1.
@patrickstox
Data Visualization
For SEO

2.
@patrickstox
• Product Advisor, Technical SEO, &
Brand Ambassador at Ahrefs
• I write for Ahrefs blog but have written for many industry publications
in the past
• I speak at some conferences like SMX, Pubcon, UnGagged, TechSEO
Boost
• Organizer for the Raleigh SEO Meetup (most successful in US) and
the Beer & SEO Meetup
• We also run a conference, the Raleigh SEO Conference
• Founder Technical SEO Slack Group (message me for an invite)
• Moderator /r/TechSEO on Reddit
Who is Patrick Stox?

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@patrickstox
30 Minutes of Line
Charts, Bar Charts,
and Pie Charts

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@patrickstox
I’m Kidding
But they’re really useful!

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@patrickstox
The Purpose of Visualizing Data
Is to communicate information quickly and easily

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@patrickstox
How Many 42s?
2382348938390432189032195729148321428342891839489898975982439328
4892482938943278432432789327819473289432894832989848329843843897
4329843798231489431289471234078578718781927589792781957391743889
3741287894787837084731074832047301874307821074893710894731094780
8032718748930710948731087408391274081327401328743028174038912784
7310987409312874097120473102874039218474803127094731087438091748
9031748903170894738740318470835665213065712658623407263532175096
4370127495017243132054701372640731275403127460127435430715437017
5435104504137540871364071325407141350487151754075335127040743172
8540317453712754307801328534075123077431275473216754784321758043
7125481327545371275743218546125487214730125413725432574712375473
1254728135407312547231854037125737543207142754170470734127504375

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@patrickstox
How Many 42s?
23823489383904321890321957291483214283428918394898989759824393
2848924829389432784324327893278194732894328948329898483298438438
9743298437982314894312894712340785787187819275897927819573917438
8937412878947878370847310748320473018743078210748937108947310947
8080327187489307109487310874083912740813274013287430281740389127
8473109874093128740971204731028740392184748031270947310874380917
4890317489031708947387403184708356652130657126586234072635321750
9643701274950172431320547013726407312754031274601274354307154370
1754351045041375408713640713254071413504871517540753351270407431
7285403174537127543078013285340751230774312754732167547843217580
4371254813275453712757432185461254872147301254137254325747123754
731254728135407312547231854037125737543207142754170470734127504
375

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@patrickstox
You Have Data

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@patrickstox
Think About:
• What's your message
• Who is the audience
• How to present it
• Tell your story

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@patrickstox
Visualization Goals
1. Answer questions
2. Make decisions
3. Find patterns
4. Tell a story
5. Give context to data
6. Inspire

11.
@patrickstox

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@patrickstox
Line / Area Chart – Comparison - Data Over
Time

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@patrickstox
Multiple Line Chart – Comparisons /
Categories Over Time
Free competitor forecasting scripts: https://ahrefs.com/blog/seo-forecasting/

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@patrickstox
Bar - Comparison

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@patrickstox
Spark Lines – Comparison - Trends
Easy to add to spreadsheets
By Alexander Blagochevsky, RU

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@patrickstox
Venn Diagram - Comparison
Keyword Gap
User:Verycurve / CC BY-SA

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@patrickstox
Venn Diagram 4+ - Comparison
Venn's_four_ellipse_construction.svg: RupertMillard derivative work: RupertMillard / CC BY-SA

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@patrickstox
Scatter Plot – Relationship / Distribution (2)

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@patrickstox
Scatter Plot + Trend – Relationship /
Distribution (2)

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@patrickstox
Bubble Chart – Relationship (3)
Competitive
Positioning
Albin Olsson / CC BY

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@patrickstox
Box Plot - Distribution

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@patrickstox
Histogram - Distribution

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@patrickstox
Heatmap - Distribution

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@patrickstox
Heatmap - Distribution
Website clicks, scroll depth
Hotjar screenshot

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@patrickstox
Maps - Distribution
Link building
Data source: Google Trends (https://www.google.com/trends).

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@patrickstox
Stacked Bar - Composition

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@patrickstox
Pie / Donut - Composition

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@patrickstox
Waterfall - Composition
Website load
Source webpagetest.org

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@patrickstox
Bubble Chart - Composition
Keyword opportunities
Deniskk25 / CC BY-SA

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@patrickstox
Tree Map - Composition
Keyword
opportunities
R Haussman, Cesar Hidalgo, et. al. Creative Commons Attribution-Share alike 3.0
Unported license. See permission to share at:
http://atlas.media.mit.edu/about/permissions/ / CC BY-SA

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@patrickstox
Tree Map - Composition
For duplicate content clusters

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@patrickstox
Word Cloud - Composition
Dave Braunschweig / CC BY-SA

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@patrickstox
Sankey Diagram - Composition
Metrics
Site issues
Budgets
SevenandForty / CC BY-SA

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@patrickstox
Impact Effort Matrix - Process
Prioritization of tasks
Source: me

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@patrickstox
Flowcharts - Process

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@patrickstox
Gantt Charts – Process - Timelines
Dbsheajr at the English language Wikipedia / CC BY-SA

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@patrickstox
Swimlane Diagram – Process –
Responsibilities & Outcomes
Nkouroun / CC BY-SA

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@patrickstox
Chord - Relationships
Nettrom / CC BY-SA

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@patrickstox
Sketchnotes
https://twitter.com/Rhoadey/status/874777698601639936

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@patrickstox
Infographics

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@patrickstox
Force Directed Diagram – Website Crawl

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@patrickstox
Force Directed Diagram – Request Map

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@patrickstox
Tree Graph - Structure
The original uploader was Aris00 at English Wikipedia. / CC BY-SA

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@patrickstox
Network Graph - Structure
Source: me

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@patrickstox
I’ve Gone Through Types Of Graphs, But
Each Type Also Has Options

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@patrickstox
Network Graph – Structure – Data OptionsNode Size - usually represented by some kind of importance
•Internal PageRank (most linked pages internally)
•CheiRank (based on links out, so shows pages that don't link out as much)
•UR (accounts for external and internal links, most comprehensive strength metric)
•Traffic (for graphs where you want to show importance of pages)
•Traffic Value (for graphs where you want to show importance of pages)
Node Color
•Issues (can be used to show things like http vs https, 404 pages, noindexed pages, non-canonical pages, etc and helps to show scope of various
issues)
•Depth (clicks from root. While I don't personally find this important some SEOs do)
•Groups (based on website structure such as folders, based on modularity which looks at link neighborhoods, or sometimes topical groups which
requires labeling)
Line Thickness - some kind of weight importance from linking page
•Internal PageRank (most linked pages internally)
•CheiRank (based on links out, so shows pages that don't link out as much)
•UR (accounts for external and internal links, most comprehensive strength metric)
•Traffic (for graphs where you want to show importance of pages)
•Traffic Value (for graphs where you want to show importance of pages)
Line Color
•Link type (follow/nofollow, Redirect)
•Location of link (header, footer, content)
•Groups (based on website structure such as folders, based on modularity which looks at link neighborhoods, or sometimes topical groups which
requires labeling)
Distance - usually represents how well linked something is. Further from center = less links to the page.

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@patrickstox
Some Tools To Help Create Visualizations
• Excel
• Tableau
• Canva
• Python or R
• Power BI
• D3.js

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@patrickstox
I Hope You Saw Something New Here

49.
@patrickstox