The document discusses the benefits and methods of SEO automation to enhance efficiency, including tools like KNIME for data analysis and various programming languages for scripting tasks. It outlines how to automate routine SEO tasks, such as keyword research and data collection, by using APIs and scheduled scripts. Furthermore, it includes practical applications for tasks like 301 redirect mapping, performance testing, and anomaly detection in search rankings.

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SEO Automation to Increase
Efficiency & Effectiveness
Working Smarter

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Why Automate?
1.Work faster and free up time for the
important stuff
2.Look at more data
3.Improved consistency and procedure

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What Can You Automate?
• If you’re doing something on a routine
basis, it can probably be automated.
• Any procedures that can be broken down
into smaller, micro tasks that can be
handled a by a computer.
• Machine Learning can help with more
complex decision making.

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How Do You Automate?

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https://www.knime.org

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Why KNIME?
• Fast way to put together complex
analyses
• Great for prototyping
• Large library of built-in “nodes”
• Free/Open Source
• Run on Windows/Mac/Linux
• Very expandable – even compatible
with R, Python, Java, JavaScript
• Easy enough for non-technical staff
to grasp

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Other Options
• Scripting Languages
• Python
• Ruby
• Node.js
• Go
• R
• Excel with VBA
• Google Sheets

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Cron & Windows Task Manager
are Your Friend

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What is Cron and Why?
• *NIX system daemon used to schedule tasks and
scripts.
• Windows Task Manager is the Windows equivalent
of Cron.
• This way we can schedule scripts and programs that
perform automated tasks on a recurring, scheduled
basis.

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Quick How To
* * * * * command /to/execute
Day of Week (0-6) (Sunday = 0)
Month (1-12)
Hour (0-23)
Day of Month (1-31)
Minute (0-59)

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Run Every Month at Midnight
0 0 1 * * python datacollector.py

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The Basics of KNIME

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What is a Node?
• Nodes are prebuilt, drag and drop modules designed perform a singular task
• Nodes are strung together like a chain to accomplish larger, more complex
tasks
• Nodes can be grouped together into “meta-nodes”, which can be configured in
unison

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How Do You Add Nodes &
How Do They Connect?
How do you add nodes to your “workflow”?
How do you string nodes together?

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How Do You Configure & Run Nodes?
Configuring Nodes
Running Workflows
OR

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Keyword Research

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Most Keyword Research Looks Like This

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Typical Time Investment for Keyword
Research
5
8
12
21 21
6
10
18
22
28
0
5
10
15
20
25
30
Micro (0-49 pages) Small (50-99 pages) Medium (100-249 pages) Large (250-499 pages) Extra Large (>500 pages)
Hours to Complete Keyword Research by Site Size
Average (Low End) Average (High End)

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Size of the Data Set
vs.

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Filtering +
Data
Manipula-
tions
One Big Keyword List
Seed Keywords
- List
- GWMT
- SEMRush Comp. KWs
- SQR Keywords
Keyword Planner
Suggestions (via
GrepWords)
Google Autocomplete
Semantic Keyword
Recommendations
(via MarketMuse)
Google Autocomplete
SEMRush
Domain vs. Domain
Keywords
Google Autocomplete

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Data Manipulations / Calculations
• Get top 10 results from rank checking API (i.e., GetSTAT)
• Use Moz API nodes and find average PA to assess
competiveness.
• Optionally, use SEMRush’s Keyword Difficulty API
Organic
Competition
Search Volume
Keyword Trends
23

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Data Manipulations / Calculations
• Get top 10 results from rank checking API (i.e., GetSTAT)
• Use Moz API nodes and find average PA to assess
competiveness.
• Optionally, use SEMRush’s Keyword Difficulty API
Organic
Competition
• Get Search Volumes via SEMRush API or via GrepWords APISearch Volume
Keyword Trends
24

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Data Manipulations / Calculations
• Get top 10 results from rank checking API (i.e., GetSTAT)
• Use Moz API nodes and find average PA to assess
competiveness.
• Optionally, use SEMRush’s Keyword Difficulty API
Organic
Competition
• Get Search Volumes via SEMRush API or via GrepWords APISearch Volume
• Use 2 Years of Google Trends data to calculate slope and
determine growing/declining keywordsKeyword Trends
25

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String ‘em All Together and then…
26

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Visualize
27
This top-right quadrant contains
keywords with:
• Low competition
• Good growth
Larger bubbles show higher
search volumes.
You can alternatively use
current rank on the x-axis to
signal organic market share like
a traditional growth-share
matrix.

