topic, identifying link opportunities, prioritizing where to link, and measuring the impact of implemented links. The goal is incremental improvements to internal linking that can boost SEO over time through better content organization and discoverability.

1. @lazarinastoy|#brightonSEO

2. @lazarinastoy|#brightonSEO
(THANKYOUFORBEINGHERE).
(ifyouneed a transcriptofthevideorecordingofmytalk,clickhere)
Hello.

3. @lazarinastoy|#brightonSEO
Because
ofthe
natureof
mytalk...

4. @lazarinastoy|#brightonSEO

5. @lazarinastoy|#brightonSEO
I am…
✅ SEO & Data Science Manager
@ Intrepid Digital
✅ Content-creator
✅ Growth & efficiency-obsessed

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I amNOT…
❌ A developer
❌ A machine learning expert
❌ An ‘expert’
❌ A ‘guru’

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INthepast2yearsI’veworked
agency-side
(with a bitofFreelanceontheside)

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Thegoal

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Thechallenge

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Theopportunity

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No
end-to-end,custom-built,ground-breaking,
newtechnologies
today…

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Only a
testedclaim
and
simplepromise:

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ML-enabled
Incrementalimprovements
canhave a
compoundingeffect
onyourSEOIMpact

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Injust20minutes…
WHY ANALYZE
DISCOVER LINK
CLUSTER
DELIVER
01 02 03
04 05 06

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Why
01

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Let’slook at(RELEVANT) Algorithmhistory

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Pagerank
Google’s first
algorithm relied
(mostly) on links,
quality and quantity.

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Rankbrain
Focus on
intent-driven
structure and topic
comprehension.
Things over strings.

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MUM
Surfacing subtopics,
semantic relationships,
multi-modal
comprehension

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Links arestill
crucialfor
discovery
(but…)

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Contentisking.

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Withoutgoodcontent,
Contextbecomes
meaningless.

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Ifthequalityisthere,
contextbecomesthe
vessel
topushthecontent
forward.

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Relevantin2022?
48mentionsof
internallinks.
17forbacklinks.

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It’swhatyoucancontrol

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Ofinlink
opportunities
82
% Aremissed

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Establishtopic
authority
BoostMoney-making
pages
Enrichsearch
intent
Buildsubtopic
relationships
AnInternallinkingstrategyshould aimto:

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AndWhodoesn’tneed

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USER
Engagement
keywords
ranked
Traffic,
CTR
Navigation
&UX
Better
structure
Improved
indexing

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Howto ANALYZe
02

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Whatshould
aninternal
link audit
assess?

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description
LinkFrequency
● # inlinks / # unique inlinks
per page
● Orphaned pages
Crawling
Pagediscovery
LinkQuality
● Link placement
● Source traffic
● Added link sections
Engagement
comprehension
Anchortext ● Type
● Length
Engagement
comprehension
Hierarchy
● Top pages
● Presence of topics, tags or
categories
● Crawl depth
Engagement&ux
Crawling
mistakes
● Broken links
● Nofollow tags
● UTM parameters
Crawling
Indexing
traffic

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Mostofthiscanbe
identifiedwith a
Quickcrawl&
cleverdata studio
template

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Buttoreallydigdeepyoucan
incorporatemachinelearning
tohelpyou

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Classify

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Identify

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assess

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More
insights

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Better
recommendations

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See your content and Links
the way search engines see it
to understand how to improve it.

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cluster
03

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Contentclusters

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TopicModels

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OLDway Newway
Thefundamentals arethesame

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Howdid come about?

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Accordingtothe author
ofthefirsttopicmodeling algorithm

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PROBLEM SOLUTION
Computational tools to
help organize, search,
and understand vast
amounts of information
Collective knowledge
increases
→information
discovery gets more
difficult

56. @lazarinastoy|#brightonSEO
PROBLEM SOLUTION
We need systems that
organise documents
based on themes
(topics) and subtopics.
Current systems of
query & links are
good, but can be
limiting

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PROBLEM SOLUTION
We need topic models
that operate under
the assumption that a
document has
multiple topics.
No ability to zoom
in and out of topics
of interest,
highlighting
patterns.

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Introduction to Probabilistic Topic Models (Blei, 2012)

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Introduction to Probabilistic Topic Models (Blei, 2012)

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Topicmodelingis
patternrecognition
inlarge,text-basedcorpusesofdata.