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Option: Tableau
28

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Option: Python + Bokeh Charts in KNIME
29

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Sample Python Code:
http://pshapi.ro/SLBokeh

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Learn More…
SearchLove Presentation about Automating Keyword Research:
http://pshapi.ro/2idcqYF
BrightonSEO Presentation about Semantic Keyword Research:
https://searchwilderness.com/semantic-keyword-research/

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What to Automate for SEO?

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Reporting

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Data Collection

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Search Console
Schedule to run monthly with Cron
and backup to SQL database:
https://searchwilderness.com/gwmt-
data-python/
JR’s BigQuery vision:
http://pshapi.ro/2vmjDe8

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301 Redirect Mapping
from Old URLs

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301 Redirect Mapping from Old URLs
Crawl
Current Site
Download
Rendered
Pages
Extract Main
Content
(BoilerPipe)
Convert to
Bitvector
Get Historic
URLs from
Wayback
Machine
API
Filter Out
URLs found
on Current
Site
Grab
Rendered
Page from
Wayback
Machine
Extract
Main
Content
(BoilerPipe)
Convert to
Bitvector
Patrick Stox
https://searchengineland.com/fixing-historical-redirects-using-wayback-machine-apis-257628
Cosine
Similarity
Generate
.htaccess
strings
1
2
3

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KNIME Toolkit

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SERP Similarity / Overlap

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Riyaad Edoo
1. Download ranking data via STAT
API
2. Compare results from 1-10 for
each query against results from 1-
10 for every other query.
3. Calculate percent similarity.
4. Schedule checks and examine
what changed.

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Test JavaScript Rendering

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http://pshapi.ro/puppetcrawl

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Performance Testing with
Lighthouse

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http://pshapi.ro/perfpony

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Anomaly Detection

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CTR
1. Data collection: We collect data on query,
page and associated metrics via the Google
Search Console Search Analytics API.
2. Round average position: I round average
position to the tenths decimal place (e.g., 1.19
is rounded to 1.2).
3. Math: We identify outliers using a combination
of the statistical methods for identifying
outliers (modified z-score, IQR).
4. Email: If any negative outliers are identified
for a keyword query and page combination at
an average position, an email is sent out
identifying all of this data to each of the SEOs
assigned to the account to investigate.
5. Scheduling: Set your script to run on a
recurring basis.
My SEL Article: http://pshapi.ro/2Ae2LYP

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Content Ideas

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Reddit Data Mining
Reddit Data Mining: Python Script
https://searchwilderness.com/reddit-python-code/
1. Enter filename for output
2. Enter a search or series of searches
3. Choose reddit sorting method. For this purpose,
choose ‘new’
4. Choose to look at all of reddit, or isolate to
particular subreddit(s).
5. Schedule with cron to find new topic ideas on a
recurring basis.
Password: fighto

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AMP Validation

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Bulk Check AMP
Pages with
AMPBench API
Python Script:
http://pshapi.ro/2AHlNaE
Requires:
• Python
• Requests package
Ideally AMPBench would run locally, but
can be ran off the appspot demo URL.

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Link Building

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Link Building: Prospecting with Competitors

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Tech Audit Related Site Changes

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• New 404s
• New redirects
• Changes to robots.txt
• Content based changes over time
• Indexation changes
• New pages

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CatalystDigital.com
Paul Shapiro
https://searchwilderness.com
@fighto
Thanks!