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Itwasmadeforus.

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Inthepast20years,
a lothashappened

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2003
LDA &
Word<>Topic
inter-exchangeability
LSA &Synonyms
2007
2008
scalability
Hybrid
models
2015
2017-
Deeplearning

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Buttheproblem
wefaceremains
thesame

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So,whynottry an
ML-basedsolution?

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twomethodstokickstartthisjourney
LDA LSA

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Or,skipthecode and
jumpstraightin

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WATCHthe
detailsLATER
I’ve recorded a step-by-step
tutorial on doing topic
modelling using a no-code,
publicly-available, web-based
app using LDA.

69. @lazarinastoy|#brightonSEO
Identifytopics
ButIn a nutshell…
Crawl
Export the content
from the website
Upload+finetune
Upload the files to the
web app + finetune
Download
Download all files
Explore+Build
Explore the outcome and
build your deliverable

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Topic
models
Topicmodels

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Topicmodels
PageInfo

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JustLook at
Whatyou
achieved✨

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Saved a tonoftime
Took you less than 30 minutes. Hooray!

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Baselineoverview
You’ve got a clear overview of the main
topic clusters and their relationship

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Testedsomethingnew
Scrutinize the output.
Tell your client how you have improved on it.

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Discoverother
04

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Enter
fuzzy
matching

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A quick anddirtyway
forcalculating
similaritybetweentwostrings

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WATCHthe
detailsLATER
I’ve recorded a step-by-step
tutorial on using fuzzy
matching for things like:
● Identifying link
opportunities
● String Similarity Analysis
● Other cool things

81. @lazarinastoy|#brightonSEO
Assesssimilarity
ButIn a nutshell…
Crawl+model
Export the content
from the website +
model the topics
Organize
Choose what you want
to assess,
where to search for link
opportunities
assess
Is the page already
linked? Output good?
recommend
Provide your final list
of recommendations

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FROm/ to Similarityscore
Checkiflinkexists

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coveryourbases

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mobile
desktop
+10% +5%
Searchpilot Case Study

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howtofind
whereto
05

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Forsmallsites/
internallink
initiatives

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Formedium-sized
sites/internallink
initiatives

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Forreallybig
sites/internal
linkinitiatives

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Thelogicis
thesame

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Searchforintent-basedkeywordvariations
Searchfordifferent anchortypes
Incorporateentity-basedlinking
Think aboutmoney-makingpages

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Build
measure 06

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Whatshouldyouincludeinyour
deliverable?

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Link
Opportunities
ANALYSIS
Prioritize,
budget
TopicModels
Highlight additional
link opportunities,
anchor strategies.
Present your analysis
in a format that allows
for benchmarking
Talk about link
implementation,
timeline, tracking.
After finalising the
categories and
structure, create
custom dimensions
for the topics in
GA/GDS/GSC

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Whatshouldyou
measure?

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Yourreportingshouldinclude
Growthmetrics
benchmarking

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forgrowthreporting,track
● Quicker Indexing
● # of pages indexed
● # of pages discovered
● Organic traffic
● Inter-cluster user flow
traffic
● CTR
● Average time per
session
● Clicks
● Interactions
engagement
● # of ranking queries
● Length of queries
● Performance (visibility;
engagement, rankings)
split per topic cluster
#Queries

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104. @lazarinastoy|#brightonSEO
As
willCritchlow
explains…

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Internallinkingeffectmeasurementis
hard

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ourintuition aboutlinkstructuresis
poor

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Inotherwords…

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Failing
ispartof
theprocess.

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Aretheway
togo📈

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BeforeIgo…

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This deck,
referencedwork
ofothercoolpeople, and a
TALKwrite-up
willbe available

113. @lazarinastoy|#brightonSEO
here.
https://lazarinastoy.com/how-to
-incorporate-machine-learning-in
-internal-linking-audits/

114. @lazarinastoy|#brightonSEO
Hiring
We are a pretty awesome team on the lookout for talent.
Search for Intrepid Digital to work with some exciting US & global brands.

115. @lazarinastoy|#brightonSEO
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THANKyou.
lazarinastoy.com
@lazarinastoy
/in/lazarinastoy/